text
stringlengths 13
30k
|
|---|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4311", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/events", "html_url": "https://github.com/huggingface/datasets/pull/4311", "id": 1231369438, "node_id": "PR_kwDODunzps43ln8-", "number": 4311, "title": "[Imagefolder] Docs + Don't infer labels from file names when there are metadata + Error messages when metadata and images aren't linked correctly", "user": {"login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "closed", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["_The documentation is not available anymore as the PR was closed or merged._", "Merging this one since mario is off, I took care of adding some tests to make sure everything is fine. Will do the release after it"], "created_at": 1652197935000, "updated_at": 1652203182000, "closed_at": 1652202707000, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4311", "html_url": "https://github.com/huggingface/datasets/pull/4311", "diff_url": "https://github.com/huggingface/datasets/pull/4311.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4311.patch", "merged_at": 1652202707000}, "body": "I updated the `docs/source/image_process.mdx` documentation and added an example for image captioning and object detection using `ImageFolder`.\r\n\r\nWhile doing so I also improved a few aspects:\r\n- we don't need to infer labels from file names when there are metadata - they can just be in the metadata if necessary\r\n- raise informative error messages when metadata and images aren't linked correctly:\r\n - when an image is missing a metadata file\r\n - when a metadata file is missing an image\r\n\r\nI added some tests for these changes as well\r\n\r\ncc @mariosasko ", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4311/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4310", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/events", "html_url": "https://github.com/huggingface/datasets/issues/4310", "id": 1231319815, "node_id": "I_kwDODunzps5JZHMH", "number": 4310, "title": "Loading dataset with streaming: '_io.BufferedReader' object has no attribute 'loc'", "user": {"login": "milmin", "id": 72745467, "node_id": "MDQ6VXNlcjcyNzQ1NDY3", "avatar_url": "https://avatars.githubusercontent.com/u/72745467?v=4", "gravatar_id": "", "url": "https://api.github.com/users/milmin", "html_url": "https://github.com/milmin", "followers_url": "https://api.github.com/users/milmin/followers", "following_url": "https://api.github.com/users/milmin/following{/other_user}", "gists_url": "https://api.github.com/users/milmin/gists{/gist_id}", "starred_url": "https://api.github.com/users/milmin/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/milmin/subscriptions", "organizations_url": "https://api.github.com/users/milmin/orgs", "repos_url": "https://api.github.com/users/milmin/repos", "events_url": "https://api.github.com/users/milmin/events{/privacy}", "received_events_url": "https://api.github.com/users/milmin/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working"}], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": [], "created_at": 1652195573000, "updated_at": 1652195573000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "draft": null, "pull_request": null, "body": "## Describe the bug\r\nLoading a datasets with `load_dataset` and `streaming=True` returns `AttributeError: '_io.BufferedReader' object has no attribute 'loc'`. Notice that loading with `streaming=False` works fine.\r\n\r\nIn the following steps we load parquet files but the same happens with pickle files. The problem seems to come from `fsspec` lib, I put in the environment info also `s3fs` and `fsspec` versions since I'm loading from an s3 bucket.\r\n\r\n## Steps to reproduce the bug\r\n```python\r\nfrom datasets import load_dataset\r\n# path is the path to parquet files\r\ndata_files = {\"train\": path + \"meta_train.parquet.gzip\", \"test\": path + \"meta_test.parquet.gzip\"}\r\ndataset = load_dataset(\"parquet\", data_files=data_files, streaming=True)\r\n```\r\n\r\n## Expected results\r\nA dataset object `datasets.dataset_dict.DatasetDict`\r\n\r\n## Actual results\r\n```\r\nAttributeError Traceback (most recent call last)\r\n<command-562086> in <module>\r\n 11 \r\n 12 data_files = {\"train\": path + \"meta_train.parquet.gzip\", \"test\": path + \"meta_test.parquet.gzip\"}\r\n---> 13 dataset = load_dataset(\"parquet\", data_files=data_files, streaming=True)\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)\r\n 1679 if streaming:\r\n 1680 extend_dataset_builder_for_streaming(builder_instance, use_auth_token=use_auth_token)\r\n-> 1681 return builder_instance.as_streaming_dataset(\r\n 1682 split=split,\r\n 1683 use_auth_token=use_auth_token,\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/builder.py in as_streaming_dataset(self, split, base_path, use_auth_token)\r\n 904 )\r\n 905 self._check_manual_download(dl_manager)\r\n--> 906 splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}\r\n 907 # By default, return all splits\r\n 908 if split is None:\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/packaged_modules/parquet/parquet.py in _split_generators(self, dl_manager)\r\n 30 if not self.config.data_files:\r\n 31 raise ValueError(f\"At least one data file must be specified, but got data_files={self.config.data_files}\")\r\n---> 32 data_files = dl_manager.download_and_extract(self.config.data_files)\r\n 33 if isinstance(data_files, (str, list, tuple)):\r\n 34 files = data_files\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in download_and_extract(self, url_or_urls)\r\n 798 \r\n 799 def download_and_extract(self, url_or_urls):\r\n--> 800 return self.extract(self.download(url_or_urls))\r\n 801 \r\n 802 def iter_archive(self, urlpath_or_buf: Union[str, io.BufferedReader]) -> Iterable[Tuple]:\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in extract(self, path_or_paths)\r\n 776 \r\n 777 def extract(self, path_or_paths):\r\n--> 778 urlpaths = map_nested(self._extract, path_or_paths, map_tuple=True)\r\n 779 return urlpaths\r\n 780 \r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types, disable_tqdm, desc)\r\n 312 num_proc = 1\r\n 313 if num_proc <= 1 or len(iterable) <= num_proc:\r\n--> 314 mapped = [\r\n 315 _single_map_nested((function, obj, types, None, True, None))\r\n 316 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in <listcomp>(.0)\r\n 313 if num_proc <= 1 or len(iterable) <= num_proc:\r\n 314 mapped = [\r\n--> 315 _single_map_nested((function, obj, types, None, True, None))\r\n 316 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)\r\n 317 ]\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in _single_map_nested(args)\r\n 267 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}\r\n 268 else:\r\n--> 269 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]\r\n 270 if isinstance(data_struct, list):\r\n 271 return mapped\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in <listcomp>(.0)\r\n 267 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}\r\n 268 else:\r\n--> 269 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]\r\n 270 if isinstance(data_struct, list):\r\n 271 return mapped\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in _single_map_nested(args)\r\n 249 # Singleton first to spare some computation\r\n 250 if not isinstance(data_struct, dict) and not isinstance(data_struct, types):\r\n--> 251 return function(data_struct)\r\n 252 \r\n 253 # Reduce logging to keep things readable in multiprocessing with tqdm\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _extract(self, urlpath)\r\n 781 def _extract(self, urlpath: str) -> str:\r\n 782 urlpath = str(urlpath)\r\n--> 783 protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)\r\n 784 if protocol is None:\r\n 785 # no extraction\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _get_extraction_protocol(urlpath, use_auth_token)\r\n 371 urlpath, kwargs = urlpath, {}\r\n 372 with fsspec.open(urlpath, **kwargs) as f:\r\n--> 373 return _get_extraction_protocol_with_magic_number(f)\r\n 374 \r\n 375 \r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _get_extraction_protocol_with_magic_number(f)\r\n 335 def _get_extraction_protocol_with_magic_number(f) -> Optional[str]:\r\n 336 \"\"\"read the magic number from a file-like object and return the compression protocol\"\"\"\r\n--> 337 prev_loc = f.loc\r\n 338 magic_number = f.read(MAGIC_NUMBER_MAX_LENGTH)\r\n 339 f.seek(prev_loc)\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/fsspec/implementations/local.py in __getattr__(self, item)\r\n 337 \r\n 338 def __getattr__(self, item):\r\n--> 339 return getattr(self.f, item)\r\n 340 \r\n 341 def __enter__(self):\r\n\r\nAttributeError: '_io.BufferedReader' object has no attribute 'loc'\r\n```\r\n## Environment info\r\n- `datasets` version: 2.1.0\r\n- Platform: Linux-5.4.0-1071-aws-x86_64-with-glibc2.29\r\n- Python version: 3.8.10\r\n- PyArrow version: 8.0.0\r\n- Pandas version: 1.4.2\r\n- `fsspec` version: 2021.08.1\r\n- `s3fs` version: 2021.08.1", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4310/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/timeline", "performed_via_github_app": null, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4309", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/events", "html_url": "https://github.com/huggingface/datasets/pull/4309", "id": 1231232935, "node_id": "PR_kwDODunzps43lKpm", "number": 4309, "title": "[WIP] Add TEDLIUM dataset", "user": {"login": "sanchit-gandhi", "id": 93869735, "node_id": "U_kgDOBZhWpw", "avatar_url": "https://avatars.githubusercontent.com/u/93869735?v=4", "gravatar_id": "", "url": "https://api.github.com/users/sanchit-gandhi", "html_url": "https://github.com/sanchit-gandhi", "followers_url": "https://api.github.com/users/sanchit-gandhi/followers", "following_url": "https://api.github.com/users/sanchit-gandhi/following{/other_user}", "gists_url": "https://api.github.com/users/sanchit-gandhi/gists{/gist_id}", "starred_url": "https://api.github.com/users/sanchit-gandhi/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/sanchit-gandhi/subscriptions", "organizations_url": "https://api.github.com/users/sanchit-gandhi/orgs", "repos_url": "https://api.github.com/users/sanchit-gandhi/repos", "events_url": "https://api.github.com/users/sanchit-gandhi/events{/privacy}", "received_events_url": "https://api.github.com/users/sanchit-gandhi/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 2067376369, "node_id": "MDU6TGFiZWwyMDY3Mzc2MzY5", "url": "https://api.github.com/repos/huggingface/datasets/labels/dataset%20request", "name": "dataset request", "color": "e99695", "default": false, "description": "Requesting to add a new dataset"}, {"id": 2725241052, "node_id": "MDU6TGFiZWwyNzI1MjQxMDUy", "url": "https://api.github.com/repos/huggingface/datasets/labels/speech", "name": "speech", "color": "d93f0b", "default": false, "description": ""}], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4309). All of your documentation changes will be reflected on that endpoint.", "```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset('./datasets/tedlium', 'release1', cache_dir='/home/sanchitgandhi/cache')\r\n```\r\n\r\n```\r\nDownloading and preparing dataset tedlium/release1 to /home/sanchitgandhi/cache/tedlium/release1/1.0.1/5a9fcb97b4b52d5a1c9dc7bde4b1d5994cd89c4a3425ea36c789bf6096fee4f0...\r\nTraceback (most recent call last):\r\n File \"<string>\", line 1, in <module>\r\n File \"/home/sanchit_huggingface_co/datasets/src/datasets/load.py\", line 1703, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/home/sanchit_huggingface_co/datasets/src/datasets/builder.py\", line 605, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/home/sanchit_huggingface_co/datasets/src/datasets/builder.py\", line 1240, in _download_and_prepare\r\n raise MissingBeamOptions(\r\ndatasets.builder.MissingBeamOptions: Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided in `load_dataset` or in the builder arguments. For big datasets it has to run on large-scale data processing tools like Dataflow, Spark, etc. More information about Apache Beam runners at https://beam.apache.org/documentation/runners/capability-matrix/\r\nIf you really want to run it locally because you feel like the Dataset is small enough, you can use the local beam runner called `DirectRunner` (you may run out of memory). \r\nExample of usage: \r\n `load_dataset('tedlium', 'release1', beam_runner='DirectRunner')`\r\n```\r\nSpecifying the `beam_runner='DirectRunner'` works:\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset('./datasets/tedlium', 'release1', cache_dir='/home/sanchitgandhi/cache', beam_runner='DirectRunner')\r\n```"], "created_at": 1652191967000, "updated_at": 1652200645000, "closed_at": null, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4309", "html_url": "https://github.com/huggingface/datasets/pull/4309", "diff_url": "https://github.com/huggingface/datasets/pull/4309.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4309.patch", "merged_at": null}, "body": "Adds the TED-LIUM dataset https://www.tensorflow.org/datasets/catalog/tedlium#tedliumrelease3 \r\n\r\nTODO:\r\n\r\n- [x] Port `tedium.py` from TF datasets using `convert_dataset.sh` script\r\n- [ ] Make `load_dataset` work\r\n- [ ] Run `datasets-cli` command to generate `dataset_infos.json`\r\n- [ ] Create dummy data for continuous testing\r\n- [ ] Dummy data tests\r\n- [ ] Real data tests\r\n- [ ] Create the metadata JSON\r\n- [ ] Close PR and add directly to the Hub under LIUM org", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4309/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4308", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/events", "html_url": "https://github.com/huggingface/datasets/pull/4308", "id": 1231217783, "node_id": "PR_kwDODunzps43lHdP", "number": 4308, "title": "Remove unused multiprocessing args from test CLI", "user": {"login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4308). All of your documentation changes will be reflected on that endpoint."], "created_at": 1652191335000, "updated_at": 1652192606000, "closed_at": null, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4308", "html_url": "https://github.com/huggingface/datasets/pull/4308", "diff_url": "https://github.com/huggingface/datasets/pull/4308.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4308.patch", "merged_at": null}, "body": "Multiprocessing is not used in the test CLI.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4308/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4307", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/events", "html_url": "https://github.com/huggingface/datasets/pull/4307", "id": 1231175639, "node_id": "PR_kwDODunzps43k-Wo", "number": 4307, "title": "Add packaged builder configs to the documentation", "user": {"login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "closed", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["_The documentation is not available anymore as the PR was closed or merged._"], "created_at": 1652189659000, "updated_at": 1652191430000, "closed_at": 1652190954000, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4307", "html_url": "https://github.com/huggingface/datasets/pull/4307", "diff_url": "https://github.com/huggingface/datasets/pull/4307.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4307.patch", "merged_at": 1652190954000}, "body": "Add the packaged builders configurations to the docs reference is useful to show the list of all parameters one can use when loading data in many formats: CSV, JSON, etc.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4307/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4305", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/events", "html_url": "https://github.com/huggingface/datasets/pull/4305", "id": 1231099934, "node_id": "PR_kwDODunzps43kt4P", "number": 4305, "title": "Fixes FrugalScore", "user": {"login": "moussaKam", "id": 28675016, "node_id": "MDQ6VXNlcjI4Njc1MDE2", "avatar_url": "https://avatars.githubusercontent.com/u/28675016?v=4", "gravatar_id": "", "url": "https://api.github.com/users/moussaKam", "html_url": "https://github.com/moussaKam", "followers_url": "https://api.github.com/users/moussaKam/followers", "following_url": "https://api.github.com/users/moussaKam/following{/other_user}", "gists_url": "https://api.github.com/users/moussaKam/gists{/gist_id}", "starred_url": "https://api.github.com/users/moussaKam/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/moussaKam/subscriptions", "organizations_url": "https://api.github.com/users/moussaKam/orgs", "repos_url": "https://api.github.com/users/moussaKam/repos", "events_url": "https://api.github.com/users/moussaKam/events{/privacy}", "received_events_url": "https://api.github.com/users/moussaKam/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4305). All of your documentation changes will be reflected on that endpoint."], "created_at": 1652186646000, "updated_at": 1652187343000, "closed_at": null, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4305", "html_url": "https://github.com/huggingface/datasets/pull/4305", "diff_url": "https://github.com/huggingface/datasets/pull/4305.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4305.patch", "merged_at": null}, "body": "There are two minor modifications in this PR:\r\n1) `predictions` and `references` are swapped. Basically Frugalscore is commutative, however some tiny differences can occur if we swap the references and the predictions. I decided to swap them just to obtain the exact results as reported in the paper.\r\n2) I switched to dynamic padding that was was used in the training, forcing the padding to `max_length` introduces errors for some reason that I ignore.\r\n\r\n@lhoestq ", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4305/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4304", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4304/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4304/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4304/events", "html_url": "https://github.com/huggingface/datasets/issues/4304", "id": 1231047051, "node_id": "I_kwDODunzps5JYEmL", "number": 4304, "title": "Language code search does direct matches", "user": {"login": "leondz", "id": 121934, "node_id": "MDQ6VXNlcjEyMTkzNA==", "avatar_url": "https://avatars.githubusercontent.com/u/121934?v=4", "gravatar_id": "", "url": "https://api.github.com/users/leondz", "html_url": "https://github.com/leondz", "followers_url": "https://api.github.com/users/leondz/followers", "following_url": "https://api.github.com/users/leondz/following{/other_user}", "gists_url": "https://api.github.com/users/leondz/gists{/gist_id}", "starred_url": "https://api.github.com/users/leondz/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/leondz/subscriptions", "organizations_url": "https://api.github.com/users/leondz/orgs", "repos_url": "https://api.github.com/users/leondz/repos", "events_url": "https://api.github.com/users/leondz/events{/privacy}", "received_events_url": "https://api.github.com/users/leondz/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working"}], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Thanks for reporting ! I forwarded the issue to the front-end team :)\r\n\r\nWill keep you posted !\r\n\r\nI also changed the tagging app to suggest two letters code for now."], "created_at": 1652183956000, "updated_at": 1652186322000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "draft": null, "pull_request": null, "body": "## Describe the bug\r\n\r\nHi. Searching for bcp47 tags that are just the language prefix (e.g. `sq` or `da`) excludes datasets that have added extra information in their language metadata (e.g. `sq-AL` or `da-bornholm`). The example codes given in the [tagging app](https://huggingface.co/spaces/huggingface/datasets-tagging) encourages addition of the additional codes (\"_expected format is BCP47 tags separated for ';' e.g. 'en-US;fr-FR'_\") but this would lead to those datasets being hidden in datasets search.\r\n\r\n## Steps to reproduce the bug\r\n1. Add a dataset using a variant tag (e.g. [`sq-AL`](https://huggingface.co/datasets?languages=languages:sq-AL))\r\n2. Look for datasets using the full code \r\n3. Note that they're missing when just the language is searched for (e.g. [`sq`](https://huggingface.co/datasets?languages=languages:sq))\r\n\r\nSome datasets are already affected by this - e.g. `AmazonScience/massive` is listed under `sq-AL` but not `sq`.\r\n\r\nOne workaround is for dataset creators to add an additional root language tag to dataset YAML metadata, but it's unclear how to communicate this. It might be possible to index the search on `languagecode.split('-')[0]` but I wanted to float this issue before trying to write any code :)\r\n\r\n## Expected results\r\nDatasets using longer bcp47 tags also appear under searches for just the language code; e.g. Quebecois datasets (`fr-CA`) would come up when looking for French datasets with no region specification (`fr`), or US English (`en-US`) datasets would come up when searching for English datasets (`en`).\r\n\r\n## Actual results\r\nThe language codes seem to be directly string matched, excluding datasets with specific language tags from non-specific searches.\r\n\r\n## Environment info\r\n(web app)", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4304/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4304/timeline", "performed_via_github_app": null, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4303", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4303/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4303/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4303/events", "html_url": "https://github.com/huggingface/datasets/pull/4303", "id": 1230867728, "node_id": "PR_kwDODunzps43j8cH", "number": 4303, "title": "Fix: Add missing comma", "user": {"login": "mrm8488", "id": 3653789, "node_id": "MDQ6VXNlcjM2NTM3ODk=", "avatar_url": "https://avatars.githubusercontent.com/u/3653789?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mrm8488", "html_url": "https://github.com/mrm8488", "followers_url": "https://api.github.com/users/mrm8488/followers", "following_url": "https://api.github.com/users/mrm8488/following{/other_user}", "gists_url": "https://api.github.com/users/mrm8488/gists{/gist_id}", "starred_url": "https://api.github.com/users/mrm8488/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mrm8488/subscriptions", "organizations_url": "https://api.github.com/users/mrm8488/orgs", "repos_url": "https://api.github.com/users/mrm8488/repos", "events_url": "https://api.github.com/users/mrm8488/events{/privacy}", "received_events_url": "https://api.github.com/users/mrm8488/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": [], "created_at": 1652174498000, "updated_at": 1652174498000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4303", "html_url": "https://github.com/huggingface/datasets/pull/4303", "diff_url": "https://github.com/huggingface/datasets/pull/4303.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4303.patch", "merged_at": null}, "body": null, "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4303/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4303/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4302", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4302/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4302/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4302/events", "html_url": "https://github.com/huggingface/datasets/pull/4302", "id": 1230651117, "node_id": "PR_kwDODunzps43jPE5", "number": 4302, "title": "Remove hacking license tags when mirroring datasets on the Hub", "user": {"login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4302). All of your documentation changes will be reflected on that endpoint.", "The Hub doesn't allow these characters in the YAML tags, and git push fails if you want to push a dataset card containing these characters."], "created_at": 1652161966000, "updated_at": 1652204850000, "closed_at": null, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4302", "html_url": "https://github.com/huggingface/datasets/pull/4302", "diff_url": "https://github.com/huggingface/datasets/pull/4302.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4302.patch", "merged_at": null}, "body": "Currently, when mirroring datasets on the Hub, the license tags are hacked: removed of characters \".\" and \"$\". On the contrary, this hacking is not applied to community datasets on the Hub. This generates multiple variants of the same tag on the Hub. \r\n\r\nI guess this hacking is no longer necessary:\r\n- it is not applied to community datasets\r\n- all canonical datasets are validated by maintainers before being merged: CI + maintainers make sure license tags are the right ones\r\n\r\nFix #4298.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4302/reactions", "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4302/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"Unnamed: 0": 0, "title": "Yangliuqing", "text": "Yangliuqing () is a market town in Xiqing District, in the western suburbs of Tianjin, People's Republic of China. Despite its relatively small size, it has been named since 2006 in the \"famous historical and cultural market towns in China\". It is best known in China for creating nianhua or Yangliuqing nianhua. For more than 400 years, Yangliuqing has in effect specialised in the creation of these woodcuts for the New Year. wood block prints using vivid colourschemes to portray traditional scenes of children's games often interwoven with auspiciouse objects. , it had 27 residential communities () and 25 villages", "mpww_match": 0.0}
|
{"Unnamed: 0": 2, "title": "Yangliuqing", "text": "1,200 square meters, incorporates the elegance of imperial garden and delicacy of south garden. Now the courtyard of Shi family covers about 10,000 square meters, which is called the first mansion in North China. Now it serves as the folk custom museum in Yangliuqing, which has a large collection of folk custom museum in Yanliuqing, which has a large collection of folk art pieces like Yanliuqing New Year pictures, brick sculpture. Shi's ancestor came from Dong'e County in Shandong Province, engaged in water transport of grain. As the wealth gradually accumulated, the Shi Family moved to Yangliuqing and bought large", "mpww_match": 2.0}
|
{"Unnamed: 0": 3, "title": "Yangliuqing", "text": "tracts of land and set up their residence. Shi Yuanshi came from the fourth generation of the family, who was a successful businessman and a good household manager, and the residence was thus enlarged for several times until it acquired the present scale. It is believed to be the first mansion in the west of Tianjin. The residence is symmetric based on the axis formed by a passageway in the middle, on which there are four archways. On the east side of the courtyard, there are traditional single-story houses with rows of rooms around the four sides, which was once", "mpww_match": null}
|
{"Unnamed: 0": 4, "title": "Yangliuqing", "text": "the living area for the Shi Family. The rooms on north side were the accountants' office. On the west are the major constructions including the family hall for worshipping Buddha, theater and the south reception room. On both sides of the residence are side yard rooms for maids and servants. Today, the Shi mansion, located in the township of Yangliuqing to the west of central Tianjin, stands as a surprisingly well-preserved monument to China's pre-revolution mercantile spirit. It also serves as an on-location shoot for many of China's popular historical dramas. Many of the rooms feature period furniture, paintings and", "mpww_match": 3.0}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3659", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3659/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3659/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3659/events", "html_url": "https://github.com/huggingface/datasets/issues/3659", "id": 1120913672, "node_id": "I_kwDODunzps5Cz8kI", "number": 3659, "title": "push_to_hub but preview not working", "user": {"login": "thomas-happify", "id": 66082334, "node_id": "MDQ6VXNlcjY2MDgyMzM0", "avatar_url": "https://avatars.githubusercontent.com/u/66082334?v=4", "gravatar_id": "", "url": "https://api.github.com/users/thomas-happify", "html_url": "https://github.com/thomas-happify", "followers_url": "https://api.github.com/users/thomas-happify/followers", "following_url": "https://api.github.com/users/thomas-happify/following{/other_user}", "gists_url": "https://api.github.com/users/thomas-happify/gists{/gist_id}", "starred_url": "https://api.github.com/users/thomas-happify/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/thomas-happify/subscriptions", "organizations_url": "https://api.github.com/users/thomas-happify/orgs", "repos_url": "https://api.github.com/users/thomas-happify/repos", "events_url": "https://api.github.com/users/thomas-happify/events{/privacy}", "received_events_url": "https://api.github.com/users/thomas-happify/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 3470211881, "node_id": "LA_kwDODunzps7O1zsp", "url": "https://api.github.com/repos/huggingface/datasets/labels/dataset-viewer", "name": "dataset-viewer", "color": "E5583E", "default": false, "description": "Related to the dataset viewer on huggingface.co"}], "state": "open", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": [], "created_at": 1643732637000, "updated_at": 1643732637000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "body": "## Dataset viewer issue for '*happifyhealth/twitter_pnn*'\r\n\r\n**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/happifyhealth/twitter_pnn)*\r\n\r\nI used \r\n```\r\ndataset.push_to_hub(\"happifyhealth/twitter_pnn\")\r\n```\r\nbut the preview is not working.\r\n\r\nAm I the one who added this dataset ? Yes\r\n\r\n\r\n", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3659/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3659/timeline", "performed_via_github_app": null, "draft": null, "pull_request": {"url": "", "html_url": "", "diff_url": "", "patch_url": "", "merged_at": 0}, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3658", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3658/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3658/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3658/events", "html_url": "https://github.com/huggingface/datasets/issues/3658", "id": 1120880395, "node_id": "I_kwDODunzps5Cz0cL", "number": 3658, "title": "Dataset viewer issue for *P3*", "user": {"login": "jeffistyping", "id": 22351555, "node_id": "MDQ6VXNlcjIyMzUxNTU1", "avatar_url": "https://avatars.githubusercontent.com/u/22351555?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jeffistyping", "html_url": "https://github.com/jeffistyping", "followers_url": "https://api.github.com/users/jeffistyping/followers", "following_url": "https://api.github.com/users/jeffistyping/following{/other_user}", "gists_url": "https://api.github.com/users/jeffistyping/gists{/gist_id}", "starred_url": "https://api.github.com/users/jeffistyping/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jeffistyping/subscriptions", "organizations_url": "https://api.github.com/users/jeffistyping/orgs", "repos_url": "https://api.github.com/users/jeffistyping/repos", "events_url": "https://api.github.com/users/jeffistyping/events{/privacy}", "received_events_url": "https://api.github.com/users/jeffistyping/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 3470211881, "node_id": "LA_kwDODunzps7O1zsp", "url": "https://api.github.com/repos/huggingface/datasets/labels/dataset-viewer", "name": "dataset-viewer", "color": "E5583E", "default": false, "description": "Related to the dataset viewer on huggingface.co"}], "state": "open", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": [], "created_at": 1643731076000, "updated_at": 1643731076000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "body": "## Dataset viewer issue for '*P3*'\r\n\r\n**Link: https://huggingface.co/datasets/bigscience/P3**\r\n\r\n```\r\nStatus code: 400\r\nException: SplitsNotFoundError\r\nMessage: The split names could not be parsed from the dataset config.\r\n```\r\nAm I the one who added this dataset ? No\r\n", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3658/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3658/timeline", "performed_via_github_app": null, "draft": null, "pull_request": {"url": "", "html_url": "", "diff_url": "", "patch_url": "", "merged_at": 0}, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3656", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3656/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3656/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3656/events", "html_url": "https://github.com/huggingface/datasets/issues/3656", "id": 1120510823, "node_id": "I_kwDODunzps5CyaNn", "number": 3656, "title": "checksum error subjqa dataset", "user": {"login": "RensDimmendaal", "id": 9828683, "node_id": "MDQ6VXNlcjk4Mjg2ODM=", "avatar_url": "https://avatars.githubusercontent.com/u/9828683?v=4", "gravatar_id": "", "url": "https://api.github.com/users/RensDimmendaal", "html_url": "https://github.com/RensDimmendaal", "followers_url": "https://api.github.com/users/RensDimmendaal/followers", "following_url": "https://api.github.com/users/RensDimmendaal/following{/other_user}", "gists_url": "https://api.github.com/users/RensDimmendaal/gists{/gist_id}", "starred_url": "https://api.github.com/users/RensDimmendaal/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/RensDimmendaal/subscriptions", "organizations_url": "https://api.github.com/users/RensDimmendaal/orgs", "repos_url": "https://api.github.com/users/RensDimmendaal/repos", "events_url": "https://api.github.com/users/RensDimmendaal/events{/privacy}", "received_events_url": "https://api.github.com/users/RensDimmendaal/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working"}], "state": "open", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": [], "created_at": 1643712813000, "updated_at": 1643712813000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "body": "## Describe the bug\r\n\r\nI get a checksum error when loading the `subjqa` dataset (used in the transformers book).\r\n\r\n## Steps to reproduce the bug\r\n```python\r\nfrom datasets import load_dataset\r\nsubjqa = load_dataset(\"subjqa\",\"electronics\")\r\n```\r\n\r\n## Expected results\r\nLoading the dataset\r\n\r\n## Actual results\r\n\r\n```\r\n---------------------------------------------------------------------------\r\n\r\nNonMatchingChecksumError Traceback (most recent call last)\r\n\r\n<ipython-input-2-d2857d460155> in <module>()\r\n 2 from datasets import load_dataset\r\n 3 \r\n----> 4 subjqa = load_dataset(\"subjqa\",\"electronics\")\r\n\r\n3 frames\r\n\r\n/usr/local/lib/python3.7/dist-packages/datasets/utils/info_utils.py in verify_checksums(expected_checksums, recorded_checksums, verification_name)\r\n 38 if len(bad_urls) > 0:\r\n 39 error_msg = \"Checksums didn't match\" + for_verification_name + \":\\n\"\r\n---> 40 raise NonMatchingChecksumError(error_msg + str(bad_urls))\r\n 41 logger.info(\"All the checksums matched successfully\" + for_verification_name)\r\n 42 \r\n\r\nNonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://github.com/lewtun/SubjQA/archive/refs/heads/master.zip']\r\n```\r\n\r\n## Environment info\r\n\r\nGoogle colab\r\n\r\n- `datasets` version: 1.18.2\r\n- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic\r\n- Python version: 3.7.12\r\n- PyArrow version: 3.0.0", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3656/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3656/timeline", "performed_via_github_app": null, "draft": null, "pull_request": {"url": "", "html_url": "", "diff_url": "", "patch_url": "", "merged_at": 0}, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3655", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3655/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3655/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3655/events", "html_url": "https://github.com/huggingface/datasets/issues/3655", "id": 1119801077, "node_id": "I_kwDODunzps5Cvs71", "number": 3655, "title": "Pubmed dataset not reachable", "user": {"login": "abhi-mosaic", "id": 77638579, "node_id": "MDQ6VXNlcjc3NjM4NTc5", "avatar_url": "https://avatars.githubusercontent.com/u/77638579?v=4", "gravatar_id": "", "url": "https://api.github.com/users/abhi-mosaic", "html_url": "https://github.com/abhi-mosaic", "followers_url": "https://api.github.com/users/abhi-mosaic/followers", "following_url": "https://api.github.com/users/abhi-mosaic/following{/other_user}", "gists_url": "https://api.github.com/users/abhi-mosaic/gists{/gist_id}", "starred_url": "https://api.github.com/users/abhi-mosaic/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/abhi-mosaic/subscriptions", "organizations_url": "https://api.github.com/users/abhi-mosaic/orgs", "repos_url": "https://api.github.com/users/abhi-mosaic/repos", "events_url": "https://api.github.com/users/abhi-mosaic/events{/privacy}", "received_events_url": "https://api.github.com/users/abhi-mosaic/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working"}], "state": "open", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": [], "created_at": 1643654747000, "updated_at": 1643654747000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "body": "## Describe the bug\r\nTrying to use the `pubmed` dataset fails to reach / download the source files.\r\n\r\n## Steps to reproduce the bug\r\n```python\r\npubmed_train = datasets.load_dataset('pubmed', split='train')\r\n```\r\n\r\n## Expected results\r\nShould begin downloading the pubmed dataset.\r\n\r\n## Actual results\r\n```\r\nConnectionError: Couldn't reach ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed21n0865.xml.gz (InvalidSchema(\"No connection adapters were found for 'ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed21n0865.xml.gz'\"))\r\n```\r\n\r\n## Environment info\r\n- `datasets` version: 1.18.2\r\n- Platform: macOS-11.4-x86_64-i386-64bit\r\n- Python version: 3.8.2\r\n- PyArrow version: 6.0.0\r\n", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3655/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3655/timeline", "performed_via_github_app": null, "draft": null, "pull_request": {"url": "", "html_url": "", "diff_url": "", "patch_url": "", "merged_at": 0}, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3654", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3654/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3654/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3654/events", "html_url": "https://github.com/huggingface/datasets/pull/3654", "id": 1119717475, "node_id": "PR_kwDODunzps4x2kiX", "number": 3654, "title": "Better TQDM output", "user": {"login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": [], "created_at": 1643649763000, "updated_at": 1643723173000, "closed_at": null, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "body": "This PR does the following:\r\n* if `dataset_infos.json` exists for a dataset, uses `num_examples` to print the total number of examples that needs to be generated (in `builder.py`)\r\n* fixes `tqdm` + multiprocessing in Jupyter Notebook/Colab (the issue stems from this commit in the `tqdm` repo: https://github.com/tqdm/tqdm/commit/f7722edecc3010cb35cc1c923ac4850a76336f82) \r\n* adds the missing `drop_last_batch` and `with_ranks` params to `DatasetDict.map` \r\n* correctly computes the number of iterations in `map` and the CSV/JSON loader when `batched=True` to fix `tqdm` progress bars\r\n* removes the `bool(logging.get_verbosity() == logging.NOTSET)` (or simplifies `bool(logging.get_verbosity() == logging.NOTSET) or not utils.is_progress_bar_enabled()` to `not utils.is_progress_bar_enabled()`) condition and uses `utils.is_progress_bar_enabled` to check if `tqdm` output is enabled (this comment from @stas00 explains why the `bool(logging.get_verbosity() == logging.NOTSET)` check is problematic: https://github.com/huggingface/transformers/issues/14889#issue-1087318463)\r\n\r\nFix #2630", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3654/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3654/timeline", "performed_via_github_app": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/3654", "html_url": "https://github.com/huggingface/datasets/pull/3654", "diff_url": "https://github.com/huggingface/datasets/pull/3654.diff", "patch_url": "https://github.com/huggingface/datasets/pull/3654.patch", "merged_at": null}, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3653", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3653/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3653/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3653/events", "html_url": "https://github.com/huggingface/datasets/issues/3653", "id": 1119186952, "node_id": "I_kwDODunzps5CtXAI", "number": 3653, "title": "`to_json` in multiprocessing fashion sometimes deadlock", "user": {"login": "thomasw21", "id": 24695242, "node_id": "MDQ6VXNlcjI0Njk1MjQy", "avatar_url": "https://avatars.githubusercontent.com/u/24695242?v=4", "gravatar_id": "", "url": "https://api.github.com/users/thomasw21", "html_url": "https://github.com/thomasw21", "followers_url": "https://api.github.com/users/thomasw21/followers", "following_url": "https://api.github.com/users/thomasw21/following{/other_user}", "gists_url": "https://api.github.com/users/thomasw21/gists{/gist_id}", "starred_url": "https://api.github.com/users/thomasw21/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/thomasw21/subscriptions", "organizations_url": "https://api.github.com/users/thomasw21/orgs", "repos_url": "https://api.github.com/users/thomasw21/repos", "events_url": "https://api.github.com/users/thomasw21/events{/privacy}", "received_events_url": "https://api.github.com/users/thomasw21/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working"}], "state": "open", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": [], "created_at": 1643621707000, "updated_at": 1643621707000, "closed_at": null, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "body": "## Describe the bug\r\n\r\n`to_json` in multiprocessing fashion sometimes deadlock, instead of raising exceptions. Temporary solution is to see that it deadlocks, and then reduce the number of processes or batch size in order to reduce the memory footprint.\r\n\r\nAs @lhoestq pointed out, this might be related to https://bugs.python.org/issue22393#msg315684 where `multiprocessing` fails to raise the OOM exception. One suggested alternative is not use `concurrent.futures` instead.\r\n\r\n## Steps to reproduce the bug\r\n\r\n## Expected results\r\n\r\nScript fails when one worker hits OOM, and raise appropriate error.\r\n\r\n## Actual results\r\n\r\nDeadlock\r\n\r\n## Environment info\r\n<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->\r\n- `datasets` version: 1.8.1\r\n- Platform: Linux\r\n- Python version: 3.8\r\n- PyArrow version: 6.0.1\r\n", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3653/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3653/timeline", "performed_via_github_app": null, "draft": null, "pull_request": {"url": "", "html_url": "", "diff_url": "", "patch_url": "", "merged_at": 0}, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3652", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3652/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3652/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3652/events", "html_url": "https://github.com/huggingface/datasets/pull/3652", "id": 1118808738, "node_id": "PR_kwDODunzps4xzinr", "number": 3652, "title": "sp. Columbia => Colombia", "user": {"login": "serapio", "id": 3781280, "node_id": "MDQ6VXNlcjM3ODEyODA=", "avatar_url": "https://avatars.githubusercontent.com/u/3781280?v=4", "gravatar_id": "", "url": "https://api.github.com/users/serapio", "html_url": "https://github.com/serapio", "followers_url": "https://api.github.com/users/serapio/followers", "following_url": "https://api.github.com/users/serapio/following{/other_user}", "gists_url": "https://api.github.com/users/serapio/gists{/gist_id}", "starred_url": "https://api.github.com/users/serapio/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/serapio/subscriptions", "organizations_url": "https://api.github.com/users/serapio/orgs", "repos_url": "https://api.github.com/users/serapio/repos", "events_url": "https://api.github.com/users/serapio/events{/privacy}", "received_events_url": "https://api.github.com/users/serapio/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "closed", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": [], "created_at": 1643589663000, "updated_at": 1643617747000, "closed_at": 1643617747000, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "body": "\"Columbia\" is various places in North America. The country is \"Colombia\".", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3652/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3652/timeline", "performed_via_github_app": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/3652", "html_url": "https://github.com/huggingface/datasets/pull/3652", "diff_url": "https://github.com/huggingface/datasets/pull/3652.diff", "patch_url": "https://github.com/huggingface/datasets/pull/3652.patch", "merged_at": 1643617747000}, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3651", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3651/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3651/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3651/events", "html_url": "https://github.com/huggingface/datasets/pull/3651", "id": 1118597647, "node_id": "PR_kwDODunzps4xy3De", "number": 3651, "title": "Update link in wiki_bio dataset", "user": {"login": "jxmorris12", "id": 13238952, "node_id": "MDQ6VXNlcjEzMjM4OTUy", "avatar_url": "https://avatars.githubusercontent.com/u/13238952?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jxmorris12", "html_url": "https://github.com/jxmorris12", "followers_url": "https://api.github.com/users/jxmorris12/followers", "following_url": "https://api.github.com/users/jxmorris12/following{/other_user}", "gists_url": "https://api.github.com/users/jxmorris12/gists{/gist_id}", "starred_url": "https://api.github.com/users/jxmorris12/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jxmorris12/subscriptions", "organizations_url": "https://api.github.com/users/jxmorris12/orgs", "repos_url": "https://api.github.com/users/jxmorris12/repos", "events_url": "https://api.github.com/users/jxmorris12/events{/privacy}", "received_events_url": "https://api.github.com/users/jxmorris12/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "closed", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": ["> all the tests pass, but I'm still not able to import the dataset\r\n\r\nSince it's not merged on `master` yet, you have to provide the path to your local `wiki_bio.py` to use it.\r\nIndeed the library downloads the dataset files from `master` if you have a dev installation of the library.\r\n\r\nI agree it would be nice to change that, and use the local dataset scripts from the `datasets` directory - it feels definitely more natural.", "Cool, thanks for your help and I agree!"], "created_at": 1643560134000, "updated_at": 1643640648000, "closed_at": 1643618289000, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "body": "Fixes #3580 and makes the wiki_bio dataset work again. I changed the link and some documentation, and all the tests pass. Thanks @lhoestq for uploading the dataset to the HuggingFace data bucket.\r\n\r\n@lhoestq -- all the tests pass, but I'm still not able to import the dataset, as the old Google Drive link is cached somewhere:\r\n```python\r\n>>> from datasets import load_dataset\r\nload_dataset(\"wiki_bio>>> load_dataset(\"wiki_bio\")\r\nUsing custom data configuration default\r\nDownloading and preparing dataset wiki_bio/default (download: 318.53 MiB, generated: 736.94 MiB, post-processed: Unknown size, total: 1.03 GiB) to /home/jxm3/.cache/huggingface/datasets/wiki_bio/default/1.1.0/5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9...\r\nTraceback (most recent call last):\r\n ...\r\n File \"/home/jxm3/random/datasets/src/datasets/utils/file_utils.py\", line 612, in get_from_cache\r\n raise FileNotFoundError(f\"Couldn't find file at {url}\")\r\nFileNotFoundError: Couldn't find file at https://drive.google.com/uc?export=download&id=1L7aoUXzHPzyzQ0ns4ApBbYepsjFOtXil\r\n```\r\n\r\nwhat do I have to do to invalidate the cache and actually import the dataset? It's clearly set up correctly, since the data is downloaded and processed by the tests.\r\n\r\nAs an aside, this caching-loading-scripts behavior makes for a really bad developer experience. I just wasted an hour trying to figure out where the caching was happening and how to disable it, and I don't know. All I wanted to do was update the link and submit a pull request! I recommend that you all either change this behavior (i.e. updating the link to a dataset should \"just work\") or document it, since I couldn't find any information about this in the contributing.md or readme or anywhere else! Thanks!", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3651/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3651/timeline", "performed_via_github_app": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/3651", "html_url": "https://github.com/huggingface/datasets/pull/3651", "diff_url": "https://github.com/huggingface/datasets/pull/3651.diff", "patch_url": "https://github.com/huggingface/datasets/pull/3651.patch", "merged_at": 1643618289000}, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/3650", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/3650/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/3650/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/3650/events", "html_url": "https://github.com/huggingface/datasets/pull/3650", "id": 1118537429, "node_id": "PR_kwDODunzps4xyr2o", "number": 3650, "title": "Allow 'to_json' to run in unordered fashion in order to lower memory footprint", "user": {"login": "thomasw21", "id": 24695242, "node_id": "MDQ6VXNlcjI0Njk1MjQy", "avatar_url": "https://avatars.githubusercontent.com/u/24695242?v=4", "gravatar_id": "", "url": "https://api.github.com/users/thomasw21", "html_url": "https://github.com/thomasw21", "followers_url": "https://api.github.com/users/thomasw21/followers", "following_url": "https://api.github.com/users/thomasw21/following{/other_user}", "gists_url": "https://api.github.com/users/thomasw21/gists{/gist_id}", "starred_url": "https://api.github.com/users/thomasw21/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/thomasw21/subscriptions", "organizations_url": "https://api.github.com/users/thomasw21/orgs", "repos_url": "https://api.github.com/users/thomasw21/repos", "events_url": "https://api.github.com/users/thomasw21/events{/privacy}", "received_events_url": "https://api.github.com/users/thomasw21/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "assignees": [], "milestone": {"url": "", "html_url": "", "labels_url": "", "id": 0, "node_id": "", "number": 0, "title": "", "description": "", "creator": {"login": "", "id": 0, "node_id": "", "avatar_url": "", "gravatar_id": "", "url": "", "html_url": "", "followers_url": "", "following_url": "", "gists_url": "", "starred_url": "", "subscriptions_url": "", "organizations_url": "", "repos_url": "", "events_url": "", "received_events_url": "", "type": "", "site_admin": false}, "open_issues": 0, "closed_issues": 0, "state": "", "created_at": 0, "updated_at": 0, "due_on": 0, "closed_at": null}, "comments": ["Hi @thomasw21, I remember suggesting `imap_unordered` to @lhoestq at that time to speed up `to_json` further but after trying `pool_imap` on multiple datasets (>9GB) , memory utilisation was almost constant and we decided to go ahead with that only. \r\n\r\n1. Did you try this without `gzip`? Because `gzip` feature was introduced recently and I didn't check multi_proc thing with `gzip`. One thing I know is that `gzip` is slow in our implementation than `zip` (it's a WIP #3551) \r\n2. You can try reducing your batch size, this can also help in avoiding OOM errors!", "Thanks @bhavitvyamalik ! I see. I'm not sure this PR actually fixes things for me either (I ended up reducing the num_proc/batch_size to lower it). It does allow the process to run for longer, but I think the reason why it was waiting is that one of the process crashes .... Unfortunately I was working on a setup with a low RAM/cpu core ratio. I'm actually very surprised that it doesn't change memory utilization, otherwise I don't see the purpose of `imap_unordered` existing. I think it's main purpose are when you have high variance in samples (in terms of bytes), which causes unecessary accumulation in `imap`\r\n 1. Did not try without `gzip`\r\n 2. Yeah or `num_proc`"], "created_at": 1643548999000, "updated_at": 1643711949000, "closed_at": null, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "body": "I'm using `to_json(..., num_proc=num_proc, compressiong='gzip')` with `num_proc>1`. I'm having an issue where things seem to deadlock at some point. Eventually I see OOM. I'm guessing it's an issue where one process starts to take a long time for a specific batch, and so other process keep accumulating their results in memory.\r\n\r\nIn order to flush memory, I propose we use optional `imap_unordered`. This will prevent one process to block the other ones. The logical thinking is that index are rarily relevant, and in one wants to keep an index, one can still create another column and reconstruct from there.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/3650/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/3650/timeline", "performed_via_github_app": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/3650", "html_url": "https://github.com/huggingface/datasets/pull/3650", "diff_url": "https://github.com/huggingface/datasets/pull/3650.diff", "patch_url": "https://github.com/huggingface/datasets/pull/3650.patch", "merged_at": null}, "is_pull_request": true}
|
{"fname": 64760, "labels": "Electric_guitar,Guitar,Plucked_string_instrument,Musical_instrument,Music", "mids": "/m/02sgy,/m/0342h,/m/0fx80y,/m/04szw,/m/04rlf", "mp3": [73, 68, 51, 4, 0, 0, 0, 0, 0, 35, 84, 83, 83, 69, 0, 0, 0, 15, 0, 0, 3, 76, 97, 118, 102, 53, 55, 46, 56, 51, 46, 49, 48, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 88, 192, 0, 0, 0, 0, 0, 0, 0, 0, 0, 73, 110, 102, 111, 0, 0, 0, 15, 0, 0, 0, 50, 0, 0, 21, 204, 0, 13, 18, 18, 23, 23, 28, 28, 33, 33, 37, 37, 42, 42, 47, 47, 52, 52, 57, 57, 62, 62, 67, 67, 72, 72, 77, 77, 82, 82, 87, 87, 92, 92, 97, 97, 102, 102, 107, 107, 112, 112, 117, 117, 122, 122, 127, 127, 132, 132, 137, 137, 142, 142, 146, 146, 151, 151, 156, 156, 161, 161, 166, 166, 171, 171, 176, 176, 181, 181, 186, 186, 191, 191, 196, 196, 201, 201, 206, 206, 211, 211, 216, 216, 221, 221, 226, 226, 231, 231, 236, 236, 241, 241, 246, 246, 251, 251, 255, 255, 0, 0, 0, 0, 76, 97, 118, 99, 53, 55, 46, 49, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 36, 3, 27, 0, 0, 0, 0, 0, 0, 21, 204, 54, 96, 2, 239, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 56, 196, 0, 18, 49, 186, 149, 71, 70, 40, 0, 192, 0, 68, 17, 159, 189, 223, 247, 119, 123, 251, 158, 64, 0, 64, 134, 89, 50, 100, 195, 132, 80, 248, 6, 31, 23, 127, 169, 207, 242, 16, 132, 200, 66, 16, 132, 244, 33, 8, 79, 144, 132, 33, 39, 33, 8, 223, 35, 127, 242, 16, 80, 138, 28, 14, 6, 50, 158, 15, 135, 225, 130, 129, 142, 24, 234, 12, 116, 242, 142, 255, 254, 113, 168, 64, 1, 156, 0, 5, 11, 25, 198, 114, 222, 189, 147, 215, 113, 251, 130, 105, 198, 202, 129, 176, 255, 243, 56, 196, 22, 26, 138, 82, 213, 109, 140, 64, 0, 48, 31, 136, 208, 48, 70, 4, 172, 213, 8, 236, 145, 94, 66, 128, 176, 56, 177, 74, 78, 93, 97, 174, 97, 237, 16, 190, 6, 217, 144, 164, 45, 12, 252, 67, 251, 50, 189, 101, 110, 104, 216, 246, 33, 132, 86, 190, 154, 86, 58, 181, 120, 164, 171, 168, 98, 182, 181, 166, 190, 162, 102, 234, 191, 113, 134, 196, 205, 68, 124, 62, 38, 163, 82, 91, 215, 233, 91, 190, 110, 223, 255, 255, 245, 170, 222, 34, 211, 113, 255, 73, 204, 39, 48, 201, 255, 243, 56, 196, 10, 23, 9, 102, 254, 87, 204, 48, 2, 4, 28, 173, 96, 233, 89, 26, 181, 165, 133, 197, 67, 110, 215, 62, 13, 186, 245, 87, 181, 132, 144, 170, 170, 171, 2, 150, 255, 245, 103, 103, 146, 213, 59, 239, 61, 247, 221, 196, 79, 237, 157, 187, 181, 108, 122, 249, 157, 147, 204, 116, 48, 20, 29, 69, 128, 53, 17, 107, 64, 43, 19, 180, 52, 87, 181, 103, 86, 53, 174, 42, 219, 90, 234, 9, 220, 199, 39, 253, 19, 0, 5, 213, 29, 0, 20, 153, 0, 41, 71, 239, 177, 234, 116, 44, 255, 243, 56, 196, 12, 24, 17, 218, 210, 54, 89, 134, 176, 250, 68, 224, 25, 194, 39, 131, 225, 194, 0, 7, 192, 172, 81, 125, 78, 164, 59, 228, 55, 230, 135, 133, 231, 223, 164, 160, 31, 161, 41, 104, 68, 36, 28, 244, 108, 161, 31, 172, 53, 224, 153, 158, 249, 14, 15, 201, 18, 48, 52, 231, 164, 147, 218, 145, 2, 20, 98, 226, 163, 33, 200, 242, 89, 89, 210, 139, 89, 144, 9, 20, 86, 237, 97, 16, 58, 67, 87, 42, 142, 245, 3, 112, 58, 85, 17, 0, 26, 218, 84, 167, 66, 224, 196, 239, 255, 243, 56, 196, 10, 23, 89, 94, 226, 54, 1, 144, 22, 94, 143, 30, 112, 58, 48, 12, 3, 133, 129, 132, 161, 83, 93, 197, 134, 62, 65, 137, 33, 59, 15, 32, 56, 72, 171, 209, 142, 29, 67, 81, 201, 110, 226, 16, 95, 114, 186, 183, 122, 255, 226, 186, 157, 241, 211, 70, 157, 169, 197, 66, 239, 50, 153, 147, 147, 99, 68, 11, 88, 156, 248, 243, 9, 221, 198, 148, 138, 143, 91, 109, 27, 72, 163, 136, 55, 101, 47, 210, 194, 165, 75, 33, 74, 30, 32, 7, 238, 209, 77, 199, 231, 202, 79, 214, 255, 243, 56, 196, 11, 23, 202, 86, 222, 54, 88, 196, 248, 161, 249, 38, 144, 230, 180, 48, 71, 82, 39, 45, 230, 211, 161, 93, 4, 225, 204, 60, 54, 64, 48, 67, 147, 48, 56, 200, 68, 6, 35, 58, 71, 169, 34, 224, 232, 190, 153, 66, 195, 167, 19, 32, 146, 135, 135, 253, 90, 32, 225, 23, 101, 174, 250, 118, 237, 179, 72, 166, 60, 143, 254, 168, 100, 105, 145, 70, 19, 52, 106, 137, 72, 45, 226, 102, 0, 129, 225, 222, 73, 14, 102, 81, 244, 85, 17, 16, 118, 167, 128, 214, 7, 144, 7, 225, 255, 243, 56, 196, 10, 21, 178, 66, 222, 54, 19, 6, 61, 134, 28, 104, 218, 208, 11, 90, 59, 42, 196, 87, 95, 121, 181, 161, 221, 127, 94, 203, 60, 137, 142, 223, 8, 197, 24, 137, 92, 205, 143, 195, 23, 9, 194, 15, 118, 14, 42, 156, 207, 233, 89, 65, 75, 105, 31, 244, 252, 180, 45, 97, 77, 63, 252, 239, 20, 231, 33, 229, 250, 151, 41, 126, 127, 58, 162, 215, 168, 49, 52, 87, 99, 69, 141, 101, 187, 241, 249, 5, 89, 145, 37, 193, 251, 114, 177, 23, 3, 186, 37, 167, 194, 249, 161, 24, 255, 243, 56, 196, 18, 20, 242, 182, 229, 150, 48, 197, 10, 113, 188, 211, 96, 212, 150, 234, 55, 3, 50, 95, 196, 152, 136, 135, 100, 194, 22, 237, 83, 168, 8, 97, 42, 133, 183, 185, 219, 208, 233, 84, 191, 245, 214, 68, 101, 65, 136, 236, 231, 75, 144, 27, 34, 49, 239, 66, 41, 83, 101, 110, 150, 204, 149, 244, 255, 255, 200, 152, 203, 91, 147, 254, 154, 79, 41, 133, 0, 4, 64, 85, 25, 99, 187, 21, 171, 173, 150, 204, 114, 7, 78, 76, 98, 66, 166, 131, 237, 187, 207, 206, 187, 58, 123, 241, 255, 243, 56, 196, 29, 20, 225, 202, 210, 14, 11, 6, 60, 255, 91, 230, 75, 200, 185, 240, 198, 35, 210, 161, 184, 171, 204, 219, 134, 244, 169, 77, 139, 125, 243, 19, 254, 254, 77, 186, 226, 26, 82, 44, 95, 122, 51, 134, 23, 96, 160, 92, 218, 204, 216, 63, 62, 101, 64, 74, 245, 123, 174, 71, 255, 168, 10, 213, 142, 38, 174, 234, 169, 57, 70, 155, 177, 0, 174, 34, 15, 197, 43, 247, 184, 205, 46, 231, 150, 70, 250, 199, 246, 196, 195, 194, 71, 21, 114, 54, 198, 170, 196, 33, 33, 69, 137, 209, 255, 243, 56, 196, 40, 20, 216, 202, 246, 54, 59, 4, 114, 24, 226, 149, 49, 121, 241, 16, 96, 5, 21, 17, 18, 88, 152, 144, 73, 209, 34, 90, 121, 194, 102, 40, 88, 92, 235, 182, 162, 26, 141, 6, 168, 109, 84, 33, 233, 0, 60, 247, 43, 232, 243, 210, 10, 88, 82, 65, 101, 72, 212, 73, 223, 135, 196, 72, 170, 31, 48, 14, 22, 27, 43, 228, 88, 193, 104, 192, 207, 107, 161, 45, 52, 29, 107, 226, 17, 176, 189, 61, 186, 31, 153, 71, 79, 29, 104, 161, 217, 94, 104, 218, 142, 27, 19, 42, 255, 243, 56, 196, 51, 19, 192, 210, 234, 254, 26, 80, 68, 151, 63, 139, 12, 36, 93, 130, 138, 26, 242, 113, 208, 191, 82, 182, 184, 203, 182, 57, 20, 90, 145, 83, 158, 251, 95, 115, 106, 126, 36, 19, 130, 166, 19, 57, 102, 29, 109, 108, 219, 73, 65, 4, 73, 226, 151, 159, 186, 95, 184, 236, 105, 254, 243, 233, 111, 61, 141, 25, 133, 162, 19, 216, 75, 155, 169, 145, 128, 92, 145, 155, 191, 152, 107, 122, 18, 250, 167, 90, 35, 89, 43, 212, 138, 202, 234, 231, 234, 48, 163, 139, 80, 70, 161, 146, 255, 243, 56, 196, 67, 20, 9, 234, 214, 14, 96, 69, 12, 13, 62, 180, 92, 183, 42, 203, 242, 186, 254, 189, 142, 3, 213, 145, 34, 81, 170, 148, 167, 4, 222, 5, 244, 10, 111, 195, 132, 42, 142, 92, 109, 184, 185, 183, 214, 155, 186, 226, 115, 39, 74, 18, 148, 224, 140, 8, 49, 153, 216, 204, 59, 126, 197, 49, 238, 27, 211, 182, 69, 240, 228, 230, 153, 178, 197, 244, 4, 45, 134, 121, 129, 187, 103, 139, 10, 177, 225, 4, 21, 46, 215, 28, 114, 24, 167, 174, 206, 181, 178, 173, 143, 119, 173, 231, 255, 243, 56, 196, 81, 21, 65, 66, 230, 54, 97, 134, 210, 29, 255, 235, 147, 176, 128, 0, 42, 80, 57, 199, 245, 74, 51, 154, 202, 38, 106, 96, 28, 157, 30, 42, 107, 26, 131, 132, 97, 238, 21, 68, 243, 67, 133, 117, 4, 69, 194, 17, 200, 136, 140, 132, 66, 16, 148, 36, 136, 163, 175, 237, 189, 243, 38, 83, 114, 55, 158, 61, 145, 214, 142, 202, 164, 179, 203, 245, 187, 245, 122, 255, 195, 158, 83, 26, 57, 86, 88, 24, 226, 195, 123, 47, 145, 253, 7, 21, 29, 66, 210, 26, 129, 55, 131, 105, 255, 243, 56, 196, 91, 20, 146, 62, 218, 54, 72, 196, 212, 162, 56, 178, 26, 51, 168, 23, 129, 197, 74, 218, 42, 159, 215, 83, 94, 182, 244, 52, 84, 173, 224, 215, 97, 164, 164, 231, 99, 115, 172, 92, 166, 9, 56, 92, 232, 99, 203, 163, 29, 30, 212, 45, 72, 242, 29, 115, 23, 217, 213, 211, 178, 149, 41, 226, 223, 163, 58, 36, 177, 5, 83, 8, 159, 242, 109, 28, 225, 105, 243, 235, 74, 254, 143, 255, 90, 51, 216, 153, 165, 41, 193, 218, 57, 160, 224, 88, 144, 76, 8, 27, 250, 148, 203, 73, 255, 243, 56, 196, 103, 20, 233, 250, 222, 54, 3, 10, 28, 216, 141, 237, 249, 72, 89, 62, 170, 238, 183, 193, 25, 93, 199, 23, 147, 142, 251, 209, 119, 230, 233, 95, 250, 59, 78, 109, 106, 65, 179, 99, 222, 31, 181, 156, 9, 119, 143, 147, 159, 127, 92, 231, 220, 105, 117, 153, 214, 39, 159, 142, 5, 143, 88, 199, 12, 227, 177, 102, 184, 103, 117, 9, 214, 178, 143, 109, 255, 246, 77, 85, 157, 194, 50, 52, 19, 48, 255, 21, 51, 165, 69, 232, 239, 74, 171, 84, 108, 33, 116, 203, 74, 159, 40, 65, 255, 243, 56, 196, 114, 22, 73, 162, 229, 150, 19, 12, 86, 234, 223, 42, 196, 59, 209, 20, 120, 195, 77, 2, 161, 60, 150, 223, 44, 24, 72, 77, 103, 116, 186, 42, 207, 249, 54, 218, 231, 113, 126, 31, 29, 145, 207, 134, 20, 215, 42, 94, 154, 44, 40, 189, 190, 8, 138, 227, 239, 77, 114, 56, 189, 152, 93, 219, 252, 189, 69, 94, 197, 33, 101, 88, 125, 192, 89, 203, 178, 15, 88, 13, 7, 55, 150, 98, 89, 216, 133, 41, 10, 28, 176, 105, 32, 2, 184, 255, 221, 175, 44, 179, 169, 82, 173, 42, 255, 243, 56, 196, 119, 25, 218, 10, 206, 46, 121, 134, 240, 214, 16, 104, 191, 174, 9, 233, 244, 108, 176, 54, 117, 38, 170, 198, 115, 145, 38, 146, 17, 64, 53, 222, 9, 13, 17, 141, 121, 123, 40, 32, 62, 207, 58, 64, 40, 140, 88, 217, 153, 14, 145, 223, 200, 149, 122, 238, 108, 254, 155, 172, 126, 215, 28, 88, 233, 107, 177, 65, 55, 200, 123, 100, 119, 59, 40, 219, 101, 115, 144, 105, 20, 78, 83, 140, 88, 134, 12, 180, 82, 39, 152, 206, 175, 162, 212, 100, 209, 125, 220, 189, 160, 223, 101, 72, 255, 243, 56, 196, 110, 28, 162, 178, 198, 22, 122, 4, 252, 254, 100, 80, 233, 90, 12, 33, 116, 21, 128, 167, 135, 255, 230, 60, 157, 117, 1, 213, 236, 117, 109, 141, 34, 79, 5, 1, 234, 247, 20, 111, 251, 130, 34, 148, 217, 82, 21, 196, 121, 85, 185, 41, 105, 131, 137, 178, 71, 24, 168, 134, 48, 250, 155, 46, 96, 101, 164, 25, 215, 220, 41, 83, 206, 251, 84, 43, 70, 151, 111, 87, 35, 207, 14, 28, 99, 53, 190, 103, 63, 17, 81, 163, 57, 74, 167, 116, 19, 17, 82, 50, 158, 233, 219, 70, 255, 243, 56, 196, 90, 27, 243, 30, 206, 54, 122, 10, 253, 56, 89, 223, 63, 56, 131, 37, 52, 214, 211, 145, 8, 117, 67, 191, 111, 175, 239, 226, 14, 42, 34, 30, 36, 96, 137, 212, 73, 220, 63, 240, 165, 146, 53, 108, 229, 150, 230, 51, 122, 36, 189, 116, 120, 151, 113, 173, 61, 183, 236, 222, 178, 157, 143, 6, 214, 41, 203, 200, 203, 42, 54, 81, 181, 45, 178, 221, 66, 37, 189, 75, 140, 247, 64, 122, 177, 102, 91, 88, 43, 19, 63, 95, 163, 168, 65, 113, 149, 4, 3, 112, 130, 197, 3, 86, 255, 243, 56, 196, 73, 25, 114, 174, 222, 86, 121, 133, 8, 81, 1, 20, 135, 59, 89, 234, 108, 221, 211, 105, 237, 70, 182, 220, 200, 205, 239, 111, 99, 13, 30, 0, 219, 69, 156, 185, 148, 34, 11, 82, 16, 15, 173, 4, 239, 8, 219, 17, 71, 155, 226, 169, 139, 130, 156, 180, 166, 141, 46, 85, 217, 201, 36, 30, 181, 31, 101, 132, 227, 46, 116, 77, 50, 56, 8, 220, 147, 192, 204, 169, 145, 36, 247, 15, 5, 25, 79, 255, 221, 144, 223, 239, 39, 13, 255, 58, 173, 11, 221, 118, 50, 255, 57, 51, 255, 243, 56, 196, 66, 22, 89, 230, 222, 214, 3, 6, 28, 19, 6, 150, 153, 120, 170, 214, 84, 96, 245, 20, 131, 205, 26, 171, 93, 125, 13, 151, 255, 233, 36, 225, 213, 17, 36, 215, 110, 148, 168, 255, 182, 50, 218, 150, 23, 52, 161, 82, 134, 228, 35, 37, 213, 169, 89, 253, 115, 106, 26, 69, 50, 237, 251, 155, 148, 7, 139, 76, 135, 6, 56, 33, 168, 101, 102, 184, 138, 43, 25, 140, 65, 182, 92, 137, 123, 246, 33, 142, 139, 255, 214, 28, 176, 237, 66, 130, 16, 22, 98, 41, 207, 82, 163, 237, 255, 243, 56, 196, 71, 23, 138, 102, 226, 46, 75, 196, 170, 58, 102, 119, 71, 250, 91, 5, 71, 90, 172, 84, 115, 139, 17, 188, 218, 45, 233, 255, 73, 101, 4, 198, 42, 24, 192, 64, 117, 240, 41, 7, 244, 65, 218, 129, 168, 150, 136, 239, 155, 250, 212, 38, 81, 205, 190, 237, 75, 97, 202, 142, 48, 53, 180, 69, 74, 151, 191, 28, 138, 12, 88, 60, 118, 77, 81, 42, 155, 19, 219, 168, 120, 10, 21, 162, 53, 66, 253, 8, 241, 47, 247, 33, 218, 244, 189, 32, 0, 136, 210, 43, 48, 48, 131, 200, 255, 243, 56, 196, 71, 22, 241, 94, 214, 78, 67, 6, 92, 177, 163, 11, 32, 227, 134, 83, 176, 203, 105, 164, 206, 245, 185, 65, 243, 174, 87, 94, 87, 162, 113, 18, 161, 233, 132, 167, 4, 206, 63, 99, 217, 108, 121, 69, 16, 145, 94, 78, 177, 131, 8, 228, 22, 155, 169, 162, 151, 16, 33, 179, 76, 2, 40, 57, 86, 165, 196, 99, 56, 105, 91, 179, 89, 74, 47, 167, 78, 194, 77, 104, 212, 165, 192, 196, 169, 28, 67, 240, 70, 187, 148, 194, 102, 69, 30, 230, 225, 87, 74, 141, 19, 127, 50, 185, 255, 243, 56, 196, 74, 21, 217, 90, 230, 54, 98, 6, 210, 71, 196, 177, 138, 66, 40, 54, 133, 134, 99, 255, 165, 226, 245, 176, 65, 158, 31, 11, 188, 254, 208, 81, 23, 1, 96, 100, 124, 49, 84, 135, 131, 59, 34, 211, 220, 133, 197, 143, 10, 51, 64, 64, 128, 71, 62, 130, 22, 23, 206, 166, 58, 146, 169, 81, 106, 33, 12, 225, 125, 185, 82, 174, 180, 105, 220, 210, 18, 59, 171, 81, 172, 48, 120, 138, 185, 217, 136, 34, 143, 87, 90, 100, 107, 58, 116, 68, 186, 107, 246, 217, 35, 78, 28, 0, 255, 243, 56, 196, 81, 22, 146, 78, 205, 100, 88, 203, 17, 27, 61, 230, 229, 189, 217, 95, 243, 231, 21, 181, 32, 4, 80, 204, 6, 92, 63, 167, 166, 42, 74, 40, 233, 61, 101, 4, 82, 61, 173, 174, 206, 155, 10, 116, 66, 33, 230, 227, 90, 192, 153, 75, 129, 121, 174, 120, 163, 63, 22, 162, 66, 79, 165, 100, 42, 195, 250, 102, 251, 82, 81, 210, 28, 195, 243, 161, 66, 250, 212, 198, 181, 93, 10, 99, 110, 204, 228, 244, 80, 238, 155, 157, 87, 66, 122, 191, 93, 156, 73, 212, 61, 129, 82, 139, 255, 243, 56, 196, 85, 23, 242, 94, 222, 86, 72, 197, 44, 112, 232, 197, 139, 147, 22, 248, 2, 134, 94, 81, 56, 70, 5, 32, 253, 164, 158, 140, 116, 26, 56, 33, 53, 106, 17, 208, 39, 178, 21, 64, 121, 22, 113, 160, 122, 36, 89, 149, 150, 9, 37, 41, 17, 96, 135, 117, 54, 243, 135, 94, 164, 249, 196, 15, 181, 74, 111, 153, 173, 159, 251, 142, 149, 233, 192, 225, 84, 3, 121, 23, 204, 180, 60, 247, 224, 118, 215, 164, 50, 176, 40, 158, 213, 228, 73, 49, 75, 122, 117, 254, 141, 74, 8, 120, 255, 243, 56, 196, 84, 20, 89, 162, 217, 78, 65, 70, 232, 83, 60, 192, 83, 226, 208, 44, 74, 120, 1, 196, 167, 132, 115, 96, 182, 6, 28, 171, 83, 231, 158, 133, 89, 80, 167, 182, 208, 158, 54, 84, 65, 169, 104, 7, 190, 231, 159, 198, 10, 169, 242, 45, 198, 249, 135, 51, 232, 83, 69, 183, 180, 220, 155, 44, 254, 85, 4, 160, 152, 184, 64, 72, 134, 134, 29, 5, 210, 76, 152, 68, 0, 57, 241, 180, 172, 250, 168, 102, 183, 46, 215, 208, 223, 183, 247, 169, 117, 120, 104, 85, 102, 73, 252, 187, 255, 243, 56, 196, 97, 22, 89, 138, 222, 182, 3, 6, 28, 248, 248, 202, 9, 140, 130, 77, 20, 142, 226, 242, 82, 70, 48, 249, 240, 218, 144, 172, 171, 180, 233, 131, 189, 26, 59, 163, 85, 25, 137, 149, 253, 132, 199, 185, 76, 135, 92, 136, 172, 6, 108, 125, 16, 94, 71, 28, 132, 31, 153, 229, 229, 230, 161, 157, 101, 55, 156, 97, 23, 255, 253, 1, 1, 216, 132, 49, 121, 40, 227, 107, 84, 247, 99, 127, 126, 213, 158, 0, 151, 32, 18, 232, 248, 120, 140, 25, 168, 229, 115, 213, 102, 80, 104, 139, 255, 243, 56, 196, 102, 20, 226, 62, 238, 246, 88, 71, 52, 227, 160, 198, 69, 13, 113, 127, 190, 24, 17, 15, 219, 111, 235, 217, 223, 188, 33, 148, 249, 50, 37, 108, 68, 234, 194, 172, 136, 91, 89, 89, 255, 177, 68, 46, 204, 87, 114, 9, 145, 12, 145, 78, 74, 118, 203, 141, 97, 67, 128, 146, 147, 110, 5, 103, 93, 12, 186, 148, 84, 255, 127, 234, 105, 181, 141, 165, 9, 113, 244, 37, 56, 62, 59, 33, 157, 101, 210, 126, 146, 68, 192, 81, 30, 111, 188, 145, 118, 182, 201, 73, 200, 138, 131, 203, 255, 243, 56, 196, 113, 20, 161, 166, 218, 22, 89, 132, 208, 105, 98, 90, 3, 234, 24, 246, 50, 99, 243, 209, 153, 157, 60, 8, 237, 4, 168, 213, 22, 41, 29, 47, 107, 184, 210, 6, 27, 71, 114, 105, 32, 130, 168, 116, 110, 214, 147, 130, 9, 255, 119, 126, 182, 220, 178, 201, 125, 116, 255, 90, 21, 60, 1, 140, 31, 250, 77, 105, 66, 168, 246, 209, 17, 96, 192, 41, 151, 184, 19, 192, 170, 11, 38, 222, 219, 99, 159, 220, 203, 148, 155, 166, 123, 236, 73, 125, 241, 202, 28, 100, 225, 204, 145, 244, 255, 243, 56, 196, 125, 20, 81, 58, 242, 86, 89, 133, 38, 206, 100, 111, 104, 82, 254, 110, 105, 112, 95, 179, 204, 50, 34, 154, 12, 3, 68, 70, 123, 33, 5, 22, 63, 199, 26, 116, 200, 202, 8, 219, 216, 137, 168, 192, 4, 253, 254, 165, 19, 98, 72, 113, 220, 5, 222, 63, 173, 84, 48, 48, 7, 26, 186, 65, 199, 194, 94, 43, 68, 14, 177, 41, 144, 215, 34, 81, 212, 82, 177, 2, 37, 96, 3, 62, 222, 115, 20, 100, 164, 178, 208, 108, 95, 49, 228, 238, 189, 225, 201, 195, 234, 244, 170, 183, 255, 243, 56, 196, 138, 20, 98, 10, 209, 100, 73, 134, 236, 162, 159, 75, 54, 253, 36, 77, 221, 218, 201, 244, 164, 250, 24, 64, 106, 123, 77, 44, 125, 5, 89, 53, 223, 236, 216, 241, 85, 18, 54, 73, 81, 28, 10, 76, 61, 8, 68, 193, 131, 130, 194, 148, 129, 108, 153, 40, 191, 201, 105, 53, 108, 70, 52, 137, 4, 90, 165, 228, 228, 132, 227, 103, 70, 187, 194, 14, 15, 83, 149, 76, 233, 71, 156, 168, 213, 193, 35, 25, 200, 78, 154, 208, 17, 166, 127, 66, 158, 205, 179, 107, 171, 151, 14, 143, 255, 243, 56, 196, 151, 20, 226, 70, 230, 86, 64, 197, 16, 26, 210, 162, 239, 152, 50, 46, 48, 38, 8, 31, 4, 40, 50, 245, 166, 150, 205, 255, 252, 106, 22, 57, 46, 255, 233, 187, 134, 36, 234, 212, 236, 7, 169, 105, 0, 0, 137, 92, 156, 211, 129, 12, 113, 166, 75, 69, 86, 228, 21, 113, 54, 81, 96, 27, 69, 87, 52, 130, 192, 100, 119, 40, 106, 59, 136, 31, 179, 37, 17, 214, 37, 43, 33, 211, 191, 184, 197, 70, 179, 13, 134, 172, 106, 202, 44, 136, 68, 29, 48, 92, 249, 229, 63, 62, 255, 243, 56, 196, 162, 21, 233, 254, 226, 86, 57, 132, 116, 55, 189, 131, 105, 249, 179, 192, 113, 94, 197, 47, 21, 113, 150, 197, 197, 106, 8, 66, 66, 144, 155, 18, 238, 9, 33, 61, 221, 68, 67, 9, 139, 138, 135, 198, 0, 108, 23, 37, 173, 50, 132, 15, 6, 171, 19, 29, 203, 179, 89, 131, 32, 224, 254, 170, 25, 149, 89, 97, 16, 162, 45, 142, 193, 160, 43, 12, 141, 64, 113, 37, 237, 22, 125, 128, 36, 0, 146, 203, 4, 48, 42, 24, 108, 35, 75, 60, 144, 163, 235, 33, 20, 246, 94, 226, 255, 243, 56, 196, 169, 22, 145, 151, 2, 54, 2, 74, 26, 90, 255, 214, 118, 138, 218, 148, 140, 154, 128, 43, 198, 69, 74, 180, 158, 24, 42, 134, 72, 128, 181, 16, 42, 83, 164, 70, 74, 19, 69, 132, 9, 208, 44, 18, 221, 213, 55, 115, 40, 93, 164, 236, 6, 152, 36, 86, 47, 144, 76, 129, 2, 9, 141, 50, 113, 226, 129, 100, 23, 65, 103, 164, 48, 86, 96, 31, 40, 114, 47, 63, 26, 130, 13, 73, 250, 62, 133, 13, 26, 141, 191, 39, 165, 191, 212, 66, 209, 192, 97, 122, 180, 16, 6, 130, 255, 243, 56, 196, 173, 20, 161, 18, 222, 214, 3, 6, 20, 86, 25, 57, 70, 123, 14, 122, 98, 195, 179, 38, 8, 81, 46, 0, 6, 173, 91, 155, 16, 48, 154, 226, 140, 51, 82, 14, 30, 185, 97, 45, 191, 11, 16, 219, 223, 51, 74, 200, 86, 157, 58, 86, 159, 161, 247, 246, 248, 59, 175, 239, 199, 65, 19, 205, 212, 241, 228, 45, 239, 130, 189, 240, 150, 90, 127, 240, 184, 94, 77, 14, 12, 73, 93, 207, 70, 215, 165, 63, 254, 133, 13, 85, 21, 4, 64, 45, 5, 56, 255, 105, 203, 121, 97, 41, 255, 243, 56, 196, 185, 21, 97, 50, 222, 54, 10, 70, 24, 194, 126, 36, 38, 230, 32, 84, 150, 183, 140, 64, 236, 149, 26, 255, 246, 46, 40, 57, 217, 151, 26, 32, 184, 155, 63, 116, 185, 85, 163, 237, 228, 222, 85, 21, 210, 227, 177, 76, 70, 103, 49, 97, 237, 117, 41, 57, 5, 33, 181, 74, 89, 23, 54, 220, 169, 181, 50, 52, 191, 78, 255, 94, 53, 214, 183, 235, 185, 19, 13, 26, 57, 9, 82, 96, 160, 2, 188, 92, 158, 62, 65, 143, 217, 209, 89, 90, 193, 140, 102, 26, 134, 230, 26, 43, 255, 243, 56, 196, 194, 21, 170, 90, 218, 14, 9, 134, 24, 252, 44, 161, 98, 139, 3, 170, 180, 24, 132, 30, 218, 185, 179, 30, 203, 206, 59, 89, 20, 166, 22, 149, 247, 203, 34, 238, 187, 89, 70, 65, 44, 146, 24, 24, 144, 73, 42, 189, 10, 98, 13, 146, 242, 50, 200, 17, 166, 81, 238, 79, 172, 251, 227, 188, 194, 9, 106, 46, 116, 145, 197, 170, 22, 78, 239, 255, 233, 203, 199, 218, 116, 164, 112, 132, 10, 49, 58, 4, 252, 60, 236, 138, 122, 52, 145, 132, 247, 124, 26, 72, 117, 104, 231, 173, 255, 243, 56, 196, 202, 20, 242, 170, 222, 46, 65, 132, 176, 254, 197, 160, 252, 141, 253, 42, 30, 120, 234, 252, 99, 51, 19, 199, 84, 30, 201, 70, 186, 112, 84, 255, 101, 211, 150, 51, 55, 162, 108, 154, 82, 138, 168, 75, 16, 2, 8, 26, 132, 59, 91, 139, 6, 216, 100, 11, 94, 165, 120, 186, 129, 66, 142, 6, 97, 164, 50, 37, 56, 41, 176, 231, 54, 20, 202, 23, 227, 153, 225, 88, 34, 172, 208, 99, 43, 35, 225, 55, 9, 52, 219, 187, 209, 145, 137, 112, 106, 73, 59, 178, 189, 76, 5, 139, 255, 243, 56, 196, 213, 21, 73, 158, 222, 150, 2, 196, 28, 24, 210, 48, 228, 168, 178, 139, 33, 180, 20, 70, 65, 198, 209, 220, 96, 113, 29, 204, 84, 151, 8, 49, 191, 203, 109, 214, 72, 243, 177, 147, 230, 214, 203, 169, 81, 44, 95, 167, 226, 76, 53, 9, 61, 213, 93, 29, 246, 117, 183, 85, 84, 68, 100, 97, 152, 119, 36, 167, 81, 61, 51, 90, 81, 81, 121, 74, 0, 165, 19, 56, 85, 94, 181, 148, 165, 234, 224, 114, 68, 28, 8, 104, 218, 97, 172, 142, 71, 211, 57, 110, 56, 239, 36, 67, 255, 243, 56, 196, 222, 21, 129, 175, 6, 54, 106, 68, 150, 135, 193, 184, 56, 188, 12, 135, 114, 5, 61, 239, 79, 248, 198, 19, 148, 169, 77, 161, 150, 34, 30, 167, 184, 81, 90, 222, 160, 137, 210, 33, 150, 149, 11, 128, 19, 20, 223, 20, 114, 81, 242, 71, 222, 133, 235, 173, 172, 177, 201, 107, 122, 63, 143, 89, 80, 16, 98, 102, 2, 231, 31, 209, 161, 88, 0, 60, 170, 254, 101, 216, 84, 185, 133, 202, 35, 79, 168, 208, 62, 86, 159, 86, 76, 26, 226, 17, 228, 61, 238, 68, 13, 9, 7, 165, 255, 243, 56, 196, 231, 25, 186, 202, 226, 246, 11, 202, 56, 204, 209, 87, 250, 9, 250, 70, 177, 252, 198, 211, 125, 56, 223, 87, 179, 29, 170, 80, 103, 223, 255, 88, 217, 175, 208, 117, 77, 16, 114, 14, 159, 72, 24, 141, 44, 32, 14, 24, 40, 180, 71, 234, 5, 132, 46, 138, 26, 72, 112, 105, 70, 159, 128, 54, 51, 241, 252, 44, 57, 42, 29, 138, 161, 72, 240, 171, 197, 205, 153, 83, 23, 49, 177, 65, 147, 228, 24, 30, 81, 132, 4, 236, 28, 53, 157, 60, 77, 247, 39, 136, 123, 25, 195, 59, 255, 243, 56, 196, 223, 21, 193, 82, 222, 214, 96, 203, 12, 232, 13, 222, 66, 21, 217, 14, 142, 180, 74, 109, 207, 179, 167, 209, 211, 251, 36, 102, 170, 28, 181, 75, 140, 229, 132, 113, 129, 5, 138, 178, 228, 19, 220, 65, 189, 86, 54, 63, 34, 116, 113, 175, 27, 223, 208, 167, 213, 17, 128, 73, 128, 157, 31, 244, 150, 61, 152, 212, 208, 7, 24, 68, 136, 218, 16, 89, 25, 96, 140, 70, 143, 172, 112, 180, 161, 69, 227, 233, 151, 255, 76, 95, 159, 108, 2, 82, 220, 224, 236, 245, 154, 97, 224, 91, 255, 243, 56, 196, 231, 25, 89, 210, 218, 214, 75, 208, 192, 171, 241, 243, 115, 14, 80, 99, 139, 36, 147, 98, 108, 141, 208, 130, 163, 156, 93, 220, 38, 30, 23, 65, 33, 132, 35, 144, 157, 23, 122, 50, 163, 216, 100, 138, 61, 59, 116, 101, 197, 203, 98, 215, 172, 2, 92, 155, 207, 151, 62, 20, 127, 75, 28, 171, 80, 120, 216, 1, 17, 146, 4, 192, 94, 25, 42, 24, 147, 191, 224, 232, 137, 6, 63, 79, 229, 230, 191, 201, 126, 169, 105, 179, 169, 253, 54, 22, 70, 130, 129, 156, 248, 23, 110, 190, 255, 243, 56, 196, 224, 20, 73, 182, 226, 78, 2, 68, 28, 97, 97, 247, 244, 29, 242, 101, 221, 125, 180, 247, 220, 17, 5, 63, 241, 28, 35, 38, 99, 164, 23, 6, 246, 155, 193, 110, 28, 241, 27, 152, 22, 35, 9, 38, 213, 7, 44, 79, 99, 190, 105, 4, 201, 62, 228, 255, 120, 250, 85, 185, 18, 13, 128, 167, 31, 230, 149, 88, 129, 17, 191, 193, 47, 228, 49, 229, 222, 235, 48, 151, 220, 41, 109, 111, 112, 7, 44, 129, 208, 113, 104, 215, 82, 140, 70, 50, 89, 198, 7, 5, 204, 227, 154, 33, 255, 243, 56, 196, 237, 26, 114, 74, 206, 14, 73, 138, 212, 49, 209, 17, 68, 17, 17, 82, 165, 22, 242, 173, 164, 71, 33, 159, 32, 211, 34, 85, 157, 136, 83, 69, 134, 153, 119, 51, 169, 8, 201, 106, 236, 246, 158, 126, 166, 245, 184, 211, 45, 20, 27, 21, 42, 203, 16, 44, 197, 139, 255, 78, 217, 20, 136, 149, 252, 51, 203, 246, 243, 140, 253, 214, 16, 102, 83, 12, 148, 229, 58, 65, 96, 42, 158, 113, 254, 22, 112, 246, 9, 164, 9, 198, 60, 109, 153, 9, 144, 27, 10, 147, 177, 72, 72, 80, 255, 243, 56, 196, 226, 21, 81, 194, 214, 14, 3, 6, 28, 213, 221, 173, 6, 167, 153, 254, 163, 22, 180, 48, 170, 52, 212, 231, 65, 114, 215, 174, 184, 237, 47, 11, 181, 218, 45, 226, 232, 202, 103, 66, 142, 85, 111, 245, 174, 188, 102, 99, 176, 231, 87, 185, 143, 94, 94, 171, 156, 208, 154, 64, 254, 185, 246, 193, 218, 147, 54, 196, 100, 228, 22, 52, 233, 250, 115, 70, 125, 42, 4, 127, 42, 148, 170, 150, 223, 253, 160, 231, 95, 159, 144, 219, 73, 227, 185, 176, 205, 122, 63, 120, 100, 213, 74, 152, 255, 243, 56, 196, 235, 24, 210, 70, 214, 15, 79, 40, 0, 90, 130, 188, 171, 150, 74, 215, 255, 255, 255, 252, 116, 246, 161, 230, 178, 127, 175, 76, 102, 244, 131, 54, 37, 131, 24, 90, 96, 127, 250, 85, 0, 177, 149, 39, 21, 87, 140, 117, 117, 1, 18, 187, 1, 1, 16, 96, 35, 80, 21, 17, 12, 6, 184, 150, 29, 172, 53, 253, 110, 253, 11, 13, 114, 63, 14, 172, 239, 255, 150, 243, 219, 132, 74, 127, 226, 85, 157, 255, 242, 74, 76, 65, 77, 69, 51, 46, 49, 48, 48, 170, 170, 170, 170, 170, 255, 243, 56, 196, 230, 41, 82, 198, 168, 1, 152, 120, 0, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 255, 243, 56, 196, 159, 12, 88, 102, 24, 87, 195, 24, 0, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170]}
|
{"fname": 16399, "labels": "Electric_guitar,Guitar,Plucked_string_instrument,Musical_instrument,Music", "mids": "/m/02sgy,/m/0342h,/m/0fx80y,/m/04szw,/m/04rlf", "mp3": [73, 68, 51, 4, 0, 0, 0, 0, 0, 35, 84, 83, 83, 69, 0, 0, 0, 15, 0, 0, 3, 76, 97, 118, 102, 53, 55, 46, 56, 51, 46, 49, 48, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 88, 192, 0, 0, 0, 0, 0, 0, 0, 0, 0, 73, 110, 102, 111, 0, 0, 0, 15, 0, 0, 0, 46, 0, 0, 20, 28, 0, 14, 14, 19, 19, 25, 25, 30, 30, 35, 35, 41, 41, 41, 46, 46, 51, 51, 57, 57, 62, 62, 68, 68, 73, 73, 73, 78, 78, 84, 84, 89, 89, 94, 94, 100, 100, 105, 105, 105, 110, 110, 116, 116, 121, 121, 127, 127, 132, 132, 137, 137, 137, 143, 143, 148, 148, 153, 153, 159, 159, 164, 164, 164, 170, 170, 175, 175, 180, 180, 186, 186, 191, 191, 196, 196, 196, 202, 202, 207, 207, 213, 213, 218, 218, 223, 223, 229, 229, 229, 234, 234, 239, 239, 245, 245, 250, 250, 255, 255, 0, 0, 0, 0, 76, 97, 118, 99, 53, 55, 46, 49, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 36, 3, 235, 0, 0, 0, 0, 0, 0, 20, 28, 91, 29, 42, 92, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 56, 196, 0, 18, 8, 114, 128, 13, 70, 16, 0, 10, 72, 247, 119, 119, 224, 128, 12, 47, 98, 61, 147, 38, 16, 67, 45, 61, 131, 16, 22, 22, 4, 6, 131, 224, 129, 119, 130, 16, 65, 192, 249, 240, 124, 249, 64, 192, 144, 48, 176, 125, 64, 251, 240, 112, 225, 122, 131, 253, 16, 252, 230, 176, 126, 126, 81, 192, 133, 103, 203, 135, 232, 134, 63, 255, 175, 168, 48, 80, 49, 47, 15, 170, 99, 93, 48, 151, 137, 23, 40, 65, 216, 99, 3, 40, 89, 68, 241, 58, 101, 157, 33, 160, 100, 11, 255, 243, 56, 196, 22, 26, 137, 178, 204, 1, 143, 120, 0, 137, 206, 166, 66, 9, 202, 42, 196, 201, 21, 133, 99, 91, 157, 223, 43, 145, 47, 114, 214, 219, 72, 26, 212, 60, 37, 87, 79, 157, 193, 143, 15, 27, 243, 196, 188, 219, 166, 177, 157, 193, 167, 255, 255, 138, 199, 135, 104, 148, 174, 55, 111, 237, 255, 255, 250, 223, 56, 214, 175, 184, 251, 131, 88, 178, 105, 150, 171, 56, 100, 136, 13, 195, 33, 214, 175, 253, 42, 67, 64, 136, 127, 255, 244, 85, 110, 186, 40, 2, 181, 104, 120, 112, 161, 17, 255, 243, 56, 196, 10, 22, 241, 162, 152, 31, 218, 104, 0, 41, 200, 44, 180, 128, 175, 201, 82, 95, 99, 22, 216, 51, 139, 106, 165, 65, 121, 142, 19, 253, 56, 13, 34, 28, 118, 5, 146, 45, 102, 247, 233, 139, 165, 178, 232, 158, 133, 248, 249, 136, 117, 63, 147, 6, 8, 217, 100, 138, 245, 18, 202, 162, 106, 134, 140, 201, 109, 93, 36, 187, 168, 200, 199, 91, 105, 85, 255, 253, 107, 73, 37, 152, 151, 78, 138, 12, 78, 71, 255, 199, 45, 1, 164, 145, 255, 142, 2, 71, 136, 134, 145, 205, 10, 88, 255, 243, 56, 196, 13, 23, 193, 34, 152, 92, 14, 86, 26, 70, 179, 115, 108, 165, 167, 39, 182, 79, 44, 4, 192, 60, 229, 60, 124, 81, 56, 206, 23, 80, 46, 19, 254, 20, 30, 242, 65, 12, 204, 18, 106, 242, 81, 119, 16, 49, 158, 222, 255, 39, 16, 54, 250, 212, 33, 186, 126, 248, 167, 195, 117, 130, 139, 169, 9, 17, 41, 128, 41, 34, 236, 230, 53, 73, 238, 213, 237, 103, 162, 219, 34, 139, 208, 150, 55, 189, 44, 177, 209, 168, 143, 4, 59, 183, 255, 91, 71, 126, 144, 168, 209, 111, 72, 162, 255, 243, 56, 196, 13, 23, 201, 162, 144, 126, 211, 202, 204, 3, 23, 133, 155, 68, 228, 96, 218, 161, 216, 97, 232, 200, 36, 24, 244, 25, 235, 107, 21, 40, 185, 28, 56, 98, 196, 157, 20, 225, 187, 34, 173, 6, 135, 181, 127, 111, 255, 195, 41, 241, 235, 122, 148, 2, 151, 182, 141, 217, 157, 21, 210, 86, 122, 191, 78, 231, 233, 233, 196, 202, 164, 82, 185, 205, 170, 90, 209, 241, 150, 183, 177, 181, 35, 150, 177, 241, 100, 150, 246, 186, 228, 170, 208, 210, 237, 219, 127, 246, 184, 111, 52, 7, 163, 132, 255, 243, 56, 196, 12, 23, 217, 118, 193, 190, 126, 26, 226, 212, 10, 42, 97, 248, 61, 68, 213, 169, 34, 20, 231, 142, 48, 122, 57, 123, 12, 137, 181, 200, 78, 222, 231, 97, 173, 206, 151, 163, 189, 36, 38, 142, 185, 116, 31, 19, 165, 212, 128, 241, 191, 125, 31, 232, 22, 212, 206, 147, 89, 76, 204, 142, 215, 76, 237, 167, 4, 145, 44, 12, 226, 109, 10, 176, 218, 185, 155, 232, 20, 200, 177, 148, 102, 80, 149, 206, 221, 251, 190, 146, 98, 242, 245, 129, 39, 45, 183, 91, 104, 31, 250, 69, 231, 146, 255, 243, 56, 196, 11, 22, 112, 218, 177, 30, 195, 26, 202, 174, 4, 168, 91, 147, 23, 199, 10, 183, 240, 205, 84, 103, 245, 81, 45, 167, 40, 228, 22, 53, 191, 7, 42, 242, 166, 63, 23, 162, 175, 202, 230, 84, 200, 37, 204, 171, 95, 144, 252, 115, 49, 109, 55, 36, 85, 33, 48, 11, 214, 208, 198, 246, 94, 133, 50, 221, 212, 33, 54, 187, 101, 233, 24, 88, 98, 147, 38, 44, 27, 177, 130, 242, 105, 21, 42, 148, 188, 93, 40, 184, 220, 178, 38, 1, 144, 137, 96, 76, 72, 31, 1, 89, 19, 209, 255, 243, 56, 196, 16, 20, 217, 34, 156, 126, 14, 26, 26, 224, 133, 42, 82, 186, 222, 182, 228, 168, 207, 47, 52, 182, 214, 122, 171, 35, 141, 247, 99, 83, 220, 170, 111, 47, 62, 86, 205, 58, 11, 5, 212, 175, 46, 127, 253, 185, 168, 242, 136, 161, 47, 19, 6, 132, 15, 44, 160, 197, 174, 56, 154, 108, 75, 162, 131, 23, 2, 88, 101, 127, 217, 254, 59, 171, 37, 185, 106, 45, 201, 36, 182, 70, 6, 68, 162, 43, 54, 91, 129, 138, 237, 0, 80, 12, 40, 137, 214, 114, 91, 14, 119, 54, 182, 102, 255, 243, 56, 196, 27, 21, 0, 222, 160, 126, 14, 22, 26, 114, 174, 154, 36, 203, 214, 64, 62, 35, 61, 196, 245, 144, 162, 7, 110, 72, 191, 64, 13, 187, 223, 239, 202, 239, 121, 81, 250, 155, 248, 168, 101, 33, 70, 180, 217, 193, 206, 183, 112, 81, 73, 200, 88, 197, 43, 69, 39, 139, 229, 208, 153, 59, 255, 219, 161, 139, 10, 31, 110, 73, 26, 3, 189, 176, 58, 17, 71, 18, 29, 136, 215, 35, 69, 186, 71, 137, 48, 1, 9, 182, 64, 59, 66, 188, 114, 148, 117, 186, 65, 128, 157, 64, 170, 109, 255, 243, 56, 196, 38, 21, 17, 38, 148, 254, 203, 212, 106, 134, 53, 85, 102, 114, 102, 107, 129, 99, 255, 31, 127, 158, 223, 201, 172, 123, 210, 225, 144, 90, 105, 143, 44, 100, 185, 210, 57, 227, 227, 133, 133, 82, 228, 19, 23, 9, 17, 89, 223, 23, 253, 40, 156, 255, 250, 106, 68, 7, 37, 187, 109, 255, 219, 1, 111, 87, 171, 43, 70, 126, 209, 225, 58, 227, 98, 26, 37, 190, 37, 82, 172, 183, 165, 80, 181, 58, 160, 2, 2, 39, 199, 79, 195, 136, 54, 90, 65, 235, 74, 214, 192, 30, 119, 236, 255, 243, 56, 196, 48, 21, 48, 218, 198, 94, 194, 78, 202, 45, 244, 240, 81, 74, 12, 108, 106, 3, 37, 226, 105, 171, 100, 99, 64, 10, 101, 155, 189, 187, 84, 170, 174, 69, 69, 44, 60, 116, 202, 56, 152, 93, 10, 137, 18, 102, 5, 35, 109, 187, 109, 104, 13, 142, 102, 117, 25, 202, 215, 63, 82, 178, 165, 84, 213, 180, 242, 5, 195, 19, 68, 163, 170, 34, 227, 87, 122, 31, 72, 5, 154, 144, 50, 211, 228, 34, 220, 230, 54, 37, 28, 146, 148, 156, 14, 31, 95, 25, 79, 58, 196, 208, 178, 169, 255, 243, 56, 196, 58, 21, 8, 218, 141, 30, 211, 206, 136, 187, 153, 95, 53, 32, 241, 186, 220, 123, 124, 224, 228, 53, 213, 110, 217, 182, 241, 78, 166, 82, 231, 174, 153, 166, 10, 213, 64, 102, 229, 182, 237, 173, 16, 82, 243, 22, 198, 173, 58, 217, 32, 222, 124, 236, 183, 114, 130, 229, 178, 51, 23, 212, 119, 166, 157, 100, 237, 74, 211, 136, 113, 203, 7, 183, 132, 210, 202, 199, 178, 212, 47, 210, 137, 226, 198, 136, 188, 212, 70, 60, 136, 2, 26, 105, 226, 196, 202, 53, 20, 67, 199, 78, 210, 90, 255, 243, 56, 196, 68, 20, 248, 218, 177, 190, 195, 212, 138, 106, 235, 149, 79, 172, 32, 116, 236, 107, 5, 111, 177, 139, 255, 255, 218, 0, 52, 83, 146, 75, 99, 108, 75, 42, 102, 74, 146, 134, 209, 108, 114, 36, 83, 143, 203, 73, 94, 168, 117, 181, 49, 89, 246, 54, 157, 178, 43, 208, 128, 218, 1, 188, 131, 179, 4, 21, 155, 121, 128, 48, 250, 158, 138, 128, 119, 239, 169, 181, 247, 249, 245, 235, 207, 66, 19, 91, 171, 81, 152, 247, 61, 43, 18, 202, 8, 32, 175, 115, 189, 204, 255, 183, 234, 247, 255, 243, 56, 196, 79, 20, 201, 214, 157, 190, 193, 196, 206, 219, 147, 78, 229, 85, 96, 139, 42, 186, 237, 191, 218, 208, 18, 214, 89, 166, 183, 205, 208, 121, 203, 147, 52, 25, 234, 197, 56, 186, 52, 234, 197, 128, 50, 175, 19, 62, 14, 6, 110, 22, 171, 0, 121, 198, 184, 245, 174, 55, 237, 216, 84, 238, 184, 170, 213, 178, 230, 106, 81, 57, 9, 224, 208, 96, 180, 187, 66, 144, 169, 97, 159, 123, 79, 117, 144, 38, 46, 230, 13, 240, 4, 237, 106, 246, 161, 181, 105, 210, 2, 219, 110, 198, 128, 249, 255, 243, 56, 196, 90, 20, 248, 222, 190, 94, 51, 206, 22, 185, 73, 44, 8, 113, 202, 246, 163, 2, 19, 20, 111, 33, 221, 255, 4, 24, 143, 29, 206, 87, 91, 83, 157, 201, 14, 145, 169, 254, 108, 127, 108, 107, 61, 47, 151, 0, 89, 43, 121, 64, 13, 83, 102, 14, 235, 147, 232, 87, 218, 135, 104, 157, 32, 27, 149, 173, 8, 67, 221, 120, 38, 194, 202, 115, 174, 122, 175, 242, 47, 22, 167, 107, 216, 173, 127, 25, 117, 0, 1, 17, 178, 91, 190, 214, 65, 150, 234, 149, 104, 187, 47, 37, 161, 71, 255, 243, 56, 196, 101, 20, 232, 218, 120, 94, 218, 74, 196, 131, 86, 154, 44, 14, 166, 5, 6, 175, 87, 96, 106, 178, 222, 147, 217, 188, 147, 232, 90, 81, 156, 0, 230, 186, 233, 37, 253, 193, 235, 242, 105, 74, 7, 250, 232, 224, 200, 157, 61, 61, 204, 87, 222, 254, 158, 141, 113, 53, 90, 220, 107, 81, 5, 75, 160, 14, 177, 12, 8, 244, 13, 52, 85, 12, 48, 241, 232, 24, 130, 187, 90, 215, 140, 10, 34, 147, 45, 166, 100, 163, 75, 188, 233, 194, 137, 210, 66, 147, 146, 116, 147, 245, 34, 35, 255, 243, 56, 196, 112, 25, 249, 146, 134, 94, 211, 10, 200, 150, 35, 199, 236, 21, 165, 14, 88, 3, 152, 154, 74, 177, 10, 37, 9, 106, 150, 132, 144, 118, 126, 170, 33, 170, 24, 84, 8, 129, 101, 64, 171, 226, 100, 120, 31, 179, 245, 17, 30, 166, 119, 32, 254, 185, 165, 209, 181, 185, 120, 194, 28, 129, 160, 121, 45, 69, 168, 60, 161, 46, 163, 101, 35, 220, 180, 61, 82, 169, 22, 115, 28, 246, 162, 187, 28, 161, 169, 66, 179, 86, 206, 180, 186, 216, 56, 47, 115, 213, 2, 54, 228, 187, 248, 183, 255, 243, 56, 196, 103, 24, 57, 34, 112, 92, 222, 14, 104, 5, 80, 140, 115, 26, 214, 249, 190, 194, 191, 139, 225, 24, 100, 195, 46, 1, 1, 121, 71, 42, 15, 89, 16, 86, 253, 245, 195, 38, 121, 40, 114, 172, 103, 57, 172, 0, 85, 150, 244, 3, 255, 23, 243, 89, 77, 175, 84, 175, 125, 107, 92, 230, 122, 62, 250, 185, 20, 183, 81, 97, 160, 72, 72, 14, 188, 38, 173, 108, 109, 238, 29, 60, 228, 75, 161, 85, 152, 21, 0, 188, 245, 247, 161, 69, 2, 42, 44, 218, 33, 146, 47, 90, 0, 42, 255, 243, 56, 196, 101, 24, 169, 174, 120, 124, 211, 196, 112, 244, 150, 111, 253, 144, 118, 229, 114, 11, 71, 199, 166, 154, 21, 184, 106, 8, 2, 92, 50, 17, 49, 153, 249, 108, 54, 245, 56, 94, 131, 77, 147, 190, 45, 62, 12, 40, 158, 42, 70, 248, 170, 210, 213, 9, 203, 216, 23, 219, 255, 97, 183, 219, 94, 77, 91, 68, 161, 172, 126, 11, 87, 89, 149, 166, 82, 51, 43, 171, 54, 174, 106, 71, 177, 38, 147, 48, 171, 208, 130, 111, 52, 62, 180, 167, 211, 90, 234, 181, 197, 42, 2, 22, 165, 145, 255, 243, 56, 196, 97, 23, 18, 18, 137, 190, 203, 196, 140, 239, 244, 144, 119, 59, 99, 17, 145, 222, 252, 96, 35, 88, 141, 4, 116, 126, 145, 92, 173, 14, 241, 84, 45, 119, 36, 116, 123, 232, 172, 184, 51, 244, 3, 179, 233, 77, 184, 13, 29, 111, 32, 126, 158, 95, 191, 127, 235, 78, 116, 251, 213, 219, 35, 106, 149, 59, 79, 123, 49, 211, 137, 4, 9, 30, 109, 116, 160, 131, 188, 109, 168, 191, 120, 213, 242, 76, 220, 137, 59, 88, 69, 170, 23, 5, 216, 227, 187, 237, 28, 25, 85, 190, 48, 57, 255, 243, 56, 196, 99, 22, 1, 202, 133, 190, 202, 68, 196, 79, 82, 30, 52, 242, 149, 25, 230, 136, 75, 34, 55, 190, 198, 161, 29, 210, 31, 72, 36, 214, 36, 2, 253, 135, 223, 245, 108, 205, 79, 184, 78, 189, 205, 242, 122, 89, 120, 243, 86, 32, 112, 245, 156, 50, 73, 163, 218, 244, 72, 90, 231, 164, 98, 158, 137, 33, 57, 183, 56, 152, 9, 21, 117, 227, 207, 56, 81, 84, 110, 244, 116, 168, 213, 0, 169, 52, 182, 221, 182, 214, 193, 216, 35, 188, 40, 193, 150, 57, 196, 165, 30, 78, 24, 196, 255, 243, 56, 196, 106, 21, 41, 38, 133, 30, 202, 68, 196, 212, 247, 213, 87, 100, 68, 108, 208, 80, 27, 64, 48, 149, 132, 251, 27, 178, 86, 106, 243, 60, 182, 94, 7, 96, 163, 213, 0, 146, 107, 108, 142, 94, 148, 184, 243, 86, 181, 20, 146, 107, 78, 159, 88, 226, 146, 68, 143, 140, 117, 250, 19, 184, 162, 244, 238, 132, 152, 231, 220, 226, 2, 149, 170, 0, 8, 228, 146, 91, 126, 214, 49, 218, 152, 14, 12, 87, 140, 162, 185, 12, 100, 72, 174, 29, 4, 37, 15, 112, 111, 4, 41, 227, 136, 32, 255, 243, 56, 196, 116, 21, 8, 218, 182, 94, 110, 14, 78, 227, 100, 139, 165, 50, 11, 118, 2, 109, 157, 153, 43, 91, 224, 187, 237, 23, 217, 122, 232, 115, 111, 214, 229, 68, 247, 138, 214, 164, 173, 208, 188, 109, 41, 177, 238, 124, 131, 210, 117, 142, 78, 98, 180, 6, 17, 125, 87, 125, 67, 54, 34, 154, 0, 72, 228, 146, 75, 109, 178, 64, 6, 241, 4, 7, 148, 217, 7, 172, 89, 133, 224, 63, 2, 125, 212, 112, 180, 163, 241, 161, 130, 99, 106, 6, 199, 213, 10, 235, 82, 154, 149, 27, 173, 182, 255, 243, 56, 196, 126, 20, 224, 222, 138, 94, 203, 196, 80, 192, 25, 90, 73, 28, 156, 123, 195, 200, 204, 164, 98, 168, 66, 108, 117, 231, 212, 134, 184, 240, 218, 138, 37, 13, 26, 121, 137, 215, 158, 222, 149, 37, 246, 95, 187, 81, 253, 5, 77, 213, 0, 25, 53, 154, 203, 191, 218, 64, 253, 69, 231, 136, 34, 34, 187, 233, 201, 25, 91, 241, 250, 36, 148, 119, 44, 245, 205, 81, 156, 46, 37, 163, 6, 151, 248, 106, 163, 185, 158, 135, 220, 4, 179, 154, 244, 25, 86, 221, 247, 243, 204, 159, 125, 84, 255, 243, 56, 196, 137, 20, 136, 146, 166, 94, 19, 212, 22, 49, 145, 100, 60, 68, 146, 6, 239, 36, 46, 174, 159, 173, 228, 148, 47, 48, 52, 55, 170, 208, 57, 196, 255, 204, 89, 242, 42, 0, 122, 101, 114, 255, 245, 140, 40, 2, 28, 131, 97, 231, 173, 95, 28, 60, 153, 56, 253, 18, 83, 42, 207, 210, 90, 60, 220, 168, 147, 209, 136, 62, 195, 168, 18, 212, 183, 135, 196, 11, 219, 192, 218, 38, 110, 133, 148, 194, 144, 249, 198, 184, 115, 70, 176, 187, 218, 229, 12, 121, 194, 198, 207, 206, 50, 125, 255, 243, 56, 196, 149, 20, 88, 182, 142, 94, 203, 10, 192, 105, 75, 115, 142, 77, 55, 81, 88, 46, 221, 13, 143, 174, 7, 239, 88, 170, 133, 170, 3, 57, 100, 146, 237, 173, 144, 119, 116, 197, 73, 9, 53, 73, 125, 61, 74, 23, 38, 252, 58, 35, 20, 15, 13, 208, 18, 8, 69, 234, 171, 64, 173, 64, 208, 67, 56, 157, 146, 81, 44, 74, 200, 201, 216, 165, 24, 220, 253, 234, 169, 200, 181, 207, 85, 51, 253, 234, 34, 77, 132, 160, 170, 218, 151, 120, 199, 165, 75, 125, 41, 138, 149, 23, 67, 42, 255, 243, 56, 196, 162, 21, 80, 146, 137, 190, 54, 74, 20, 31, 181, 8, 66, 182, 54, 184, 173, 135, 205, 85, 242, 215, 32, 64, 222, 224, 21, 120, 11, 136, 184, 34, 0, 193, 129, 171, 164, 223, 131, 84, 12, 161, 70, 213, 67, 184, 84, 110, 8, 131, 176, 187, 202, 73, 151, 52, 1, 119, 57, 44, 3, 45, 123, 103, 166, 93, 85, 61, 139, 166, 244, 61, 110, 95, 76, 248, 71, 10, 145, 65, 59, 83, 30, 178, 232, 67, 73, 71, 171, 224, 51, 195, 194, 203, 254, 165, 171, 77, 233, 128, 194, 192, 55, 170, 255, 243, 56, 196, 171, 21, 136, 182, 133, 190, 211, 212, 104, 0, 37, 35, 177, 73, 182, 213, 177, 150, 165, 132, 49, 6, 136, 75, 238, 16, 56, 138, 207, 140, 54, 66, 81, 232, 229, 130, 47, 172, 221, 96, 116, 19, 227, 84, 191, 131, 11, 153, 69, 241, 152, 141, 70, 203, 96, 13, 116, 244, 173, 2, 89, 182, 182, 48, 160, 240, 197, 151, 52, 0, 4, 30, 98, 39, 128, 6, 168, 210, 197, 131, 197, 236, 113, 192, 105, 164, 200, 67, 44, 164, 112, 20, 159, 215, 166, 166, 111, 169, 149, 50, 223, 40, 70, 171, 255, 243, 56, 196, 179, 20, 200, 146, 104, 52, 219, 202, 136, 200, 2, 187, 66, 97, 137, 116, 236, 16, 60, 4, 37, 64, 44, 28, 131, 100, 77, 185, 162, 3, 202, 253, 128, 160, 254, 182, 168, 119, 178, 117, 76, 33, 205, 146, 26, 6, 77, 179, 145, 237, 150, 145, 110, 57, 15, 74, 83, 60, 225, 101, 34, 35, 75, 3, 130, 130, 97, 195, 150, 3, 107, 30, 247, 41, 75, 17, 226, 39, 229, 144, 34, 22, 115, 46, 93, 14, 108, 115, 72, 64, 99, 204, 20, 97, 42, 111, 189, 32, 73, 100, 181, 219, 191, 246, 255, 243, 56, 196, 190, 22, 88, 146, 134, 94, 214, 22, 44, 65, 157, 46, 67, 177, 19, 129, 99, 2, 170, 19, 10, 2, 188, 130, 178, 209, 136, 36, 162, 183, 116, 51, 162, 186, 176, 53, 2, 109, 115, 21, 226, 225, 65, 232, 179, 129, 180, 72, 181, 180, 41, 40, 237, 81, 177, 73, 74, 88, 213, 14, 124, 81, 33, 240, 141, 195, 147, 24, 146, 204, 22, 24, 165, 247, 218, 45, 31, 45, 177, 122, 30, 158, 88, 109, 22, 57, 234, 0, 39, 173, 240, 34, 62, 23, 2, 88, 131, 214, 31, 119, 32, 70, 160, 28, 255, 243, 56, 196, 195, 23, 48, 146, 100, 52, 222, 22, 72, 104, 202, 27, 97, 64, 232, 166, 52, 10, 80, 148, 86, 48, 156, 89, 221, 27, 29, 38, 55, 226, 123, 241, 14, 49, 143, 8, 202, 238, 222, 175, 177, 199, 220, 245, 79, 208, 214, 161, 224, 6, 131, 196, 67, 83, 172, 62, 141, 136, 216, 209, 131, 211, 111, 170, 155, 110, 252, 147, 99, 233, 154, 74, 94, 72, 117, 8, 106, 128, 40, 224, 170, 96, 41, 128, 253, 162, 162, 156, 10, 236, 27, 194, 170, 53, 226, 75, 132, 152, 171, 1, 37, 36, 91, 25, 255, 243, 56, 196, 197, 21, 24, 146, 138, 94, 203, 202, 76, 7, 232, 238, 137, 27, 113, 87, 236, 143, 75, 69, 138, 170, 135, 231, 35, 147, 189, 165, 200, 77, 166, 66, 214, 122, 10, 36, 60, 112, 179, 158, 180, 57, 135, 194, 143, 49, 46, 139, 29, 186, 103, 157, 123, 214, 21, 117, 235, 139, 18, 91, 215, 77, 131, 133, 149, 0, 120, 227, 114, 93, 172, 136, 90, 237, 18, 183, 147, 137, 158, 176, 225, 19, 20, 82, 66, 4, 48, 34, 47, 0, 129, 56, 95, 41, 213, 86, 163, 65, 82, 31, 106, 155, 141, 93, 255, 243, 56, 196, 207, 20, 168, 150, 105, 116, 102, 210, 16, 22, 218, 162, 154, 236, 182, 165, 202, 151, 77, 174, 113, 85, 210, 100, 72, 215, 140, 106, 205, 13, 54, 210, 237, 84, 84, 165, 34, 238, 75, 99, 235, 98, 66, 66, 119, 61, 10, 176, 38, 42, 231, 165, 149, 165, 39, 153, 186, 133, 178, 221, 138, 77, 175, 80, 43, 8, 220, 171, 160, 252, 136, 81, 23, 241, 124, 74, 4, 104, 15, 169, 126, 98, 92, 249, 91, 246, 17, 26, 167, 224, 83, 204, 19, 126, 11, 127, 164, 22, 57, 54, 78, 71, 234, 177, 255, 243, 56, 196, 219, 21, 16, 150, 100, 180, 222, 86, 44, 172, 154, 68, 157, 51, 138, 62, 169, 102, 136, 214, 193, 67, 69, 13, 8, 205, 145, 189, 148, 82, 148, 216, 162, 138, 0, 46, 149, 207, 56, 208, 25, 46, 222, 155, 198, 45, 237, 112, 177, 247, 30, 44, 2, 224, 229, 75, 156, 147, 3, 207, 19, 237, 150, 190, 66, 169, 99, 207, 138, 60, 242, 40, 25, 19, 173, 169, 33, 70, 129, 252, 170, 100, 119, 215, 19, 249, 2, 7, 185, 21, 88, 94, 149, 182, 221, 251, 153, 125, 180, 173, 127, 77, 155, 78, 255, 243, 56, 196, 229, 21, 224, 146, 129, 190, 211, 202, 76, 237, 87, 178, 93, 249, 158, 99, 144, 177, 239, 68, 114, 53, 204, 44, 224, 157, 227, 18, 170, 92, 208, 147, 222, 234, 90, 9, 147, 142, 108, 114, 79, 216, 184, 162, 66, 197, 236, 85, 193, 83, 64, 189, 83, 95, 42, 1, 132, 214, 9, 156, 129, 113, 71, 201, 87, 19, 214, 84, 65, 34, 29, 143, 66, 73, 98, 62, 157, 76, 54, 90, 46, 113, 88, 233, 174, 124, 254, 226, 217, 250, 213, 241, 156, 99, 30, 170, 237, 118, 20, 80, 227, 67, 175, 100, 255, 243, 56, 196, 236, 22, 56, 146, 100, 50, 222, 76, 48, 115, 135, 21, 80, 56, 132, 54, 36, 2, 15, 73, 249, 226, 97, 247, 60, 9, 177, 138, 104, 209, 197, 146, 44, 202, 170, 81, 72, 12, 229, 162, 204, 182, 151, 153, 58, 117, 140, 156, 20, 147, 5, 79, 145, 26, 164, 2, 0, 202, 185, 89, 98, 24, 57, 155, 128, 171, 154, 86, 88, 39, 203, 111, 191, 35, 1, 81, 43, 17, 185, 39, 63, 201, 83, 14, 120, 68, 123, 136, 5, 232, 52, 152, 149, 202, 181, 76, 153, 202, 88, 197, 78, 186, 164, 177, 255, 243, 56, 196, 242, 23, 169, 218, 92, 18, 219, 202, 136, 135, 130, 206, 26, 173, 140, 185, 196, 148, 166, 17, 60, 125, 195, 133, 84, 164, 23, 97, 226, 174, 42, 165, 210, 58, 112, 80, 185, 65, 103, 37, 21, 33, 202, 46, 42, 147, 168, 98, 208, 46, 101, 128, 53, 0, 32, 143, 228, 102, 98, 57, 232, 65, 213, 174, 65, 99, 132, 241, 224, 252, 77, 197, 87, 170, 199, 69, 52, 94, 63, 186, 1, 36, 55, 83, 49, 118, 162, 171, 242, 215, 239, 87, 86, 181, 30, 182, 96, 94, 155, 16, 218, 22, 149, 165, 255, 243, 56, 196, 242, 24, 0, 150, 100, 52, 222, 18, 72, 150, 190, 53, 89, 226, 4, 158, 56, 17, 88, 34, 227, 108, 159, 80, 208, 41, 4, 177, 173, 85, 129, 84, 28, 123, 109, 83, 30, 10, 150, 245, 32, 154, 22, 76, 92, 228, 192, 17, 106, 90, 57, 116, 21, 189, 89, 201, 45, 160, 32, 251, 23, 163, 16, 67, 30, 182, 194, 95, 144, 98, 100, 74, 157, 169, 11, 133, 225, 147, 48, 145, 227, 24, 25, 112, 134, 65, 37, 210, 98, 91, 127, 55, 153, 233, 236, 254, 58, 215, 247, 46, 11, 249, 120, 159, 255, 243, 56, 196, 241, 23, 48, 146, 96, 20, 227, 202, 104, 19, 199, 250, 220, 242, 6, 219, 131, 253, 228, 183, 14, 246, 255, 255, 223, 139, 189, 20, 54, 195, 118, 231, 154, 165, 184, 247, 209, 117, 65, 117, 99, 112, 228, 63, 23, 145, 193, 70, 228, 41, 239, 158, 2, 96, 110, 168, 24, 43, 148, 195, 82, 146, 132, 28, 9, 50, 8, 8, 137, 24, 152, 204, 28, 74, 64, 92, 86, 102, 164, 114, 239, 211, 50, 189, 123, 192, 217, 139, 82, 80, 36, 145, 185, 78, 74, 83, 206, 169, 127, 187, 73, 96, 121, 2, 255, 243, 56, 196, 243, 23, 104, 154, 92, 50, 199, 22, 12, 34, 38, 85, 141, 200, 145, 114, 129, 149, 184, 217, 82, 36, 66, 38, 16, 92, 2, 101, 84, 64, 27, 86, 40, 28, 48, 229, 189, 119, 30, 0, 220, 139, 5, 196, 65, 81, 8, 178, 2, 181, 90, 203, 229, 11, 204, 117, 29, 5, 54, 139, 90, 151, 197, 200, 12, 67, 50, 150, 42, 96, 18, 131, 187, 22, 127, 33, 233, 61, 171, 177, 120, 79, 57, 77, 204, 42, 2, 206, 228, 214, 226, 92, 175, 222, 173, 179, 125, 196, 187, 151, 217, 223, 103, 112, 255, 243, 56, 196, 244, 24, 48, 130, 88, 8, 230, 138, 49, 237, 255, 216, 87, 185, 143, 223, 219, 102, 245, 71, 122, 248, 219, 205, 179, 4, 187, 183, 91, 119, 165, 220, 233, 157, 146, 12, 217, 113, 130, 100, 228, 11, 206, 193, 120, 48, 76, 220, 125, 217, 61, 174, 145, 108, 201, 21, 0, 2, 0, 36, 171, 102, 245, 68, 136, 167, 44, 242, 103, 3, 71, 22, 118, 96, 9, 6, 70, 76, 89, 115, 7, 10, 52, 146, 241, 96, 192, 192, 212, 226, 38, 13, 142, 151, 164, 88, 12, 53, 105, 195, 33, 73, 20, 141, 255, 243, 56, 196, 242, 23, 24, 118, 88, 18, 199, 12, 20, 128, 240, 11, 128, 23, 1, 177, 38, 83, 37, 150, 80, 56, 90, 18, 153, 7, 54, 32, 228, 81, 70, 206, 199, 210, 94, 69, 200, 153, 4, 34, 134, 148, 80, 169, 122, 150, 182, 55, 117, 38, 102, 110, 125, 55, 187, 35, 101, 46, 169, 113, 4, 19, 78, 157, 53, 86, 200, 165, 69, 105, 221, 153, 73, 38, 154, 8, 50, 122, 105, 186, 180, 147, 90, 40, 45, 39, 73, 189, 42, 157, 105, 186, 8, 106, 65, 52, 223, 117, 162, 116, 217, 52, 86, 141, 255, 243, 56, 196, 244, 25, 16, 154, 72, 1, 92, 48, 1, 208, 117, 173, 90, 221, 118, 90, 151, 79, 164, 133, 52, 253, 204, 15, 3, 231, 127, 208, 207, 244, 170, 2, 36, 12, 159, 57, 56, 34, 32, 193, 195, 115, 24, 0, 127, 204, 110, 100, 49, 32, 72, 193, 226, 196, 182, 255, 50, 193, 140, 193, 96, 115, 1, 128, 25, 223, 248, 0, 212, 1, 108, 49, 137, 241, 12, 42, 60, 82, 4, 136, 21, 160, 175, 89, 34, 56, 76, 124, 130, 28, 194, 56, 228, 28, 164, 170, 6, 44, 101, 242, 112, 212, 94, 52, 255, 243, 56, 196, 238, 41, 11, 34, 64, 19, 155, 136, 0, 30, 37, 58, 139, 202, 50, 127, 199, 137, 124, 205, 105, 146, 196, 244, 157, 29, 31, 244, 202, 7, 208, 53, 56, 100, 113, 36, 89, 108, 173, 95, 249, 64, 190, 120, 190, 99, 47, 38, 195, 220, 152, 83, 73, 37, 58, 61, 75, 53, 71, 255, 199, 162, 199, 226, 121, 112, 213, 212, 98, 146, 36, 226, 88, 154, 147, 25, 41, 42, 191, 255, 255, 204, 9, 127, 250, 234, 76, 65, 77, 69, 51, 46, 49, 48, 48, 170, 170, 170, 170, 170, 170, 170, 170, 170, 255, 243, 56, 196, 168, 37, 83, 46, 64, 163, 156, 104, 0, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 255, 243, 56, 196, 113, 0, 0, 3, 72, 1, 192, 0, 0, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170]}
|
{"fname": 16401, "labels": "Electric_guitar,Guitar,Plucked_string_instrument,Musical_instrument,Music", "mids": "/m/02sgy,/m/0342h,/m/0fx80y,/m/04szw,/m/04rlf", "mp3": [73, 68, 51, 4, 0, 0, 0, 0, 0, 35, 84, 83, 83, 69, 0, 0, 0, 15, 0, 0, 3, 76, 97, 118, 102, 53, 55, 46, 56, 51, 46, 49, 48, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 88, 192, 0, 0, 0, 0, 0, 0, 0, 0, 0, 73, 110, 102, 111, 0, 0, 0, 15, 0, 0, 0, 39, 0, 0, 17, 40, 0, 16, 16, 23, 23, 23, 29, 29, 35, 35, 35, 41, 41, 48, 48, 48, 54, 54, 60, 60, 60, 67, 67, 67, 73, 73, 79, 79, 79, 86, 86, 92, 92, 92, 98, 98, 104, 104, 104, 111, 111, 111, 117, 117, 123, 123, 123, 130, 130, 136, 136, 136, 142, 142, 148, 148, 148, 155, 155, 161, 161, 161, 167, 167, 167, 174, 174, 180, 180, 180, 186, 186, 193, 193, 193, 199, 199, 205, 205, 205, 211, 211, 211, 218, 218, 224, 224, 224, 230, 230, 237, 237, 237, 243, 243, 249, 249, 249, 255, 255, 0, 0, 0, 0, 76, 97, 118, 99, 53, 55, 46, 49, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 36, 4, 81, 0, 0, 0, 0, 0, 0, 17, 40, 21, 132, 108, 235, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 56, 196, 0, 16, 72, 186, 172, 15, 73, 24, 0, 18, 74, 143, 8, 101, 163, 70, 218, 128, 152, 109, 186, 64, 129, 3, 11, 138, 9, 49, 116, 115, 223, 248, 136, 155, 188, 119, 115, 209, 10, 132, 4, 22, 15, 142, 7, 222, 32, 56, 80, 226, 195, 240, 253, 156, 159, 57, 62, 92, 255, 4, 57, 119, 148, 57, 57, 255, 255, 7, 249, 67, 156, 63, 255, 16, 42, 110, 104, 144, 69, 68, 163, 128, 176, 88, 80, 40, 24, 16, 156, 112, 101, 74, 33, 37, 208, 219, 61, 28, 10, 33, 64, 131, 80, 158, 255, 243, 56, 196, 29, 27, 201, 78, 237, 191, 143, 96, 2, 178, 144, 131, 72, 21, 92, 21, 155, 103, 133, 4, 11, 46, 74, 209, 228, 194, 242, 235, 20, 220, 11, 83, 45, 212, 80, 80, 219, 98, 213, 172, 37, 118, 87, 60, 235, 39, 144, 91, 151, 74, 220, 153, 153, 153, 255, 237, 203, 253, 86, 187, 37, 91, 197, 146, 46, 146, 4, 193, 83, 193, 47, 46, 84, 184, 246, 15, 54, 210, 179, 165, 127, 176, 242, 20, 135, 63, 97, 105, 230, 127, 139, 85, 4, 33, 110, 91, 117, 160, 15, 203, 44, 136, 5, 52, 255, 243, 56, 196, 12, 22, 25, 42, 181, 159, 216, 88, 2, 255, 73, 211, 244, 42, 183, 118, 196, 169, 45, 133, 182, 214, 153, 85, 167, 109, 51, 108, 234, 84, 175, 160, 94, 125, 16, 157, 75, 65, 150, 181, 164, 146, 115, 182, 143, 35, 164, 237, 203, 91, 28, 168, 230, 183, 219, 81, 197, 66, 81, 236, 152, 113, 227, 65, 112, 145, 167, 30, 247, 109, 21, 11, 193, 40, 195, 100, 191, 70, 67, 26, 174, 41, 109, 197, 98, 170, 88, 48, 149, 182, 221, 181, 144, 119, 153, 89, 12, 58, 180, 203, 166, 208, 80, 117, 255, 243, 56, 196, 18, 24, 80, 194, 177, 190, 195, 208, 146, 91, 252, 31, 113, 181, 6, 89, 128, 95, 4, 28, 165, 183, 134, 2, 75, 220, 94, 17, 215, 108, 249, 0, 97, 197, 213, 73, 194, 187, 91, 6, 47, 155, 52, 48, 176, 176, 199, 134, 146, 196, 153, 188, 186, 138, 68, 18, 98, 174, 18, 176, 60, 88, 249, 38, 220, 8, 4, 66, 48, 145, 240, 240, 64, 54, 44, 68, 106, 136, 128, 64, 142, 95, 247, 177, 234, 254, 255, 250, 170, 33, 131, 11, 154, 237, 183, 218, 209, 253, 37, 8, 75, 157, 137, 66, 255, 243, 56, 196, 15, 24, 97, 194, 186, 94, 126, 4, 62, 45, 22, 167, 13, 212, 42, 149, 76, 153, 252, 105, 130, 34, 236, 183, 95, 112, 100, 211, 220, 228, 109, 91, 183, 107, 175, 133, 249, 238, 200, 21, 154, 69, 187, 3, 247, 51, 170, 181, 19, 159, 177, 63, 245, 122, 255, 187, 35, 47, 127, 158, 142, 140, 236, 195, 49, 176, 81, 173, 189, 248, 165, 40, 107, 205, 22, 42, 66, 193, 89, 200, 50, 29, 4, 83, 20, 187, 173, 72, 83, 9, 208, 154, 0, 32, 84, 142, 239, 180, 148, 103, 90, 42, 210, 140, 255, 243, 56, 196, 12, 24, 32, 178, 133, 190, 214, 32, 132, 245, 65, 99, 82, 104, 218, 64, 159, 217, 141, 78, 91, 18, 10, 47, 1, 216, 76, 214, 190, 205, 4, 29, 34, 29, 137, 226, 232, 17, 205, 221, 8, 97, 83, 84, 35, 240, 211, 205, 139, 205, 185, 205, 45, 179, 81, 36, 51, 161, 98, 212, 96, 67, 235, 30, 130, 182, 49, 135, 214, 180, 90, 76, 242, 114, 203, 73, 97, 34, 78, 234, 90, 120, 79, 82, 103, 8, 127, 33, 133, 8, 152, 23, 113, 42, 4, 34, 253, 185, 39, 129, 67, 134, 12, 89, 255, 243, 56, 196, 10, 20, 64, 178, 149, 156, 14, 150, 30, 100, 72, 127, 226, 8, 10, 56, 192, 225, 63, 117, 74, 3, 52, 172, 198, 6, 218, 56, 42, 23, 204, 189, 28, 23, 31, 107, 64, 10, 78, 146, 51, 241, 32, 148, 49, 164, 90, 185, 213, 216, 146, 23, 104, 161, 115, 128, 249, 101, 10, 161, 9, 58, 227, 106, 6, 19, 145, 197, 76, 75, 75, 219, 175, 239, 123, 151, 217, 60, 205, 136, 34, 3, 84, 182, 221, 174, 214, 208, 226, 186, 147, 246, 93, 168, 44, 168, 48, 107, 239, 228, 53, 139, 168, 238, 255, 243, 56, 196, 24, 20, 200, 154, 186, 94, 14, 30, 6, 29, 241, 78, 194, 62, 109, 208, 90, 153, 183, 149, 40, 85, 101, 136, 243, 140, 211, 191, 26, 87, 143, 103, 190, 147, 110, 60, 23, 9, 10, 131, 197, 169, 152, 245, 125, 136, 90, 168, 182, 231, 172, 218, 151, 174, 239, 67, 19, 165, 171, 78, 31, 245, 223, 22, 189, 78, 50, 164, 213, 4, 32, 25, 55, 39, 209, 249, 118, 140, 110, 5, 19, 123, 103, 130, 200, 56, 199, 157, 91, 82, 209, 81, 1, 216, 197, 131, 59, 46, 26, 30, 52, 42, 184, 232, 255, 243, 56, 196, 35, 21, 32, 138, 141, 156, 198, 152, 78, 167, 178, 125, 75, 86, 165, 149, 168, 99, 211, 247, 232, 74, 22, 27, 96, 101, 40, 209, 104, 13, 204, 114, 218, 46, 127, 1, 128, 135, 151, 20, 51, 139, 47, 190, 198, 77, 216, 216, 2, 25, 122, 135, 129, 145, 255, 95, 203, 166, 149, 4, 34, 168, 49, 39, 249, 35, 120, 2, 188, 53, 200, 220, 176, 187, 230, 237, 49, 171, 182, 21, 92, 76, 165, 11, 140, 57, 105, 181, 115, 124, 210, 110, 61, 148, 186, 52, 6, 199, 89, 103, 77, 127, 36, 168, 255, 243, 56, 196, 45, 20, 184, 154, 145, 156, 14, 82, 26, 255, 76, 135, 254, 229, 86, 228, 160, 218, 106, 89, 96, 177, 68, 91, 172, 116, 164, 83, 90, 212, 186, 95, 123, 149, 133, 84, 65, 143, 234, 39, 80, 61, 22, 50, 76, 163, 26, 4, 120, 14, 91, 18, 66, 93, 67, 40, 83, 19, 57, 99, 18, 65, 135, 165, 102, 4, 4, 96, 208, 146, 154, 240, 193, 99, 113, 147, 157, 56, 41, 255, 37, 17, 60, 47, 206, 50, 0, 225, 142, 82, 16, 152, 250, 248, 134, 175, 150, 28, 255, 241, 139, 237, 107, 174, 255, 243, 56, 196, 57, 21, 88, 142, 120, 254, 222, 88, 104, 211, 105, 243, 171, 139, 20, 54, 131, 175, 22, 30, 23, 41, 147, 99, 34, 156, 239, 235, 163, 50, 200, 196, 107, 181, 221, 76, 243, 21, 0, 33, 27, 8, 75, 101, 104, 80, 203, 224, 70, 70, 107, 43, 137, 43, 156, 172, 132, 102, 155, 76, 98, 174, 132, 68, 67, 200, 18, 83, 249, 173, 136, 68, 108, 233, 248, 18, 141, 116, 179, 162, 150, 44, 253, 172, 83, 80, 27, 189, 159, 254, 255, 108, 245, 233, 237, 23, 90, 229, 133, 147, 220, 186, 148, 198, 255, 243, 56, 196, 66, 21, 24, 154, 125, 190, 211, 196, 140, 194, 135, 67, 169, 36, 195, 69, 85, 121, 7, 130, 244, 126, 184, 179, 44, 126, 211, 106, 1, 129, 19, 140, 1, 109, 182, 0, 192, 25, 161, 134, 67, 207, 204, 108, 136, 134, 48, 95, 255, 136, 36, 202, 244, 139, 70, 66, 176, 140, 86, 4, 70, 119, 160, 32, 245, 179, 29, 191, 255, 215, 20, 158, 197, 39, 100, 24, 234, 84, 132, 21, 106, 14, 185, 230, 145, 13, 139, 41, 174, 133, 208, 35, 113, 242, 69, 130, 18, 109, 4, 147, 18, 188, 46, 231, 255, 243, 56, 196, 76, 20, 120, 134, 166, 94, 14, 22, 18, 36, 218, 47, 20, 123, 157, 37, 131, 11, 144, 9, 45, 178, 64, 245, 93, 206, 66, 45, 36, 176, 105, 238, 225, 120, 130, 35, 123, 234, 20, 70, 121, 62, 134, 157, 62, 102, 199, 129, 16, 250, 139, 194, 110, 39, 54, 162, 63, 251, 163, 127, 118, 154, 39, 154, 210, 166, 149, 89, 33, 86, 189, 195, 148, 47, 74, 88, 190, 35, 78, 199, 227, 85, 190, 234, 228, 30, 197, 245, 166, 234, 234, 98, 36, 137, 57, 99, 104, 39, 178, 120, 52, 225, 208, 19, 255, 243, 56, 196, 89, 19, 40, 134, 166, 94, 195, 206, 106, 8, 169, 45, 27, 56, 120, 196, 0, 33, 41, 75, 122, 118, 42, 35, 24, 30, 61, 190, 171, 17, 79, 217, 61, 203, 116, 144, 247, 167, 152, 205, 233, 236, 242, 223, 125, 223, 191, 244, 115, 107, 125, 172, 134, 75, 30, 116, 154, 88, 208, 210, 156, 148, 31, 35, 65, 118, 81, 66, 135, 205, 72, 223, 142, 21, 20, 22, 104, 85, 230, 83, 128, 42, 0, 129, 17, 144, 57, 119, 213, 177, 12, 217, 198, 26, 51, 73, 135, 137, 69, 105, 146, 80, 227, 10, 255, 243, 56, 196, 107, 21, 16, 134, 116, 222, 222, 146, 104, 129, 109, 78, 47, 49, 101, 204, 222, 243, 210, 33, 133, 216, 127, 43, 103, 1, 0, 100, 131, 59, 111, 255, 175, 111, 253, 191, 235, 219, 94, 141, 190, 187, 83, 118, 146, 220, 134, 99, 67, 165, 251, 106, 229, 94, 116, 117, 72, 146, 36, 193, 239, 141, 44, 65, 116, 247, 123, 174, 61, 98, 200, 213, 233, 46, 78, 96, 104, 17, 97, 221, 146, 250, 26, 109, 16, 57, 49, 167, 203, 0, 161, 39, 34, 226, 181, 163, 48, 193, 82, 113, 16, 82, 158, 71, 255, 243, 56, 196, 117, 21, 9, 202, 134, 94, 210, 196, 164, 217, 146, 140, 238, 79, 208, 132, 60, 176, 221, 103, 77, 157, 218, 190, 219, 191, 63, 173, 65, 43, 108, 54, 246, 184, 148, 235, 78, 10, 21, 216, 146, 15, 112, 1, 35, 10, 84, 193, 87, 57, 75, 90, 101, 148, 125, 234, 162, 208, 246, 152, 169, 114, 77, 89, 33, 117, 42, 28, 4, 207, 223, 64, 176, 100, 203, 117, 243, 29, 3, 213, 211, 182, 99, 67, 198, 237, 248, 169, 104, 29, 64, 161, 8, 120, 35, 29, 175, 37, 21, 4, 115, 166, 226, 210, 255, 243, 56, 196, 127, 22, 72, 134, 108, 60, 222, 82, 104, 224, 162, 203, 51, 47, 77, 229, 108, 250, 215, 69, 247, 170, 170, 63, 87, 56, 231, 40, 114, 26, 34, 8, 29, 48, 116, 42, 163, 18, 39, 155, 123, 220, 148, 218, 246, 190, 148, 185, 168, 143, 205, 144, 39, 99, 34, 182, 8, 100, 206, 88, 211, 101, 24, 46, 8, 85, 27, 164, 10, 119, 73, 189, 88, 231, 16, 122, 29, 70, 197, 35, 192, 33, 240, 38, 12, 21, 57, 74, 34, 20, 114, 0, 186, 150, 241, 72, 235, 19, 121, 40, 12, 11, 139, 130, 255, 243, 56, 196, 132, 23, 72, 138, 92, 8, 230, 218, 50, 77, 27, 125, 123, 254, 191, 251, 118, 95, 244, 101, 173, 149, 115, 100, 106, 9, 45, 40, 77, 143, 123, 207, 129, 158, 70, 198, 10, 9, 101, 12, 160, 249, 59, 133, 213, 180, 253, 209, 48, 141, 141, 22, 221, 85, 40, 33, 180, 144, 229, 141, 165, 146, 149, 242, 21, 222, 39, 164, 144, 0, 19, 104, 153, 17, 59, 168, 88, 115, 116, 67, 245, 33, 210, 168, 196, 211, 82, 220, 1, 64, 96, 196, 230, 54, 23, 218, 142, 111, 90, 164, 187, 158, 229, 81, 255, 243, 56, 196, 133, 22, 65, 114, 100, 20, 222, 138, 104, 109, 247, 43, 66, 24, 197, 143, 42, 131, 100, 128, 177, 64, 19, 203, 243, 145, 138, 173, 20, 153, 184, 56, 165, 76, 107, 185, 114, 44, 40, 163, 44, 183, 71, 199, 153, 85, 41, 106, 8, 39, 98, 14, 205, 244, 140, 26, 26, 236, 156, 47, 145, 58, 223, 67, 137, 156, 121, 67, 32, 237, 134, 228, 68, 122, 58, 52, 35, 148, 42, 237, 9, 65, 157, 160, 228, 115, 179, 14, 207, 95, 206, 44, 103, 182, 239, 77, 239, 105, 161, 114, 130, 168, 3, 40, 255, 243, 56, 196, 139, 20, 168, 134, 112, 92, 222, 150, 40, 128, 85, 138, 93, 26, 207, 29, 8, 68, 204, 66, 76, 48, 95, 66, 74, 52, 118, 61, 71, 19, 189, 66, 37, 144, 144, 95, 83, 170, 2, 129, 100, 148, 13, 255, 218, 192, 97, 218, 3, 48, 167, 79, 182, 112, 195, 203, 98, 15, 42, 127, 156, 143, 172, 229, 238, 36, 14, 221, 148, 82, 134, 170, 10, 22, 89, 203, 63, 243, 245, 34, 164, 52, 203, 216, 57, 106, 197, 236, 190, 101, 9, 120, 243, 131, 42, 200, 178, 215, 86, 64, 182, 199, 44, 44, 255, 243, 56, 196, 151, 21, 16, 134, 129, 190, 46, 88, 12, 180, 165, 15, 39, 218, 90, 152, 241, 70, 5, 85, 65, 22, 178, 8, 9, 161, 57, 116, 73, 11, 118, 224, 149, 14, 51, 159, 2, 13, 56, 47, 17, 8, 32, 218, 13, 237, 169, 98, 5, 179, 135, 121, 129, 91, 112, 34, 70, 77, 196, 203, 91, 231, 255, 223, 191, 233, 175, 79, 86, 74, 73, 233, 110, 89, 168, 149, 209, 200, 64, 174, 213, 186, 213, 0, 201, 12, 84, 157, 129, 11, 37, 43, 66, 197, 69, 106, 189, 47, 99, 35, 116, 122, 38, 187, 255, 243, 56, 196, 161, 19, 240, 102, 142, 94, 30, 88, 12, 201, 182, 144, 184, 201, 66, 21, 22, 161, 34, 127, 32, 180, 40, 56, 246, 161, 171, 4, 187, 124, 130, 162, 39, 162, 186, 159, 83, 179, 9, 26, 76, 184, 54, 124, 165, 84, 20, 209, 65, 120, 98, 132, 137, 218, 87, 202, 236, 185, 127, 58, 184, 222, 197, 112, 22, 146, 47, 153, 142, 184, 179, 97, 145, 103, 34, 166, 92, 42, 7, 73, 114, 179, 72, 187, 152, 194, 21, 223, 72, 170, 150, 182, 40, 225, 65, 98, 204, 9, 20, 96, 21, 12, 54, 92, 255, 243, 56, 196, 176, 21, 217, 218, 117, 158, 211, 4, 132, 14, 93, 181, 172, 90, 213, 35, 69, 42, 89, 108, 174, 149, 8, 32, 7, 143, 75, 107, 89, 130, 22, 104, 227, 97, 225, 3, 73, 75, 176, 238, 195, 209, 122, 159, 236, 244, 219, 242, 138, 237, 188, 117, 18, 36, 13, 49, 131, 135, 128, 92, 66, 120, 144, 193, 170, 91, 156, 213, 137, 142, 218, 70, 150, 139, 44, 249, 97, 225, 231, 11, 90, 64, 170, 202, 151, 30, 49, 227, 152, 97, 122, 149, 192, 127, 40, 35, 58, 3, 171, 168, 241, 64, 26, 228, 255, 243, 56, 196, 183, 21, 48, 158, 96, 18, 219, 14, 132, 242, 211, 0, 64, 154, 62, 240, 245, 201, 194, 192, 5, 78, 199, 40, 2, 73, 67, 124, 152, 207, 32, 231, 53, 202, 167, 183, 209, 250, 220, 33, 121, 57, 197, 190, 164, 206, 91, 113, 162, 133, 168, 98, 223, 88, 240, 32, 32, 227, 44, 96, 244, 73, 76, 185, 142, 30, 165, 53, 196, 73, 73, 62, 113, 49, 64, 253, 238, 94, 1, 2, 0, 235, 0, 9, 190, 218, 81, 158, 229, 111, 1, 139, 210, 176, 51, 123, 97, 194, 1, 92, 222, 88, 205, 49, 255, 243, 56, 196, 193, 21, 80, 106, 129, 190, 214, 18, 40, 255, 194, 228, 178, 119, 147, 223, 99, 63, 251, 235, 255, 178, 45, 239, 239, 34, 50, 245, 84, 83, 34, 209, 61, 31, 216, 148, 38, 146, 33, 210, 150, 105, 172, 200, 207, 46, 86, 99, 50, 171, 153, 20, 134, 161, 164, 57, 138, 98, 137, 99, 50, 221, 150, 46, 44, 176, 77, 227, 77, 4, 213, 23, 228, 7, 57, 166, 181, 113, 128, 83, 75, 197, 7, 48, 183, 208, 224, 144, 57, 175, 56, 184, 150, 162, 138, 46, 44, 37, 42, 56, 2, 70, 214, 194, 255, 243, 56, 196, 202, 20, 128, 106, 104, 52, 102, 146, 12, 131, 254, 239, 247, 215, 255, 127, 253, 53, 255, 253, 187, 235, 91, 76, 190, 208, 156, 246, 158, 238, 69, 97, 228, 192, 105, 117, 132, 39, 175, 24, 164, 53, 155, 213, 66, 4, 197, 156, 215, 61, 14, 86, 217, 33, 169, 147, 161, 112, 58, 12, 245, 26, 13, 223, 172, 108, 43, 20, 182, 76, 255, 158, 58, 61, 55, 17, 247, 67, 83, 172, 170, 60, 46, 39, 107, 16, 27, 165, 0, 125, 239, 22, 59, 145, 177, 181, 253, 191, 183, 165, 82, 116, 216, 40, 255, 243, 56, 196, 215, 21, 146, 158, 134, 94, 200, 4, 236, 240, 226, 64, 198, 65, 139, 139, 188, 123, 144, 68, 130, 218, 69, 88, 190, 135, 185, 106, 75, 16, 198, 50, 102, 193, 107, 24, 101, 238, 142, 246, 220, 181, 213, 81, 65, 231, 29, 22, 22, 23, 24, 91, 208, 98, 81, 17, 8, 5, 19, 0, 160, 99, 153, 12, 71, 130, 15, 19, 37, 82, 145, 163, 68, 29, 39, 178, 205, 98, 211, 53, 50, 177, 46, 250, 155, 53, 78, 54, 198, 214, 111, 9, 196, 162, 175, 53, 150, 189, 252, 200, 212, 239, 101, 213, 255, 243, 56, 196, 223, 20, 169, 206, 100, 20, 217, 132, 136, 208, 201, 218, 232, 79, 250, 187, 206, 166, 183, 170, 236, 178, 93, 75, 117, 133, 208, 85, 223, 162, 42, 58, 50, 209, 101, 118, 3, 89, 238, 140, 69, 115, 149, 209, 151, 85, 50, 87, 132, 32, 59, 41, 92, 192, 152, 58, 170, 70, 97, 41, 117, 87, 74, 86, 156, 169, 40, 246, 74, 45, 59, 163, 162, 39, 154, 74, 159, 79, 197, 34, 138, 11, 84, 246, 166, 4, 15, 69, 158, 35, 96, 32, 181, 160, 212, 140, 246, 150, 133, 74, 110, 95, 85, 182, 255, 243, 56, 196, 235, 19, 184, 106, 129, 190, 198, 76, 40, 214, 81, 47, 72, 163, 0, 229, 28, 53, 40, 220, 68, 184, 197, 210, 129, 103, 184, 106, 239, 38, 212, 111, 94, 48, 76, 28, 73, 225, 138, 36, 29, 29, 104, 185, 132, 181, 35, 18, 105, 97, 225, 245, 40, 233, 57, 58, 8, 26, 134, 194, 75, 152, 197, 24, 40, 77, 216, 139, 151, 176, 210, 11, 157, 218, 8, 138, 179, 50, 253, 114, 188, 163, 188, 189, 248, 94, 253, 60, 81, 23, 46, 191, 15, 127, 188, 249, 254, 119, 47, 197, 165, 116, 233, 88, 255, 243, 56, 196, 251, 27, 11, 54, 80, 0, 199, 4, 24, 100, 93, 194, 4, 72, 246, 137, 53, 123, 214, 209, 228, 203, 129, 203, 156, 92, 187, 109, 57, 96, 128, 138, 208, 231, 12, 148, 9, 61, 108, 88, 68, 105, 85, 230, 210, 28, 63, 42, 71, 179, 1, 131, 141, 49, 20, 51, 40, 49, 148, 191, 198, 11, 12, 154, 37, 98, 203, 161, 136, 75, 34, 40, 25, 225, 69, 29, 134, 42, 234, 244, 60, 10, 136, 47, 85, 238, 183, 109, 251, 105, 222, 190, 218, 191, 253, 95, 47, 116, 123, 236, 121, 133, 250, 249, 255, 243, 56, 196, 237, 22, 88, 102, 92, 18, 222, 18, 96, 34, 23, 62, 143, 10, 119, 99, 220, 189, 179, 233, 23, 183, 51, 234, 119, 44, 169, 211, 52, 153, 77, 58, 107, 191, 156, 88, 41, 44, 43, 102, 115, 106, 115, 65, 175, 73, 43, 27, 45, 169, 208, 73, 2, 38, 2, 93, 248, 1, 10, 193, 128, 7, 27, 188, 6, 172, 86, 57, 48, 112, 96, 86, 138, 25, 130, 172, 47, 177, 96, 231, 113, 154, 48, 211, 166, 84, 5, 75, 65, 170, 96, 249, 63, 93, 91, 222, 125, 93, 58, 255, 191, 125, 36, 99, 255, 243, 56, 196, 242, 21, 250, 18, 108, 220, 216, 68, 252, 162, 173, 16, 149, 41, 110, 90, 51, 33, 95, 137, 74, 178, 170, 217, 244, 74, 223, 110, 198, 247, 189, 74, 102, 145, 30, 250, 163, 189, 29, 136, 133, 27, 220, 37, 180, 69, 1, 224, 78, 58, 250, 118, 17, 229, 1, 37, 34, 43, 125, 41, 42, 125, 219, 146, 58, 152, 126, 104, 113, 106, 246, 126, 0, 194, 205, 69, 187, 146, 138, 86, 54, 236, 34, 177, 96, 232, 29, 190, 22, 170, 104, 182, 127, 41, 69, 182, 45, 250, 108, 156, 109, 49, 100, 153, 255, 243, 56, 196, 249, 25, 243, 54, 84, 8, 225, 70, 216, 146, 38, 49, 72, 42, 65, 168, 30, 184, 162, 109, 152, 20, 9, 61, 138, 50, 22, 6, 5, 144, 245, 22, 65, 0, 163, 131, 132, 86, 85, 69, 218, 227, 138, 51, 50, 85, 73, 59, 81, 19, 42, 69, 164, 6, 36, 214, 211, 133, 44, 206, 8, 76, 29, 38, 172, 12, 60, 193, 5, 78, 45, 177, 24, 223, 137, 83, 9, 38, 1, 157, 237, 12, 174, 230, 22, 254, 253, 255, 214, 142, 171, 39, 139, 62, 229, 60, 238, 179, 103, 244, 124, 187, 139, 15, 255, 243, 56, 196, 240, 24, 58, 178, 88, 16, 218, 68, 133, 89, 114, 170, 202, 231, 150, 37, 117, 163, 122, 210, 63, 78, 118, 167, 210, 248, 250, 219, 165, 249, 27, 186, 148, 58, 140, 69, 195, 165, 236, 71, 198, 47, 231, 159, 114, 35, 125, 219, 236, 31, 143, 160, 108, 149, 0, 154, 250, 66, 87, 31, 96, 41, 180, 108, 178, 64, 40, 167, 85, 230, 24, 104, 254, 212, 120, 215, 154, 114, 11, 129, 84, 120, 73, 66, 91, 117, 86, 101, 166, 65, 54, 72, 151, 48, 5, 73, 95, 158, 202, 226, 225, 161, 207, 85, 255, 243, 56, 196, 238, 22, 88, 102, 100, 212, 222, 140, 40, 90, 143, 37, 206, 25, 150, 32, 89, 53, 150, 130, 185, 213, 5, 117, 36, 175, 231, 96, 208, 81, 150, 228, 150, 230, 224, 211, 211, 128, 114, 71, 84, 101, 200, 58, 97, 72, 24, 75, 103, 234, 120, 133, 192, 213, 97, 97, 6, 133, 0, 37, 64, 180, 96, 192, 44, 58, 59, 21, 34, 92, 68, 7, 3, 74, 217, 10, 136, 166, 66, 184, 101, 214, 179, 104, 86, 180, 225, 177, 161, 179, 29, 141, 208, 211, 110, 181, 41, 179, 121, 191, 109, 106, 210, 245, 255, 243, 56, 196, 243, 24, 91, 22, 84, 20, 216, 70, 249, 47, 53, 12, 212, 51, 161, 169, 209, 255, 242, 178, 35, 251, 175, 86, 169, 81, 77, 242, 232, 165, 110, 134, 42, 25, 3, 57, 39, 255, 14, 251, 112, 239, 23, 243, 69, 235, 125, 37, 48, 202, 76, 65, 77, 69, 51, 46, 49, 48, 48, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 255, 243, 56, 196, 240, 20, 120, 102, 76, 84, 222, 76, 40, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 76, 65, 77, 69, 51, 46, 49, 48, 48, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 255, 243, 56, 196, 253, 25, 226, 162, 8, 0, 210, 68, 145, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 255, 243, 56, 196, 160, 0, 0, 3, 72, 0, 0, 0, 0, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170, 170]}
|
{"fname": 16402, "labels": "Electric_guitar,Guitar,Plucked_string_instrument,Musical_instrument,Music", "mids": "/m/02sgy,/m/0342h,/m/0fx80y,/m/04szw,/m/04rlf", "mp3": [73, 68, 51, 4, 0, 0, 0, 0, 0, 35, 84, 83, 83, 69, 0, 0, 0, 15, 0, 0, 3, 76, 97, 118, 102, 53, 55, 46, 56, 51, 46, 49, 48, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 88, 192, 0, 0, 0, 0, 0, 0, 0, 0, 0, 73, 110, 102, 111, 0, 0, 0, 15, 0, 0, 0, 42, 0, 0, 18, 108, 0, 15, 15, 21, 21, 27, 27, 27, 33, 33, 39, 39, 44, 44, 44, 50, 50, 56, 56, 56, 62, 62, 68, 68, 74, 74, 74, 80, 80, 85, 85, 91, 91, 91, 97, 97, 103, 103, 103, 109, 109, 115, 115, 121, 121, 121, 127, 127, 132, 132, 138, 138, 138, 144, 144, 150, 150, 150, 156, 156, 162, 162, 168, 168, 168, 173, 173, 179, 179, 179, 185, 185, 191, 191, 197, 197, 197, 203, 203, 209, 209, 214, 214, 214, 220, 220, 226, 226, 226, 232, 232, 238, 238, 244, 244, 244, 250, 250, 255, 255, 0, 0, 0, 0, 76, 97, 118, 99, 53, 55, 46, 49, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 36, 3, 158, 0, 0, 0, 0, 0, 0, 18, 108, 15, 74, 82, 127, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 243, 56, 196, 0, 15, 200, 6, 221, 119, 65, 24, 2, 0, 34, 179, 77, 204, 6, 15, 131, 224, 249, 64, 124, 63, 113, 241, 0, 32, 8, 28, 7, 193, 240, 125, 96, 224, 32, 99, 137, 207, 255, 19, 131, 231, 254, 31, 46, 249, 64, 64, 16, 4, 14, 122, 3, 31, 193, 192, 65, 223, 163, 255, 240, 124, 31, 7, 254, 39, 7, 193, 243, 232, 40, 8, 42, 64, 128, 2, 97, 199, 4, 1, 0, 32, 142, 57, 91, 142, 103, 72, 64, 209, 101, 6, 84, 39, 81, 155, 135, 115, 60, 157, 179, 169, 41, 89, 255, 243, 56, 196, 31, 28, 217, 242, 185, 21, 153, 160, 0, 93, 128, 212, 35, 87, 1, 164, 4, 139, 133, 151, 155, 41, 137, 209, 201, 25, 177, 236, 241, 176, 96, 209, 114, 167, 21, 209, 13, 56, 58, 72, 227, 96, 250, 164, 62, 72, 139, 29, 157, 42, 204, 152, 200, 162, 59, 72, 181, 234, 50, 127, 228, 113, 62, 100, 94, 90, 170, 127, 254, 229, 18, 242, 75, 162, 93, 255, 255, 235, 64, 197, 16, 84, 96, 43, 255, 242, 194, 89, 96, 212, 183, 255, 242, 181, 3, 212, 146, 24, 25, 107, 14, 253, 217, 107, 255, 243, 56, 196, 10, 22, 209, 62, 152, 93, 219, 104, 2, 117, 2, 2, 134, 137, 130, 132, 100, 18, 169, 117, 88, 101, 217, 144, 179, 16, 19, 82, 151, 67, 214, 177, 231, 228, 128, 87, 41, 44, 186, 98, 180, 199, 208, 79, 130, 172, 82, 89, 66, 182, 151, 13, 132, 173, 181, 231, 41, 153, 58, 210, 73, 3, 100, 89, 171, 125, 169, 31, 60, 28, 3, 12, 121, 57, 53, 68, 194, 81, 168, 147, 207, 43, 255, 203, 19, 111, 31, 89, 151, 231, 21, 100, 194, 212, 146, 237, 172, 176, 84, 214, 86, 43, 0, 182, 255, 243, 56, 196, 13, 23, 81, 222, 173, 190, 161, 135, 130, 148, 108, 146, 52, 77, 67, 14, 23, 216, 197, 72, 165, 50, 90, 34, 111, 42, 250, 204, 40, 151, 121, 175, 185, 209, 114, 116, 179, 60, 246, 104, 118, 191, 53, 187, 227, 61, 140, 109, 215, 86, 115, 30, 79, 195, 120, 49, 42, 250, 156, 81, 214, 161, 82, 18, 205, 224, 149, 160, 169, 138, 42, 22, 107, 251, 187, 41, 65, 216, 197, 53, 164, 141, 36, 224, 197, 172, 84, 2, 250, 85, 1, 91, 54, 223, 91, 5, 210, 105, 236, 52, 112, 91, 126, 109, 255, 243, 56, 196, 14, 24, 89, 142, 136, 126, 172, 198, 124, 170, 145, 225, 218, 8, 26, 4, 200, 68, 84, 141, 107, 89, 152, 106, 209, 237, 13, 52, 8, 173, 135, 171, 36, 91, 117, 230, 71, 6, 53, 180, 115, 7, 35, 168, 56, 42, 142, 70, 81, 220, 178, 42, 88, 254, 87, 242, 249, 238, 93, 19, 28, 128, 251, 68, 8, 30, 40, 229, 228, 59, 200, 173, 110, 115, 42, 232, 22, 19, 168, 230, 2, 88, 101, 161, 58, 41, 90, 192, 224, 53, 218, 81, 74, 34, 221, 187, 72, 208, 158, 206, 223, 47, 223, 202, 255, 243, 56, 196, 11, 23, 41, 178, 124, 94, 227, 68, 208, 217, 0, 32, 93, 17, 55, 151, 235, 58, 148, 212, 174, 40, 177, 230, 65, 195, 206, 141, 206, 6, 130, 151, 160, 172, 161, 173, 47, 49, 135, 57, 60, 219, 59, 187, 67, 85, 9, 204, 59, 93, 47, 91, 149, 140, 221, 160, 154, 13, 137, 45, 235, 60, 101, 165, 3, 193, 129, 189, 107, 25, 21, 156, 83, 96, 70, 169, 132, 94, 167, 31, 13, 26, 208, 112, 144, 250, 85, 90, 54, 233, 85, 0, 128, 236, 182, 109, 244, 172, 59, 241, 185, 251, 121, 239, 255, 243, 56, 196, 13, 21, 9, 186, 137, 190, 219, 68, 208, 61, 39, 121, 94, 62, 183, 189, 95, 229, 170, 52, 92, 18, 1, 169, 138, 148, 165, 97, 100, 54, 63, 115, 247, 51, 220, 245, 60, 188, 195, 39, 99, 218, 190, 205, 253, 25, 59, 99, 58, 179, 255, 106, 154, 99, 205, 210, 206, 193, 218, 149, 144, 86, 199, 41, 8, 4, 35, 131, 99, 191, 237, 119, 60, 182, 45, 181, 175, 150, 78, 229, 42, 0, 128, 227, 118, 255, 245, 180, 28, 0, 75, 50, 121, 90, 195, 112, 11, 93, 86, 236, 167, 185, 88, 51, 255, 243, 56, 196, 23, 21, 9, 142, 137, 190, 77, 68, 56, 160, 227, 204, 169, 35, 173, 197, 34, 138, 170, 190, 162, 191, 203, 23, 176, 191, 147, 118, 215, 218, 149, 65, 116, 87, 178, 62, 154, 179, 35, 170, 15, 17, 68, 115, 38, 161, 97, 171, 161, 12, 121, 236, 10, 58, 81, 181, 177, 74, 91, 237, 185, 137, 86, 151, 191, 19, 213, 168, 44, 151, 85, 0, 128, 162, 86, 109, 173, 144, 51, 6, 250, 67, 90, 188, 239, 56, 157, 227, 242, 211, 91, 116, 77, 150, 138, 66, 134, 10, 227, 103, 127, 114, 4, 125, 255, 243, 56, 196, 33, 20, 153, 70, 133, 190, 220, 68, 112, 26, 180, 255, 238, 169, 156, 65, 211, 151, 70, 79, 178, 250, 232, 44, 121, 154, 45, 83, 195, 113, 122, 85, 182, 226, 20, 231, 93, 114, 168, 155, 97, 91, 210, 208, 218, 161, 119, 197, 79, 165, 77, 197, 207, 162, 42, 64, 75, 177, 106, 6, 18, 150, 198, 128, 144, 79, 206, 231, 82, 206, 173, 142, 2, 136, 211, 50, 156, 145, 187, 151, 88, 135, 129, 124, 153, 250, 29, 202, 39, 253, 150, 159, 246, 78, 225, 254, 251, 54, 191, 99, 243, 206, 106, 214, 255, 243, 56, 196, 45, 20, 233, 130, 116, 94, 228, 68, 112, 121, 118, 117, 48, 192, 16, 132, 227, 156, 88, 113, 98, 70, 7, 69, 94, 192, 129, 114, 108, 16, 52, 44, 167, 115, 207, 58, 92, 96, 233, 47, 118, 163, 52, 44, 155, 222, 52, 221, 14, 24, 154, 151, 123, 27, 11, 167, 186, 203, 27, 91, 210, 75, 141, 201, 203, 185, 150, 251, 248, 213, 73, 213, 132, 171, 61, 126, 224, 96, 155, 93, 62, 223, 61, 125, 61, 91, 118, 254, 213, 179, 234, 206, 185, 164, 231, 63, 250, 167, 9, 225, 145, 17, 66, 117, 255, 243, 56, 196, 56, 20, 1, 218, 129, 30, 218, 134, 216, 19, 53, 27, 93, 107, 40, 130, 13, 50, 16, 120, 183, 12, 207, 85, 82, 215, 103, 208, 209, 13, 192, 19, 106, 32, 255, 139, 89, 215, 166, 159, 156, 222, 66, 32, 193, 237, 3, 13, 54, 153, 182, 249, 198, 224, 178, 130, 57, 236, 244, 213, 194, 34, 222, 250, 183, 250, 123, 47, 219, 49, 151, 253, 29, 24, 181, 194, 70, 139, 189, 78, 9, 37, 44, 58, 0, 153, 48, 100, 177, 43, 25, 94, 136, 187, 16, 192, 134, 83, 106, 69, 146, 33, 74, 108, 255, 243, 56, 196, 71, 19, 121, 58, 104, 50, 227, 206, 104, 242, 185, 135, 178, 241, 141, 222, 22, 161, 26, 136, 53, 41, 44, 211, 255, 98, 66, 21, 140, 225, 209, 53, 117, 82, 220, 187, 206, 101, 213, 176, 164, 113, 229, 117, 119, 24, 212, 219, 174, 159, 81, 196, 13, 246, 95, 122, 37, 168, 198, 188, 13, 35, 59, 8, 60, 106, 230, 172, 121, 233, 213, 169, 82, 88, 204, 152, 109, 1, 118, 157, 171, 196, 163, 206, 14, 26, 61, 11, 105, 226, 145, 53, 22, 225, 3, 71, 169, 166, 36, 50, 74, 212, 224, 65, 255, 243, 56, 196, 88, 18, 232, 126, 96, 18, 207, 68, 76, 1, 253, 140, 207, 45, 107, 213, 102, 14, 6, 33, 51, 89, 235, 235, 115, 17, 170, 204, 218, 185, 95, 159, 44, 234, 250, 220, 167, 168, 2, 139, 111, 113, 162, 241, 204, 88, 177, 240, 136, 103, 216, 215, 62, 82, 132, 33, 143, 29, 39, 177, 226, 175, 0, 133, 80, 163, 26, 13, 245, 173, 91, 92, 90, 225, 3, 104, 196, 141, 147, 138, 112, 180, 5, 9, 158, 116, 198, 255, 89, 222, 240, 231, 45, 54, 38, 63, 219, 209, 187, 130, 167, 103, 167, 79, 255, 243, 56, 196, 107, 18, 184, 118, 96, 18, 225, 154, 100, 211, 189, 124, 219, 55, 239, 169, 115, 247, 90, 221, 23, 246, 238, 190, 118, 209, 18, 71, 101, 26, 64, 238, 164, 186, 40, 242, 47, 212, 150, 90, 145, 69, 45, 12, 38, 77, 128, 18, 129, 69, 195, 142, 114, 88, 78, 170, 6, 224, 9, 27, 99, 106, 52, 178, 168, 26, 158, 140, 192, 1, 99, 219, 31, 32, 26, 144, 90, 44, 190, 9, 194, 235, 57, 126, 98, 51, 207, 232, 137, 111, 207, 255, 141, 71, 173, 98, 217, 246, 57, 247, 164, 138, 102, 205, 255, 243, 56, 196, 127, 19, 161, 218, 100, 20, 79, 4, 48, 29, 82, 134, 138, 137, 93, 120, 209, 56, 108, 161, 67, 8, 13, 130, 230, 246, 208, 184, 2, 166, 19, 165, 45, 74, 158, 170, 82, 112, 78, 74, 39, 73, 162, 21, 6, 161, 168, 140, 236, 106, 14, 121, 48, 126, 12, 183, 62, 186, 78, 85, 74, 127, 203, 75, 64, 128, 76, 254, 63, 125, 57, 78, 107, 244, 219, 117, 204, 151, 161, 187, 189, 55, 133, 158, 45, 66, 128, 118, 168, 40, 68, 105, 104, 40, 198, 86, 177, 41, 121, 39, 136, 223, 8, 62, 255, 243, 56, 196, 143, 20, 152, 242, 96, 20, 227, 4, 104, 97, 2, 235, 158, 155, 161, 32, 58, 74, 32, 78, 160, 251, 72, 30, 114, 199, 152, 96, 97, 28, 31, 246, 225, 11, 153, 151, 184, 250, 153, 48, 80, 120, 253, 138, 199, 70, 176, 66, 74, 182, 88, 17, 8, 240, 123, 184, 81, 147, 119, 193, 190, 221, 243, 125, 253, 251, 45, 127, 71, 223, 245, 165, 180, 171, 236, 238, 146, 82, 247, 241, 55, 94, 172, 183, 165, 204, 168, 167, 42, 23, 102, 102, 114, 165, 246, 123, 106, 233, 71, 44, 141, 87, 102, 144, 255, 243, 56, 196, 155, 19, 240, 122, 92, 18, 199, 12, 64, 228, 83, 59, 163, 94, 153, 170, 173, 34, 213, 135, 12, 174, 243, 142, 218, 19, 2, 79, 198, 133, 72, 253, 61, 17, 202, 134, 10, 132, 231, 45, 157, 174, 21, 44, 139, 11, 191, 69, 148, 17, 17, 194, 142, 25, 145, 69, 28, 96, 115, 43, 101, 30, 135, 213, 240, 125, 235, 69, 191, 111, 206, 240, 253, 39, 57, 195, 84, 95, 202, 89, 232, 122, 127, 243, 10, 83, 31, 42, 247, 82, 151, 47, 55, 43, 12, 188, 238, 109, 220, 208, 228, 166, 106, 114, 255, 243, 56, 196, 170, 22, 171, 58, 88, 10, 225, 132, 105, 26, 153, 21, 221, 73, 13, 217, 123, 203, 154, 49, 108, 146, 43, 135, 164, 249, 63, 60, 114, 17, 21, 6, 224, 9, 250, 120, 213, 120, 68, 103, 115, 230, 5, 28, 233, 5, 17, 208, 117, 28, 197, 133, 21, 207, 110, 229, 102, 165, 180, 125, 63, 77, 95, 244, 237, 255, 182, 250, 115, 205, 125, 87, 43, 59, 186, 203, 102, 29, 213, 98, 136, 61, 227, 133, 74, 41, 131, 88, 227, 170, 65, 180, 18, 190, 40, 43, 81, 34, 200, 63, 160, 94, 135, 92, 255, 243, 56, 196, 174, 25, 26, 254, 80, 8, 232, 134, 213, 33, 88, 236, 58, 135, 66, 42, 9, 78, 77, 81, 24, 215, 72, 155, 85, 220, 11, 254, 119, 170, 61, 196, 23, 120, 40, 228, 210, 254, 170, 59, 110, 202, 208, 206, 93, 98, 200, 100, 225, 129, 209, 229, 146, 9, 181, 136, 22, 7, 32, 121, 59, 117, 25, 96, 173, 135, 193, 246, 47, 174, 19, 172, 84, 221, 182, 177, 104, 74, 182, 170, 194, 153, 10, 8, 255, 9, 32, 120, 66, 57, 35, 71, 170, 226, 89, 195, 198, 96, 153, 200, 28, 236, 238, 129, 255, 243, 56, 196, 168, 19, 217, 206, 96, 20, 199, 10, 64, 179, 145, 229, 105, 239, 209, 71, 125, 222, 213, 56, 36, 178, 211, 241, 70, 57, 85, 172, 216, 117, 141, 34, 187, 30, 198, 154, 11, 131, 103, 212, 96, 24, 49, 95, 64, 228, 157, 107, 152, 210, 140, 23, 91, 241, 80, 76, 218, 155, 48, 68, 248, 226, 21, 27, 67, 122, 27, 52, 3, 20, 114, 227, 209, 67, 7, 131, 78, 250, 211, 152, 159, 4, 237, 45, 5, 84, 196, 244, 142, 118, 74, 173, 33, 235, 111, 205, 254, 214, 213, 150, 125, 30, 253, 83, 255, 243, 56, 196, 183, 16, 160, 82, 108, 60, 102, 196, 36, 78, 182, 102, 210, 170, 250, 42, 91, 210, 155, 43, 50, 187, 81, 15, 181, 105, 26, 189, 147, 187, 26, 136, 231, 189, 103, 119, 107, 18, 172, 91, 164, 221, 61, 136, 69, 91, 173, 199, 37, 5, 204, 160, 140, 20, 194, 50, 12, 28, 140, 170, 0, 170, 240, 65, 173, 146, 171, 254, 97, 64, 161, 227, 29, 212, 51, 212, 216, 101, 201, 206, 86, 167, 199, 226, 77, 40, 240, 184, 190, 173, 81, 23, 223, 87, 198, 247, 153, 151, 85, 218, 251, 189, 228, 177, 255, 243, 56, 196, 211, 18, 152, 86, 104, 54, 78, 196, 36, 91, 51, 51, 147, 118, 102, 123, 91, 55, 216, 136, 248, 119, 35, 109, 84, 84, 233, 203, 202, 191, 69, 222, 154, 213, 216, 217, 156, 21, 132, 68, 110, 134, 119, 243, 136, 5, 238, 70, 112, 181, 105, 10, 66, 159, 6, 143, 13, 76, 242, 82, 131, 131, 22, 9, 155, 72, 2, 161, 22, 107, 82, 250, 120, 84, 102, 181, 48, 24, 28, 252, 101, 104, 51, 90, 26, 43, 192, 19, 41, 123, 158, 212, 182, 143, 183, 122, 39, 233, 211, 86, 79, 251, 111, 251, 255, 243, 56, 196, 231, 22, 67, 46, 84, 8, 225, 132, 105, 236, 248, 118, 236, 233, 178, 174, 217, 221, 226, 127, 31, 255, 91, 181, 220, 170, 108, 52, 152, 219, 91, 255, 13, 235, 41, 224, 9, 15, 95, 94, 138, 182, 214, 102, 119, 234, 221, 126, 228, 176, 230, 234, 76, 65, 77, 69, 51, 46, 49, 48, 48, 170, 170, 170, 170, 170, 170, 13, 4, 171, 146, 218, 219, 22, 14, 185, 196, 183, 192, 129, 196, 80, 77, 151, 212, 154, 78, 245, 71, 211, 62, 190, 94, 73, 141, 253, 147, 183, 172, 250, 172, 23, 101, 235, 255, 243, 56, 196, 237, 25, 251, 42, 80, 8, 225, 70, 221, 65, 100, 147, 144, 6, 7, 11, 67, 0, 99, 44, 142, 115, 210, 173, 141, 80, 241, 173, 65, 133, 125, 1, 249, 199, 144, 83, 33, 10, 29, 19, 93, 160, 2, 148, 209, 101, 113, 56, 146, 55, 54, 85, 96, 12, 14, 124, 180, 180, 25, 159, 155, 107, 65, 132, 107, 197, 43, 119, 117, 105, 7, 186, 9, 54, 149, 119, 202, 178, 53, 45, 80, 241, 234, 206, 198, 178, 113, 57, 16, 250, 50, 152, 64, 206, 86, 157, 140, 146, 144, 131, 43, 122, 169, 167, 255, 243, 56, 196, 228, 20, 17, 206, 92, 18, 216, 196, 105, 69, 51, 142, 106, 156, 166, 97, 197, 143, 103, 32, 166, 103, 51, 187, 40, 10, 165, 37, 149, 99, 110, 74, 221, 147, 83, 180, 105, 90, 54, 198, 101, 83, 93, 253, 36, 91, 21, 74, 87, 137, 189, 50, 162, 3, 89, 90, 240, 89, 33, 161, 210, 80, 36, 36, 171, 229, 207, 45, 243, 6, 4, 60, 170, 10, 73, 84, 237, 142, 131, 4, 83, 73, 65, 125, 217, 210, 186, 78, 219, 119, 193, 94, 247, 241, 58, 178, 223, 99, 250, 230, 14, 114, 79, 181, 255, 243, 56, 196, 227, 16, 184, 42, 121, 30, 51, 52, 32, 96, 223, 11, 56, 117, 80, 156, 26, 150, 34, 36, 47, 3, 84, 65, 64, 172, 153, 255, 149, 214, 18, 63, 2, 111, 121, 31, 198, 155, 138, 73, 25, 156, 30, 146, 81, 253, 103, 218, 172, 201, 243, 171, 129, 250, 223, 32, 100, 120, 181, 8, 0, 12, 189, 11, 133, 187, 65, 13, 194, 93, 100, 195, 192, 79, 247, 77, 186, 114, 93, 202, 248, 78, 95, 67, 179, 149, 22, 227, 169, 207, 87, 27, 10, 230, 157, 82, 248, 126, 247, 241, 115, 43, 47, 175, 255, 243, 56, 196, 255, 27, 179, 18, 88, 52, 217, 138, 105, 78, 189, 190, 158, 124, 159, 151, 102, 24, 167, 229, 244, 184, 16, 200, 249, 232, 89, 67, 171, 29, 162, 145, 106, 244, 21, 52, 153, 242, 249, 152, 83, 90, 251, 110, 206, 230, 12, 243, 233, 177, 219, 216, 196, 68, 185, 178, 33, 6, 104, 130, 15, 45, 196, 12, 88, 122, 6, 160, 77, 141, 134, 23, 37, 10, 150, 118, 124, 180, 7, 25, 1, 106, 136, 35, 145, 81, 4, 107, 47, 118, 118, 162, 55, 124, 157, 242, 127, 233, 255, 244, 162, 237, 108, 221, 255, 243, 56, 196, 239, 24, 162, 46, 88, 18, 216, 134, 157, 213, 180, 155, 37, 53, 246, 57, 86, 52, 176, 36, 134, 169, 75, 46, 131, 12, 9, 185, 181, 102, 29, 153, 19, 142, 212, 73, 131, 216, 233, 102, 137, 239, 67, 218, 137, 194, 225, 138, 5, 202, 118, 106, 145, 122, 24, 93, 233, 60, 90, 143, 73, 246, 119, 107, 253, 235, 159, 206, 119, 155, 40, 187, 76, 164, 79, 44, 142, 59, 100, 250, 203, 158, 114, 135, 174, 169, 18, 53, 131, 237, 53, 80, 170, 12, 210, 171, 18, 229, 249, 210, 90, 172, 5, 214, 255, 243, 56, 196, 235, 25, 107, 50, 80, 8, 216, 134, 189, 28, 44, 159, 188, 67, 52, 220, 206, 113, 2, 19, 77, 172, 47, 243, 206, 126, 249, 83, 153, 157, 255, 153, 118, 124, 187, 157, 114, 50, 43, 249, 139, 118, 2, 94, 158, 76, 65, 77, 32, 74, 73, 201, 204, 80, 58, 18, 105, 0, 228, 238, 41, 88, 112, 34, 87, 224, 123, 148, 203, 37, 100, 46, 233, 93, 157, 224, 137, 155, 190, 93, 22, 182, 61, 53, 165, 63, 86, 223, 182, 143, 113, 25, 95, 220, 140, 170, 136, 244, 86, 35, 227, 32, 98, 187, 255, 243, 56, 196, 228, 19, 33, 202, 92, 18, 126, 202, 36, 222, 92, 40, 251, 241, 91, 176, 127, 223, 158, 152, 132, 206, 112, 214, 121, 125, 127, 254, 143, 189, 127, 169, 169, 73, 212, 80, 147, 197, 146, 20, 41, 9, 106, 153, 118, 202, 95, 183, 61, 248, 18, 23, 59, 220, 249, 69, 225, 188, 129, 18, 11, 192, 104, 138, 7, 130, 131, 200, 11, 7, 97, 43, 141, 226, 78, 103, 32, 47, 135, 163, 255, 120, 15, 255, 243, 35, 191, 167, 255, 190, 177, 73, 225, 252, 235, 150, 119, 38, 92, 129, 31, 7, 110, 115, 255, 243, 56, 196, 246, 22, 243, 26, 100, 92, 208, 70, 189, 83, 132, 176, 161, 92, 125, 8, 230, 149, 233, 177, 21, 92, 200, 177, 103, 66, 25, 142, 43, 20, 162, 207, 66, 154, 222, 194, 99, 112, 33, 96, 230, 134, 42, 132, 55, 7, 6, 101, 6, 27, 83, 96, 140, 12, 231, 68, 102, 124, 164, 32, 133, 190, 221, 34, 149, 192, 65, 7, 13, 81, 47, 162, 31, 21, 163, 80, 101, 105, 209, 228, 20, 149, 85, 113, 24, 62, 251, 62, 186, 238, 186, 143, 42, 170, 214, 139, 186, 232, 189, 182, 221, 244, 183, 116, 255, 243, 56, 196, 246, 21, 113, 202, 104, 252, 78, 132, 37, 108, 151, 77, 146, 202, 78, 100, 190, 155, 89, 16, 132, 163, 130, 228, 81, 163, 61, 234, 118, 170, 213, 190, 163, 204, 122, 204, 83, 177, 140, 146, 178, 24, 176, 116, 140, 12, 113, 157, 72, 70, 83, 21, 195, 148, 104, 138, 8, 84, 41, 57, 44, 104, 130, 219, 165, 125, 121, 67, 249, 45, 135, 226, 234, 252, 217, 159, 124, 187, 158, 89, 115, 159, 95, 254, 187, 252, 255, 93, 235, 171, 245, 159, 46, 155, 44, 202, 170, 237, 69, 254, 167, 8, 203, 223, 255, 243, 56, 196, 255, 27, 195, 62, 76, 8, 217, 134, 105, 87, 40, 111, 76, 22, 251, 208, 246, 81, 211, 242, 45, 53, 95, 119, 191, 114, 188, 144, 55, 148, 138, 195, 191, 237, 194, 62, 254, 53, 34, 2, 132, 63, 94, 137, 138, 25, 74, 78, 97, 49, 82, 58, 89, 126, 46, 165, 210, 76, 147, 0, 215, 78, 143, 220, 4, 229, 48, 239, 119, 197, 104, 233, 74, 35, 224, 147, 62, 143, 153, 118, 255, 126, 156, 55, 175, 249, 255, 23, 242, 110, 225, 221, 115, 176, 62, 54, 48, 233, 73, 116, 86, 162, 65, 149, 255, 243, 56, 196, 239, 23, 227, 50, 80, 0, 217, 132, 101, 178, 12, 5, 45, 8, 126, 212, 151, 180, 85, 153, 219, 41, 51, 197, 67, 151, 49, 207, 246, 252, 169, 163, 6, 203, 99, 46, 222, 72, 199, 147, 118, 247, 157, 221, 230, 125, 116, 92, 4, 147, 76, 7, 139, 146, 68, 72, 36, 50, 183, 198, 101, 55, 34, 82, 251, 207, 57, 167, 78, 57, 135, 221, 222, 142, 182, 239, 159, 143, 96, 76, 244, 209, 245, 255, 211, 90, 73, 245, 93, 93, 221, 89, 41, 33, 27, 7, 106, 165, 25, 104, 109, 149, 21, 90, 255, 243, 56, 196, 238, 20, 225, 218, 113, 158, 200, 70, 221, 13, 1, 130, 106, 174, 56, 10, 10, 2, 77, 60, 124, 240, 197, 49, 71, 55, 31, 9, 153, 111, 186, 241, 93, 183, 57, 195, 207, 94, 27, 10, 102, 175, 241, 96, 166, 146, 237, 41, 187, 249, 14, 132, 6, 26, 101, 6, 114, 112, 203, 69, 208, 65, 129, 177, 180, 157, 26, 203, 59, 12, 238, 169, 230, 55, 23, 243, 224, 67, 243, 238, 94, 179, 83, 159, 127, 35, 89, 229, 122, 87, 105, 78, 249, 63, 97, 158, 84, 238, 80, 189, 154, 80, 222, 9, 255, 243, 56, 196, 249, 24, 251, 62, 96, 60, 208, 134, 124, 61, 226, 26, 252, 135, 79, 89, 177, 174, 116, 178, 187, 194, 52, 132, 16, 101, 52, 207, 160, 213, 84, 27, 211, 86, 67, 114, 243, 216, 66, 95, 96, 230, 12, 24, 184, 176, 225, 57, 196, 24, 133, 170, 25, 166, 10, 96, 65, 46, 40, 57, 122, 186, 18, 123, 73, 68, 107, 246, 210, 91, 166, 251, 188, 189, 186, 140, 240, 149, 71, 179, 207, 27, 7, 72, 250, 62, 125, 95, 234, 109, 93, 107, 251, 110, 125, 122, 153, 161, 252, 63, 183, 203, 203, 124, 255, 243, 56, 196, 243, 20, 193, 202, 108, 94, 198, 68, 8, 245, 13, 211, 84, 56, 179, 157, 158, 73, 220, 163, 201, 44, 238, 54, 86, 151, 24, 188, 209, 234, 41, 120, 186, 69, 145, 25, 58, 17, 36, 41, 47, 174, 72, 125, 84, 147, 31, 98, 51, 35, 161, 157, 21, 1, 160, 237, 43, 245, 249, 22, 190, 210, 99, 14, 57, 128, 8, 0, 204, 171, 243, 18, 245, 18, 178, 15, 151, 126, 60, 37, 246, 179, 83, 242, 165, 51, 203, 58, 82, 23, 226, 115, 167, 121, 207, 248, 203, 204, 178, 248, 101, 97, 88, 159, 255, 243, 56, 196, 255, 26, 203, 58, 76, 8, 217, 134, 112, 11, 82, 135, 40, 39, 108, 169, 17, 15, 164, 25, 59, 118, 114, 75, 100, 124, 251, 9, 246, 75, 9, 122, 95, 130, 37, 83, 135, 10, 76, 194, 245, 190, 211, 239, 97, 248, 234, 232, 69, 77, 104, 17, 44, 98, 56, 231, 49, 201, 42, 148, 110, 150, 26, 145, 167, 106, 31, 103, 6, 158, 27, 3, 8, 180, 4, 229, 134, 51, 88, 112, 85, 142, 106, 199, 158, 206, 123, 88, 107, 41, 147, 112, 214, 90, 77, 97, 147, 5, 88, 38, 84, 85, 162, 170, 255, 243, 56, 196, 242, 23, 219, 62, 84, 8, 208, 134, 188, 98, 177, 18, 210, 169, 53, 73, 76, 86, 164, 180, 170, 77, 80, 105, 158, 73, 106, 101, 67, 208, 106, 150, 36, 177, 208, 160, 210, 139, 141, 18, 155, 176, 164, 42, 139, 255, 47, 125, 172, 87, 172, 63, 41, 191, 228, 254, 21, 21, 5, 40, 248, 214, 147, 139, 184, 255, 40, 211, 132, 129, 153, 113, 216, 211, 128, 203, 50, 227, 180, 156, 89, 101, 92, 118, 147, 139, 44, 171, 141, 242, 113, 101, 179, 198, 98, 51, 35, 79, 35, 50, 63, 255, 255, 148, 255, 243, 56, 196, 241, 25, 11, 54, 80, 18, 209, 134, 101, 138, 255, 101, 146, 255, 101, 146, 167, 217, 65, 2, 169, 245, 168, 32, 85, 62, 176, 48, 64, 170, 31, 88, 24, 32, 85, 15, 173, 65, 2, 168, 125, 106, 8, 21, 51, 233, 162, 39, 242, 170, 109, 253, 161, 76, 65, 77, 69, 51, 46, 49, 48, 48, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 255, 243, 56, 196, 235, 23, 120, 254, 68, 0, 126, 6, 9, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 255, 243, 56, 196, 236, 22, 114, 181, 192, 0, 48, 71, 105, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85]}
|
{"id": 0, "comefrom": "<qiyuangong>011_Container_With_Most_Water_1.java", "code": "public int maxArea(int[] height) {\n\n int maxArea = 0;\n int left = 0;\n int right = height.length - 1;\n\n while (left < right) {\n maxArea = Math.max(maxArea, (right - left) * Math.min(height[left], height[right]));\n if (height[left] < height[right]) left++;\n else right--;\n }\n return maxArea;\n }", "masked": "public int sample_funcname ( int [ ] var_0 ) {\n int var_1 = 0 ;\n int var_2 = 0 ;\n int var_3 = var_0 . length - 1 ;\n while ( var_2 < var_3 ) {\n var_1 = Math . max ( var_1 , ( var_3 - var_2 ) * Math . min ( var_0 [ var_2 ] , var_0 [ var_3 ] ) ) ;\n if ( var_0 [ var_2 ] < var_0 [ var_3 ] ) var_2 ++ ;\n else var_3 -- ;\n }\n return var_1 ;\n}\n", "unique_words_num": 2, "words": "0<SEP>1"}
|
{"id": 2, "comefrom": "<qiyuangong>005_Longest_Palindromic_Substring_3.java", "code": "private static char[] removeBoundaries(char[] cs) {\n if (cs==null || cs.length<3)\n return \"\".toCharArray();\n\n char[] cs2 = new char[(cs.length-1)/2];\n for (int i = 0; i<cs2.length; i++) {\n cs2[i] = cs[i*2+1];\n }\n return cs2;\n }", "masked": "private static char [ ] sample_funcname ( char [ ] var_0 ) {\n if ( var_0 == null || var_0 . length < 3 ) return \"\" . toCharArray ( ) ;\n char [ ] var_1 = new char [ ( var_0 . length - 1 ) / 2 ] ;\n for ( int var_2 = 0 ;\n var_2 < var_1 . length ;\n var_2 ++ ) {\n var_1 [ var_2 ] = var_0 [ var_2 * 2 + 1 ] ;\n }\n return var_1 ;\n}\n", "unique_words_num": 5, "words": "2<SEP>0<SEP>1<SEP>3<SEP><D_QUOTE><D_QUOTE>"}
|
{"id": 5, "comefrom": "<qiyuangong>1323_Maximum_69_Number_1.java", "code": "public int maximum69Number (int num) {\n return Integer.valueOf(String.valueOf(num).replaceFirst(\"6\", \"9\"));\n }", "masked": "public int sample_funcname ( int var_0 ) {\n return Integer . valueOf ( String . valueOf ( var_0 ) . replaceFirst ( \"6\" , \"9\" ) ) ;\n}\n", "unique_words_num": 2, "words": "<D_QUOTE>9<D_QUOTE><SEP><D_QUOTE>6<D_QUOTE>"}
|
{"id": 6, "comefrom": "<qiyuangong>692_Top_K_Frequent_Words_2.java", "code": "public List<String> topKFrequent(String[] words, int k) {\n Map<String, Integer> count = new HashMap();\n for (String word: words) {\n count.put(word, count.getOrDefault(word, 0) + 1);\n }\n PriorityQueue<String> heap = new PriorityQueue<String>(\n (w1, w2) -> count.get(w1).equals(count.get(w2)) ?\n w2.compareTo(w1) : count.get(w1) - count.get(w2) );\n\n for (String word: count.keySet()) {\n heap.offer(word);\n if (heap.size() > k) heap.poll();\n }\n\n List<String> ans = new ArrayList();\n while (!heap.isEmpty()) ans.add(heap.poll());\n Collections.reverse(ans);\n return ans;\n }", "masked": "public List < String > var_0 ( String [ ] var_1 , int var_2 ) {\n Map < String , Integer > var_3 = new HashMap ( ) ;\n for ( String var_4 : var_1 ) {\n var_3 . put ( var_4 , var_3 . getOrDefault ( var_4 , 0 ) + 1 ) ;\n }\n PriorityQueue < String > var_7 = new PriorityQueue < String > ( ( var_5 , var_6 ) -> var_3 . get ( var_5 ) . equals ( var_3 . get ( var_6 ) ) ? var_6 . compareTo ( var_5 ) : var_3 . get ( var_5 ) - var_3 . get ( var_6 ) ) ;\n for ( String var_4 : var_3 . keySet ( ) ) {\n var_7 . offer ( var_4 ) ;\n if ( var_7 . size ( ) > var_2 ) var_7 . poll ( ) ;\n }\n List < String > var_8 = new ArrayList ( ) ;\n while ( ! var_7 . isEmpty ( ) ) var_8 . add ( var_7 . poll ( ) ) ;\n Collections . reverse ( var_8 ) ;\n return var_8 ;\n}\n", "unique_words_num": 2, "words": "0<SEP>1"}
|
{"id": 8, "comefrom": "<qiyuangong>007_Reverse_Integer_1.java", "code": "public int reverse(int x) {\n if (x == 0) return 0;\n long res = 0;\n while (x != 0) {\n res = res * 10 + x % 10;\n if (res > Integer.MAX_VALUE || res < Integer.MIN_VALUE)\n return 0;\n x /= 10;\n }\n return (int) res;\n }", "masked": "public int sample_funcname ( int var_0 ) {\n if ( var_0 == 0 ) return 0 ;\n long var_1 = 0 ;\n while ( var_0 != 0 ) {\n var_1 = var_1 * 10 + var_0 % 10 ;\n if ( var_1 > Integer . MAX_VALUE || var_1 < Integer . MIN_VALUE ) return 0 ;\n var_0 /= 10 ;\n }\n return ( int ) var_1 ;\n}\n", "unique_words_num": 2, "words": "10<SEP>0"}
|
{"text": "Shape of You Lyrics\nThe club isnt the best place to find a lover\nSo the bar is where I go\nMe and my friends at the table doing shots\nDrinking fast and then we talk slow\nAnd you come over and start up a conversation with just me\nAnd trust me Ill give it a chance now\nTake my hand, stop, put Van the Man on the jukebox\nAnd then we start to dance, and now Im singing like\nGirl, you know I want your love\nYour love was handmade for somebody like me\nCome on now, follow my lead\nI may be crazy, dont mind me\nSay, boy, lets not talk too much\nGrab on my waist and put that body on me\nCome on now, follow my lead\nCome, come on now, follow my lead\nIm in love with the shape of you\nWe push and pull like a magnet do\nAlthough my heart is falling too\nIm in love with your body\nAnd last night you were in my room\nAnd now my bed sheets smell like you\nEvery day discovering something brand new\nIm in love with your body\nOh, I, oh, I, oh, I, oh, I\nIm in love with your body\nOh, I, oh, I, oh, I, oh, I\nIm in love with your body\nOh, I, oh, I, oh, I, oh, I\nIm in love with your body\nEvery day discovering something brand new\nIm in love with the shape of you\nOne week in we let the story begin\nWere going out on our first date\nYou and me are thrifty, so go all you can eat\nFill up your bag and I fill up a plate\nWe talk for hours and hours about the sweet and the sour\nAnd how your family is doing okay\nLeave and get in a taxi, then kiss in the backseat\nTell the driver make the radio play, and Im singing like\nGirl, you know I want your love\nYour love was handmade for somebody like me\nCome on now, follow my lead\nI may be crazy, dont mind me\nSay, boy, lets not talk too much\nGrab on my waist and put that body on me\nCome on now, follow my lead\nCome, come on now, follow my lead\nIm in love with the shape of you\nWe push and pull like a magnet do\nAlthough my heart is falling too\nIm in love with your body\nAnd last night you were in my room\nAnd now my bed sheets smell like you\nEvery day discovering something brand new\nIm in love with your body\nOh, I, oh, I, oh, I, oh, I\nIm in love with your body\nOh, I, oh, I, oh, I, oh, I\nIm in love with your body\nOh, I, oh, I, oh, I, oh, I\nIm in love with your body\nEvery day discovering something brand new\nIm in love with the shape of you\nCome on, be my baby, come on\nCome on, be my baby, come on\nCome on, be my baby, come on\nCome on, be my baby, come on\nCome on, be my baby, come on\nCome on, be my baby, come on\nCome on, be my baby, come on\nCome on, be my baby, come on\nIm in love with the shape of you\nWe push and pull like a magnet do\nAlthough my heart is falling too\nIm in love with your body\nLast night you were in my room\nAnd now my bed sheets smell like you\nEvery day discovering something brand new\nIm in love with your body\nCome on, be my baby, come on\nCome on, be my baby, come on\nIm in love with your body\nCome on, be my baby, come on\nCome on, be my baby, come on\nIm in love with your body\nCome on, be my baby, come on\nCome on, be my baby, come on\nIm in love with your body\nEvery day discovering something brand new\nIm in love with the shape of you405Embed"}
|
{"text": "Perfect Lyrics\nI found a love for me\nOh darling, just dive right in and follow my lead\nWell, I found a girl, beautiful and sweet\nOh, I never knew you were the someone waiting for me\nCause we were just kids when we fell in love\nNot knowing what it was\nI will not give you up this time\nBut darling, just kiss me slow, your heart is all I own\nAnd in your eyes, youre holding mine\nBaby, Im dancing in the dark with you between my arms\nBarefoot on the grass, listening to our favourite song\nWhen you said you looked a mess, I whispered underneath my breath\nBut you heard it, darling, you look perfect tonight\nWell I found a woman, stronger than anyone I know\nShe shares my dreams, I hope that someday Ill share her home\nI found a love, to carry more than just my secrets\nTo carry love, to carry children of our own\nWe are still kids, but were so in love\nFighting against all odds\nI know well be alright this time\nDarling, just hold my hand\nBe my girl, Ill be your man\nI see my future in your eyes\nBaby, Im dancing in the dark, with you between my arms\nBarefoot on the grass, listening to our favorite song\nWhen I saw you in that dress, looking so beautiful\nI dont deserve this, darling, you look perfect tonight\nBaby, Im dancing in the dark, with you between my arms\nBarefoot on the grass, listening to our favorite song\nI have faith in what I see\nNow I know I have met an angel in person\nAnd she looks perfect\nI dont deserve this\nYou look perfect tonight258Embed"}
|
{"text": "Love Yourself Lyrics\nFor all the times that you rained on my parade\nAnd all the clubs you get in using my name\nYou think you broke my heart, oh girl, for goodness sake\nYou think Im cryin on my own, well I aint\nAnd I didnt wanna write a song\nCause I didnt want anyone thinking I still care\nI dont, but you still hit my phone up\nAnd baby, Ill be movin on\nAnd I think you should be somethin I dont wanna hold back\nMaybe you should know that\nMy mama dont like you and she likes everyone\nAnd I never like to admit that I was wrong\nAnd Ive been so caught up in my job, didnt see whats going on\nBut now I know, Im better sleeping on my own\nCause if you like the way you look that much\nOh baby, you should go and love yourself\nAnd if you think that Im still holdin on to somethin\nYou should go and love yourself\nBut when you told me that you hated my friends\nThe only problem was with you and not them\nAnd every time you told me my opinion was wrong\nAnd tried to make me forget where I came from\nAnd I didnt wanna write a song\nCause I didnt want anyone thinking I still care\nI dont, but you still hit my phone up\nAnd baby, Ill be movin on\nAnd I think you should be somethin I dont wanna hold back\nMaybe you should know that\nMy mama dont like you and she likes everyone\nAnd I never like to admit that I was wrong\nAnd Ive been so caught up in my job, didnt see whats going on\nBut now I know, Im better sleeping on my own\nCause if you like the way you look that much\nOh baby, you should go and love yourself\nAnd if you think that Im still holdin on to somethin\nYou should go and love yourself\nFor all the times that you made me feel small\nI fell in love, now I feel nothin at all\nI never felt so low and I was vulnerable\nWas I a fool to let you break down my walls?\nCause if you like the way you look that much\nOh baby, you should go and love yourself\nAnd if you think that Im still holdin on to somethin\nYou should go and love yourself\nCause if you like the way you look that much\nOh baby, you should go and love yourself\nAnd if you think that Im still holdin on to somethin\nYou should go and love yourself150Embed"}
|
{"text": "River Lyrics\nIve been a liar, been a thief\nBeen a lover, been a cheat\nAll my sins need holy water, feel it washing over me\nWell, little one, I dont want to admit to something\nIf all its gonna cause is pain\nTruth and my lies right now are falling like the rain\nSo let the river run\nHes comin home with his neck scratched, to catch flack\nSweat jackets and dress slacks, mismatched\nOn his breaths Jack, hes a sex addict\nAnd she just wants to exact revenge and get back\nIts a chess match, shes on his back like a jet-pack\nShes kept track of all his Internet chats\nAnd guess who just happens to be movin on to the next\nActually, just shit on my last chick and she has what my ex lacks\nCause she loves danger, psychopath\nAnd you dont fuck with no mans girl, even I know that\nBut shes devised some plan to stab him in the back\nKnife in hand, says their relationships hangin by a strand\nSo shes been on the web lately\nSays maybe shell be my Gwen Stacy, to spite her man\nAnd I know shes using me to try to play him, I dont care\nHi Suzanne, but I shoulda said Bye Suzanne\nAfter the first night, but tonight I am\nIve been a liar, been a thief\nBeen a lover, been a cheat\nAll my sins need holy water, feel it washing over me\nWell, little one, I dont want to admit to something\nIf all its gonna cause is pain\nThe truth and my lies now are falling like the rain\nSo let the river run\nA one-night stand turned a two-night stand\nIt was come sunlight, scram, now we hug tight, and...\nHe found out, now she feels deserted and used\nCause he left, so what? He did it first to her too\nNow how am I supposed to tell this girl that were through?\nIts hard to find the words, Im aloof, nervous, and Sue\nDont want this to hurt, but what you deserve is the truth\nDont take it personal, I just cant say this in person to you\nSo I revert to the studio, like hole-in-the-wall diners\nDont have to be reserved in a booth\nI just feel like the person who Im turning intos\nIrreversible, I preyed on you like its church at the pew\nAnd now that I got you I dont want you\nTook advantage in my thirst to pursue\nWhy do I do this dirt that I do?\nGet on my soapbox and preach, my sermon and speech\nDetergent and bleach is burnin the wound\nCause now with her in the womb\nWe cant bring her in this world, shoulda knew\nTo use protection fore I bit into your forbidden fruit\nFuck!\nIve been a liar, been a thief\nBeen a lover, been a cheat\nAll my sins need holy water, feel it washing over me\nWell, little one, I dont want to admit to something\nIf all its gonna cause is pain\nThe truth and my lies now are falling like the rain\nSo let the river run\nMy names , my names \nRiver , river run\nCall me , call me \nRiver , well let the river run\nAlways the bridesmaid, never The bride, hey!\nFuck can I say? If life was a highway\nAnd deceit was an enclave, Id be swerving in five lanes\nSpeeds at a high rate, like Im slidin on ice, maybe\nThats why I may have came at you sideways\nI cant keep my lies straight\nBut I made you terminate my baby\nThis love triangle left us in a wreck, tangled\nWhat else can I say? It was fun for a while\nBet I really woulda loved your smile\nDidnt really wanna abort, but fuck it\nWhats one more lie, to tell our unborn child?\nIve been a liar, been a thief\nBeen a lover, been a cheat\nAll my sins need holy water, feel it washing over me\nWell, little one \nI dont want to admit to something \nIf all its gonna cause is pain\nThe truth and my lies now are falling like the rain\nSo let the river run477Embed"}
|
{"text": "Castle on the Hill Lyrics\nWhen I was six years old I broke my leg\nI was running from my brother and his friends\nAnd tasted the sweet perfume of the mountain grass I rolled down\nI was younger then, take me back to when I\nFound my heart and broke it here\nMade friends and lost them through the years\nAnd Ive not seen the roaring fields in so long, I know Ive grown\nBut I cant wait to go home\nIm on my way\nDriving at 90 down those country lanes\nSinging to Tiny Dancer\nAnd I miss the way you make me feel, and its real\nWe watched the sunset over the castle on the hill\nFifteen years old and smoking hand-rolled cigarettes\nRunning from the law through the backfields and getting drunk with my friends\nHad my first kiss on a Friday night, I dont reckon that I did it right\nBut I was younger then, take me back to when\nWe found weekend jobs, when we got paid\nWed buy cheap spirits and drink them straight\nMe and my friends have not thrown up in so long, oh how weve grown\nBut I cant wait to go home\nIm on my way\nDriving at 90 down those country lanes\nSinging to Tiny Dancer\nAnd I miss the way you make me feel, and its real\nWe watched the sunset over the castle on the hill\nOver the castle on the hill\nOver the castle on the hill\nOne friend left to sell clothes\nOne works down by the coast\nOne had two kids but lives alone\nOnes brother overdosed\nOnes already on his second wife\nOnes just barely getting by\nBut these people raised me\nAnd I cant wait to go home\nAnd Im on my way, I still remember\nThese old country lanes\nWhen we did not know the answers\nAnd I miss the way you make me feel, its real\nWe watched the sunset over the castle on the hill\nOver the castle on the hill\nOver the castle on the hill89Embed"}
|
{"text": "Freaky Friday Lyrics\nLil Dicky, ooh\nMustard on the beat, ho\nI woke up Chris Breezy, oh my god Im the man \nIm so fly and I can dance \nTheres tattoos on my neck \nI just FaceTimed Kanye \nI told him Im his biggest fan, yeah \nGot all these hoes in my DM \nHoly shit, I got a kid \nOhh, I can sing so well\nWonder if I can say the n-word \nWait, can I really say the n-word?\nWhat up, my nigga? What up, my nigga?\nBig ups, my nigga, we up, my nigga\nYou pussy ass nigga, man, fuck yall niggas\nCause Im that nigga, nigga, nigga, nigga\nIm that nigga\nI woke up in Chris Browns body \nSomehow this shit turned into Freaky Friday\nBut we got no choice but to turn this bitch sideways\nI cant believe that its Freaky Friday\nYeah, its Freaky Friday\nIm in Chris Browns body\nI drive his Ferrari and Im light-skinned black\n What the fuck?\nI woke up and Im Lil Dicky \nUgh, what the fuck?\nThis shit is real weak\nHow his dick staying perched up on his balls like that?\nWalking down the street and aint nobody know my name \nAint no paparazzi flashing pictures, this is great \nAint nobody judging cause Im black or my controversial past\nIma go and see a movie and relax \nAyy, Im a Blood but I can finally wear blue \nWhy his momma calling all the time?\nLeave me the fuck alone, bitch\nWait, if Im in Dickys body, Breezy is who?\nHope my daughters in school\nFuck, if I was Chris Brown, where would I be?\nWhat would I do?\nI woke up in Chris Browns body \nSomehow this shit turned into Freaky Friday\nBut we got no choice but to turn this bitch sideways\nI cant believe that its Freaky Friday\nYeah, its Freaky Friday\nIm in Chris Browns body\nI look at my soft dick with delight, its my dream dick\nIf I was Lil Dicky in my body, where would I be?\nIm tryna to find myself like an introspective monk\nIm balling on the court, oh my god I can dunk\nSnap a flick of my junk\nMy dick is trending on Twitter? Fuck\nNow Im at the club, I talked my way into getting in\nI look up in the VIP, my goodness there I am\nI signal to him to let me in but he wont let me in\nI dont know who that is\nWait, who the fuck he think he is?\nTook a glass bottle, shatter it on the bouncers head \nWalked up to that motherfucker\nWait, think it through for a sec\nIf you hurting me then you only hurting yourself\nBut wait, I love myself\nThat was the key, now were switching back\nI woke up in Chris Browns body \nSomehow this shit turned into Freaky Friday\nBut we got no choice but to turn this bitch sideways\nI cant believe that its Freaky Friday\nLil Dicky: Wait, what the fuck?\nEd Sheeran: And now Im in Ed Sheerans body\nIts way less cool than being Chris Brown was\nLil Dicky: What the fuck again?\nDJ Khaled: Im DJ Khaled\nWhy am I yelling?\nKendall Jenner: Huh, Im Kendall Jenner\nI got a vagina, Im gonna explore that right now \nHoly shit, I got a vagina , Im gonna learn\nIm gonna understand the inner workings of a woman115Embed"}
|
{"text": "Perfect Duet Lyrics\nI found a love for me\nOh darling, just dive right in and follow my lead\nWell, I found a girl, beautiful and sweet\nOh, I never knew you were the someone waitin for me\nCause we were just kids when we fell in love\nNot knowin what it was\nI will not give you up this time\nBut darling, just kiss me slow, your heart is all I own\nAnd in your eyes, youre holding mine\nBaby, Im dancing in the dark with you between my arms\nBarefoot on the grass, listening to our favourite song\nWhen you said you looked a mess, I whispered underneath my breath\nBut you heard it, darling, you look perfect tonight\nWell, I found a man stronger than anyone I know\nHe shares my dreams, I hope that someday well share a home\nI found a love to carry more than just my secrets\nTo carry love, to carry children of our own\nWe are still kids, but were so in love\nFightin against all odds\nI know well be alright this time\nDarling, just hold my hand\nBe your girl, youll be my man\nAnd I see my future in your eyes\nWell, baby, Im dancing in the dark with you between my arms\nBarefoot on the grass while listening to our favorite song\nWhen I saw you in that dress looking so beautiful\nI dont deserve this, darling, you look perfect tonight\nBaby, Im dancing in the dark with you between my arms\nBarefoot on the grass, while listenin to our favorite song\nI have faith in what I see\nNow I know I have met an angel in person\nAnd she looks perfect, and he looks perfect\nNo, I dont deserve this\nYou look perfect tonight49Embed"}
|
{"text": "Supermarket Flowers Lyrics\nI took the supermarket flowers from the windowsill\nI threw the day old tea from the cup\nPacked up the photo album Matthew had made\nMemories of a life thats been loved\nTook the get well soon cards and stuffed animals\nPoured the old ginger beer down the sink\nDad always told me, Dont you cry when youre down\nBut mum, theres a tear every time that I blink\nOh, Im in pieces, its tearing me up, but I know\nA heart thats broke is a heart thats been loved\nSo Ill sing Hallelujah\nYou were an angel in the shape of my mum\nWhen I fell down youd be there holding me up\nSpread your wings as you go\nWhen God takes you back\nHell say, Hallelujah, youre home\nI fluffed the pillows, made the beds, stacked the chairs up\nFolded your nightgowns neatly in a case\nJohn says hed drive then put his hand on my cheek\nAnd wiped a tear from the side of my face\nI hope that I see the world as you did cause I know\nA life with love is a life thats been lived\nSo Ill sing Hallelujah\nYou were an angel in the shape of my mum\nWhen I fell down youd be there holding me up\nSpread your wings as you go\nWhen God takes you back\nHell say, Hallelujah, youre home\nHallelujah\nYou were an angel in the shape of my mum\nYou got to see the person I have become\nSpread your wings and I know\nThat when God took you back\nHe said, Hallelujah, youre home73Embed"}
|
{"repo_id": "17651/TESR", "sdk": "streamlit", "likes": 0, "user_name": "17651", "repo_name": "TESR", "repo_url": "https://huggingface.co/spaces/17651/TESR", "inputs": null, "outputs": null, "is_processed": false, "ai_ml_reqs": null, "last_commit": "7 months ago", "total_commits": 1.0, "status": "No application file", "community_interactions": 0.0}
|
{"repo_id": "17939225/cartest", "sdk": "streamlit", "likes": 0, "user_name": "17939225", "repo_name": "cartest", "repo_url": "https://huggingface.co/spaces/17939225/cartest", "inputs": null, "outputs": null, "is_processed": false, "ai_ml_reqs": null, "last_commit": "7 months ago", "total_commits": 1.0, "status": "No application file", "community_interactions": 0.0}
|
{"repo_id": "52Hz/CMFNet_deblurring", "sdk": "gradio", "likes": 12, "user_name": "52Hz", "repo_name": "CMFNet_deblurring", "repo_url": "https://huggingface.co/spaces/52Hz/CMFNet_deblurring", "inputs": "Image", "outputs": "Image", "is_processed": true, "ai_ml_reqs": "torch", "last_commit": "5 months ago", "total_commits": 29.0, "status": "Running", "community_interactions": 0.0}
|
{"repo_id": "52Hz/CMFNet_dehazing", "sdk": "gradio", "likes": 3, "user_name": "52Hz", "repo_name": "CMFNet_dehazing", "repo_url": "https://huggingface.co/spaces/52Hz/CMFNet_dehazing", "inputs": "Image", "outputs": "Image", "is_processed": true, "ai_ml_reqs": "torch", "last_commit": "5 months ago", "total_commits": 21.0, "status": "Running", "community_interactions": 0.0}
|
{"repo_id": "52Hz/CMFNet_deraindrop", "sdk": "gradio", "likes": 10, "user_name": "52Hz", "repo_name": "CMFNet_deraindrop", "repo_url": "https://huggingface.co/spaces/52Hz/CMFNet_deraindrop", "inputs": "Image", "outputs": "Image", "is_processed": true, "ai_ml_reqs": "torch", "last_commit": "5 months ago", "total_commits": 54.0, "status": "Running", "community_interactions": 0.0}
|
{"repo_id": "52Hz/HWMNet_lowlight_enhancement", "sdk": "gradio", "likes": 3, "user_name": "52Hz", "repo_name": "HWMNet_lowlight_enhancement", "repo_url": "https://huggingface.co/spaces/52Hz/HWMNet_lowlight_enhancement", "inputs": "Image,Dropdown", "outputs": "Image", "is_processed": true, "ai_ml_reqs": "torch", "last_commit": "5 months ago", "total_commits": 26.0, "status": "Running", "community_interactions": 0.0}
|
{"repo_id": "52Hz/SRMNet_AWGN_denoising", "sdk": "gradio", "likes": 7, "user_name": "52Hz", "repo_name": "SRMNet_AWGN_denoising", "repo_url": "https://huggingface.co/spaces/52Hz/SRMNet_AWGN_denoising", "inputs": "Image", "outputs": "Image", "is_processed": true, "ai_ml_reqs": "torch", "last_commit": "about 9 hours ago", "total_commits": 31.0, "status": "Running", "community_interactions": 0.0}
|
{"repo_id": "52Hz/SRMNet_real_world_denoising", "sdk": "gradio", "likes": 12, "user_name": "52Hz", "repo_name": "SRMNet_real_world_denoising", "repo_url": "https://huggingface.co/spaces/52Hz/SRMNet_real_world_denoising", "inputs": "Image", "outputs": "Image", "is_processed": true, "ai_ml_reqs": "torch", "last_commit": "about 9 hours ago", "total_commits": 67.0, "status": "Running", "community_interactions": 0.0}
|
{"repo_id": "52Hz/SUNet_AWGN_denoising", "sdk": "gradio", "likes": 8, "user_name": "52Hz", "repo_name": "SUNet_AWGN_denoising", "repo_url": "https://huggingface.co/spaces/52Hz/SUNet_AWGN_denoising", "inputs": "Image", "outputs": "Image", "is_processed": true, "ai_ml_reqs": "torch", "last_commit": "28 days ago", "total_commits": 42.0, "status": "Running", "community_interactions": 0.0}
|
{"repo_id": "609ead0502/test", "sdk": "gradio", "likes": 0, "user_name": "609ead0502", "repo_name": "test", "repo_url": "https://huggingface.co/spaces/609ead0502/test", "inputs": null, "outputs": null, "is_processed": false, "ai_ml_reqs": null, "last_commit": "6 months ago", "total_commits": 1.0, "status": "No application file", "community_interactions": 0.0}
|
{"text": "Yeah \nSo, you say youre moving out of state\nSoon as you graduate, interesting \nAnyway, youre leaving\nNeed a hug? Okay then\nCall me up, no thanks, man \nIm too busy, dont have time for\nThings you say that arent important\nWheres the bathroom at?\nLeave me alone\nI just came here to the party for the drugs \nDrugs , drugs \nIm not tryna make a friend or fall in love \nLove , love \nSo just stop the faking\nNot here for nameless faces\nPointless talking, conversations \nDrugs , drugs \nI just came here for the drugs\nLook whos here, pink t-shirt\nOh, you met him last year?\nWish I was as cool as you \nCheck it out, you got that\nBrand new Audi hatchback\nBut you came here alone\nYoure too drunk to drive home \nIm too busy, dont have time for\nThings you say that arent important\nWheres the bathroom at?\nLeave me alone\nI just came here to the party for the drugs \nDrugs , drugs \nIm not tryna make a friend or fall in love \nLove , love \nSo just stop the faking\nNot here for nameless faces\nPointless talking, conversations \nDrugs , drugs \nI just came here for the drugs\nEverybodys either here for the drugs\nOr the sex or the money or the fame\nHes on the phone asking someone for the plug\nAnd shes on the couch small talking, dropping names\nIm not here for nameless faces\nPointless talking, conversations \nDrugs , drugs\nBut I just came here for the"}
|
{"text": "Im lettin you in, youre lettin me down \nI swear when you talk you just like the sound \nOne too many times I, let you ruin my life cause\nI thought you would change but I see it now \nAll the yellin and kissin and fightin\nWe never could see eye to eye\nCause you might seem like a man but youre not one in your mind\nYeah, Im back on my shit and its temptin\nTo call you and see how youre doin\nBut I couldnt understand you if I tried\nI dont speak boyshit\nYoure always coming back but your loves poison\nSo I think that I would rather just avoid it\nI cant understand ya cause I dont speak boy, no\nI dont speak, I dont speak, I dont speak boyshit \nDont know how to talk or communicate \nWere so on and off to you its a game \nIf you dont level up, Im, leavin you in the dust, yeah\nSo Im movin on until you start tryna to act your age, yeah \nCause I dont speak boyshit\nYoure always coming back but your loves poison\nSo I think that I would rather just avoid it\nI cant understand ya cause I dont speak boy, no\nI dont speak, I dont speak, I dont speak\nAll the yellin and kissin and fightin\nWe never could see eye to eye, yeah\nYou might seem like a man but youre not one in your mind\nYeah, Im back on my shit and its temptin\nTo call you and see how youre doin\nBut I couldnt understand you if I tried\nCause I dont speak boyshit \nBoyshit \nCause I dont speak boy, no\nBoyshit \nCause I dont speak boyshit\nSo tryna get through to you is pointless\nYou might have a way with words but Im a woman\nI cant understand you\nCause I dont speak boy, no\nI dont speak, I dont speak, I dont speak boyshit \nI dont speak boyshit\nI dont speak boyshit\nCause I dont speak boy, no\nI dont speak, I dont speak, I dont speak boyshit"}
|
{"abstract": "OBJECTIVE: This retrospective chart review describes the epidemiology and clinical features of 40 patients with culture-proven Mycoplasma pneumoniae infections at King Abdulaziz University Hospital, Jeddah, Saudi Arabia. METHODS: Patients with positive M. pneumoniae cultures from respiratory specimens from January 1997 through December 1998 were identified through the Microbiology records. Charts of patients were reviewed. RESULTS: 40 patients were identified, 33 (82.5%) of whom required admission. Most infections (92.5%) were community-acquired. The infection affected all age groups but was most common in infants (32.5%) and pre-school children (22.5%). It occurred year-round but was most common in the fall (35%) and spring (30%). More than three-quarters of patients (77.5%) had comorbidities. Twenty-four isolates (60%) were associated with pneumonia, 14 (35%) with upper respiratory tract infections, and 2 (5%) with bronchiolitis. Cough (82.5%), fever (75%), and malaise (58.8%) were the most common symptoms, and crepitations (60%), and wheezes (40%) were the most common signs. Most patients with pneumonia had crepitations (79.2%) but only 25% had bronchial breathing. Immunocompromised patients were more likely than non-immunocompromised patients to present with pneumonia (8/9 versus 16/31, P = 0.05). Of the 24 patients with pneumonia, 14 (58.3%) had uneventful recovery, 4 (16.7%) recovered following some complications, 3 (12.5%) died because of M pneumoniae infection, and 3 (12.5%) died due to underlying comorbidities. The 3 patients who died of M pneumoniae pneumonia had other comorbidities. CONCLUSION: our results were similar to published data except for the finding that infections were more common in infants and preschool children and that the mortality rate of pneumonia in patients with comorbidities was high."}
|
{"abstract": "Surfactant protein-D (SP-D) participates in the innate response to inhaled microorganisms and organic antigens, and contributes to immune and inflammatory regulation within the lung. SP-D is synthesized and secreted by alveolar and bronchiolar epithelial cells, but is also expressed by epithelial cells lining various exocrine ducts and the mucosa of the gastrointestinal and genitourinary tracts. SP-D, a collagenous calcium-dependent lectin (or collectin), binds to surface glycoconjugates expressed by a wide variety of microorganisms, and to oligosaccharides associated with the surface of various complex organic antigens. SP-D also specifically interacts with glycoconjugates and other molecules expressed on the surface of macrophages, neutrophils, and lymphocytes. In addition, SP-D binds to specific surfactant-associated lipids and can influence the organization of lipid mixtures containing phosphatidylinositol in vitro. Consistent with these diverse in vitro activities is the observation that SP-D-deficient transgenic mice show abnormal accumulations of surfactant lipids, and respond abnormally to challenge with respiratory viruses and bacterial lipopolysaccharides. The phenotype of macrophages isolated from the lungs of SP-D-deficient mice is altered, and there is circumstantial evidence that abnormal oxidant metabolism and/or increased metalloproteinase expression contributes to the development of emphysema. The expression of SP-D is increased in response to many forms of lung injury, and deficient accumulation of appropriately oligomerized SP-D might contribute to the pathogenesis of a variety of human lung diseases."}
|
{"abstract": "Endothelin-1 (ET-1) is a 21 amino acid peptide with diverse biological activity that has been implicated in numerous diseases. ET-1 is a potent mitogen regulator of smooth muscle tone, and inflammatory mediator that may play a key role in diseases of the airways, pulmonary circulation, and inflammatory lung diseases, both acute and chronic. This review will focus on the biology of ET-1 and its role in lung disease."}
|
{"abstract": "Respiratory syncytial virus (RSV) and pneumonia virus of mice (PVM) are viruses of the family Paramyxoviridae, subfamily pneumovirus, which cause clinically important respiratory infections in humans and rodents, respectively. The respiratory epithelial target cells respond to viral infection with specific alterations in gene expression, including production of chemoattractant cytokines, adhesion molecules, elements that are related to the apoptosis response, and others that remain incompletely understood. Here we review our current understanding of these mucosal responses and discuss several genomic approaches, including differential display reverse transcription-polymerase chain reaction (PCR) and gene array strategies, that will permit us to unravel the nature of these responses in a more complete and systematic manner."}
|
{"abstract": "Recent evidence suggests that critically ill patients are able to tolerate lower levels of haemoglobin than was previously believed. It is our goal to show that transfusing to a level of 100 g/l does not improve mortality and other clinically important outcomes in a critical care setting. Although many questions remain, many laboratory and clinical studies, including a recent randomized controlled trial (RCT), have established that transfusing to normal haemoglobin concentrations does not improve organ failure and mortality in the critically ill patient. In addition, a restrictive transfusion strategy will reduce exposure to allogeneic transfusions, result in more efficient use of red blood cells (RBCs), save blood overall, and decrease health care costs."}
|
{"abstract": "The 21st International Symposium on Intensive Care and Emergency Medicine was dominated by the results of recent clinical trials in sepsis and acute respiratory distress syndrome (ARDS). The promise of extracorporeal liver replacement therapy and noninvasive ventilation were other areas of interest. Ethical issues also received attention. Overall, the 'state of the art' lectures, pro/con debates, seminars and tutorials were of a high standard. The meeting was marked by a sense of renewed enthusiasm that positive progress is occurring in intensive care medicine."}
|
{"content": "The 'ud () was a stringed Zakharan instrument similar to both the lute and guitar.", "page": "'Ud"}
|
{"content": "The 'Ud of the Marids was a beautiful magical 'ud created by marid luthiers to be presented to the new high chieftain of the jann of the High Desert on his ascension day.", "page": "'Ud of the marids"}
|
{"content": "The Fourth Crown War ends.", "page": "-10000 DR"}
|
{"content": "The Illuskans of Ruathym start to colonize many islands of the Trackless Sea, such as Umukek and Tuern.", "page": "-1000 DR"}
|
{"content": "The volcano known as The Hazardous Climb becomes inactive. Although a popular place to go mountaineering, no one ever reaches the 27,000-foot-high (8.2-kilometer-high) summit.", "page": "-1005 DR"}
|
{"content": "Delzoun, the Northkingdom, meets its end before the advancing phaerimms and other threats. Its citadels on the surface survive and stay under dwarven control.", "page": "-100 DR"}
|
{"content": "Shantel Othreier is destroyed by Ilythiir during the Fourth Crown War.", "page": "-10100 DR"}
|
{"content": "Circa: The dark elves of Ilythiir use enslaved dragons and other powers to burn Shantel Othreier. In half-a-century, over 70% of the forest is destroyed. In Illefarn and other neutral and free areas, over 1000 priests and High Mages react by spending decades in prayer to Corellon Larethian and the Seldarine, begging for salvation.", "page": "-10110 DR"}
|
{"text": "\"............Again. ...So, you still haven't overcome your love of alcohol?\""}
|
{"text": "== Narrator =="}
|
{"text": "The old physician let out a sigh as he removed the stethoscope."}
|
{"text": "Two elderly men could be seen in the dimly-lit study, which was filled with dust and a sickly-sweet stench."}
|
{"rem": "public synchronized StringBuffer append(char ch)", "add": "public StringBuffer append(Object obj)", "context": " public synchronized StringBuffer append(char ch) { ensureCapacity_unsynchronized(count + 1); value[count++] = ch; return this; }"}
|
{"rem": "ensureCapacity_unsynchronized(count + 1); value[count++] = ch; return this;", "add": "return append(obj == null ? \"null\" : obj.toString());", "context": " public synchronized StringBuffer append(char ch) { ensureCapacity_unsynchronized(count + 1); value[count++] = ch; return this; }"}
|
{"rem": "public String substring(int beginIndex, int endIndex)", "add": "public String substring(int begin)", "context": " public String substring(int beginIndex, int endIndex) { if (beginIndex < 0 || endIndex > count || beginIndex > endIndex) throw new StringIndexOutOfBoundsException(); if (beginIndex == 0 && endIndex == count) return this; int len = endIndex - beginIndex; // Package constructor avoids an array copy. return new String(value, beginIndex + offset, len, (len << 2) >= value.length); }"}
|
{"rem": "if (beginIndex < 0 || endIndex > count || beginIndex > endIndex) throw new StringIndexOutOfBoundsException(); if (beginIndex == 0 && endIndex == count) return this; int len = endIndex - beginIndex; return new String(value, beginIndex + offset, len, (len << 2) >= value.length);", "add": "return substring(begin, count);", "context": " public String substring(int beginIndex, int endIndex) { if (beginIndex < 0 || endIndex > count || beginIndex > endIndex) throw new StringIndexOutOfBoundsException(); if (beginIndex == 0 && endIndex == count) return this; int len = endIndex - beginIndex; // Package constructor avoids an array copy. return new String(value, beginIndex + offset, len, (len << 2) >= value.length); }"}
|
{"rem": "public Object next() {", "add": "public FSEntry next() {", "context": "\t\tpublic Object next() {\t\t\tString fs = (String)fileSystemsRoots.next();\t\t\treturn new virtualFSEntry(fs);\t\t}"}
|
{"rem": "return getEntry(\"/\" + name);", "add": "for(FSEntryIterator it = iterator() ; it.hasNext() ; ) { FSEntry entry = it.next(); if(entry.getName().equals(name)) return entry; } throw new IOException(\"Entry not found: \"+name);", "context": "\t\tpublic FSEntry getEntry(String name) throws IOException {\t\t\treturn getEntry(\"/\" + name);\t\t}"}
|
{"rem": "public Iterator iterator() {", "add": "public FSEntryIterator iterator() {", "context": "\t\tpublic Iterator iterator() {\t\t\treturn new RootsIterator(fsm.fileSystemRoots().iterator());\t\t}"}
|
{"rem": "for (Iterator i = entry.getDirectory().iterator(); i.hasNext();) {", "add": "for (FSEntryIterator i = entry.getDirectory().iterator(); i.hasNext();) {", "context": "\tpublic String[] list(File directory, FilenameFilter filter) throws IOException {\t\tfinal FSEntry entry = getEntry(directory);\t\tif (entry == null) {\t\t\tthrow new FileNotFoundException(directory.getAbsolutePath());\t\t}\t\tif (!entry.isDirectory()) {\t\t\tthrow new IOException(\"Cannot list on non-directories \" + directory);\t\t}\t\tfinal ArrayList list = new ArrayList();\t\tfor (Iterator i = entry.getDirectory().iterator(); i.hasNext();) {\t\t\tfinal FSEntry child = (FSEntry)i.next();\t\t\tfinal String name = child.getName();\t\t\tif ((filter == null) || (filter.accept(directory, name))) {\t\t\t\tlist.add(name);\t\t\t}\t\t}\t\treturn (String[])list.toArray(new String[list.size()]);\t}"}
|
{"rem": "public synchronized FileSystem getFileSystem(String rootName) { return (FileSystem)filesystems.get(rootName);", "add": "public synchronized FileSystem getFileSystem(Device device) { return (FileSystem)filesystems.get(getMountPoint(device));", "context": "\tpublic synchronized FileSystem getFileSystem(String rootName) {\t\treturn (FileSystem)filesystems.get(rootName);\t}"}
|
{"rem": "", "add": "attribHash.put(\"lessThanValue\", new XMLAttribute(null, Constants.STRING_OR_NUMBER_TYPE)); attribHash.put(\"lessThanOrEqualValue\", new XMLAttribute(null, Constants.STRING_OR_NUMBER_TYPE)); attribHash.put(\"greaterThanValue\", new XMLAttribute(null, Constants.STRING_OR_NUMBER_TYPE)); attribHash.put(\"greaterThanOrEqualValue\", new XMLAttribute(null, Constants.STRING_OR_NUMBER_TYPE)); attribHash.put(\"infiniteValue\", new XMLAttribute(null, Constants.STRING_OR_NUMBER_TYPE)); attribHash.put(\"infiniteNegativeValue\", new XMLAttribute(null, Constants.STRING_OR_NUMBER_TYPE)); attribHash.put(\"noDataValue\", new XMLAttribute(null, Constants.STRING_OR_NUMBER_TYPE));", "context": " private void init() { classXDFNodeName = \"dataFormat\"; // order matters! these are in *reverse* order of their // occurence in the XDF DTD //the order of the attributes that all sub-classses should have attribOrder.add(0,\"noDataValue\"); attribOrder.add(0,\"infiniteNegativeValue\"); attribOrder.add(0,\"infiniteValue\"); attribOrder.add(0,\"greaterThanOrEqualValue\"); attribOrder.add(0,\"greaterThanValue\"); attribOrder.add(0,\"lessThanOrEqualValue\"); attribOrder.add(0,\"lessThanValue\"); }"}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4314", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4314/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4314/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4314/events", "html_url": "https://github.com/huggingface/datasets/pull/4314", "id": 1232326726, "node_id": "PR_kwDODunzps43oqXD", "number": 4314, "title": "Catch pull error when mirroring", "user": {"login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652261915000, "updated_at": 1652262658000, "closed_at": null, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4314", "html_url": "https://github.com/huggingface/datasets/pull/4314", "diff_url": "https://github.com/huggingface/datasets/pull/4314.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4314.patch", "merged_at": null}, "body": "Catch pull errors when mirroring so that the script continues to update the other datasets.\r\n\r\nThe error will still be printed at the end of the job. In this case the job also fails, and asks to manually update the datasets that failed.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4314/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4314/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4313", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4313/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4313/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4313/events", "html_url": "https://github.com/huggingface/datasets/pull/4313", "id": 1231764100, "node_id": "PR_kwDODunzps43m4qB", "number": 4313, "title": "Add API code examples for Builder classes", "user": {"login": "stevhliu", "id": 59462357, "node_id": "MDQ6VXNlcjU5NDYyMzU3", "avatar_url": "https://avatars.githubusercontent.com/u/59462357?v=4", "gravatar_id": "", "url": "https://api.github.com/users/stevhliu", "html_url": "https://github.com/stevhliu", "followers_url": "https://api.github.com/users/stevhliu/followers", "following_url": "https://api.github.com/users/stevhliu/following{/other_user}", "gists_url": "https://api.github.com/users/stevhliu/gists{/gist_id}", "starred_url": "https://api.github.com/users/stevhliu/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/stevhliu/subscriptions", "organizations_url": "https://api.github.com/users/stevhliu/orgs", "repos_url": "https://api.github.com/users/stevhliu/repos", "events_url": "https://api.github.com/users/stevhliu/events{/privacy}", "received_events_url": "https://api.github.com/users/stevhliu/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 1935892861, "node_id": "MDU6TGFiZWwxOTM1ODkyODYx", "url": "https://api.github.com/repos/huggingface/datasets/labels/documentation", "name": "documentation", "color": "0075ca", "default": true, "description": "Improvements or additions to documentation"}], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652221352000, "updated_at": 1652258535000, "closed_at": null, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4313", "html_url": "https://github.com/huggingface/datasets/pull/4313", "diff_url": "https://github.com/huggingface/datasets/pull/4313.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4313.patch", "merged_at": null}, "body": "This PR adds API code examples for the Builder classes.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4313/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4313/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4312", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4312/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4312/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4312/events", "html_url": "https://github.com/huggingface/datasets/pull/4312", "id": 1231662775, "node_id": "PR_kwDODunzps43mlug", "number": 4312, "title": "added TR-News dataset", "user": {"login": "batubayk", "id": 25901065, "node_id": "MDQ6VXNlcjI1OTAxMDY1", "avatar_url": "https://avatars.githubusercontent.com/u/25901065?v=4", "gravatar_id": "", "url": "https://api.github.com/users/batubayk", "html_url": "https://github.com/batubayk", "followers_url": "https://api.github.com/users/batubayk/followers", "following_url": "https://api.github.com/users/batubayk/following{/other_user}", "gists_url": "https://api.github.com/users/batubayk/gists{/gist_id}", "starred_url": "https://api.github.com/users/batubayk/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/batubayk/subscriptions", "organizations_url": "https://api.github.com/users/batubayk/orgs", "repos_url": "https://api.github.com/users/batubayk/repos", "events_url": "https://api.github.com/users/batubayk/events{/privacy}", "received_events_url": "https://api.github.com/users/batubayk/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652214780000, "updated_at": 1652214780000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4312", "html_url": "https://github.com/huggingface/datasets/pull/4312", "diff_url": "https://github.com/huggingface/datasets/pull/4312.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4312.patch", "merged_at": null}, "body": null, "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4312/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4312/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4311", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/events", "html_url": "https://github.com/huggingface/datasets/pull/4311", "id": 1231369438, "node_id": "PR_kwDODunzps43ln8-", "number": 4311, "title": "[Imagefolder] Docs + Don't infer labels from file names when there are metadata + Error messages when metadata and images aren't linked correctly", "user": {"login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "closed", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652197935000, "updated_at": 1652203182000, "closed_at": 1652202707000, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4311", "html_url": "https://github.com/huggingface/datasets/pull/4311", "diff_url": "https://github.com/huggingface/datasets/pull/4311.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4311.patch", "merged_at": 1652202707000}, "body": "I updated the `docs/source/image_process.mdx` documentation and added an example for image captioning and object detection using `ImageFolder`.\r\n\r\nWhile doing so I also improved a few aspects:\r\n- we don't need to infer labels from file names when there are metadata - they can just be in the metadata if necessary\r\n- raise informative error messages when metadata and images aren't linked correctly:\r\n - when an image is missing a metadata file\r\n - when a metadata file is missing an image\r\n\r\nI added some tests for these changes as well\r\n\r\ncc @mariosasko ", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4311/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4311/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4310", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/events", "html_url": "https://github.com/huggingface/datasets/issues/4310", "id": 1231319815, "node_id": "I_kwDODunzps5JZHMH", "number": 4310, "title": "Loading dataset with streaming: '_io.BufferedReader' object has no attribute 'loc'", "user": {"login": "milmin", "id": 72745467, "node_id": "MDQ6VXNlcjcyNzQ1NDY3", "avatar_url": "https://avatars.githubusercontent.com/u/72745467?v=4", "gravatar_id": "", "url": "https://api.github.com/users/milmin", "html_url": "https://github.com/milmin", "followers_url": "https://api.github.com/users/milmin/followers", "following_url": "https://api.github.com/users/milmin/following{/other_user}", "gists_url": "https://api.github.com/users/milmin/gists{/gist_id}", "starred_url": "https://api.github.com/users/milmin/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/milmin/subscriptions", "organizations_url": "https://api.github.com/users/milmin/orgs", "repos_url": "https://api.github.com/users/milmin/repos", "events_url": "https://api.github.com/users/milmin/events{/privacy}", "received_events_url": "https://api.github.com/users/milmin/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working"}], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652195573000, "updated_at": 1652195573000, "closed_at": null, "author_association": "NONE", "active_lock_reason": null, "draft": null, "pull_request": null, "body": "## Describe the bug\r\nLoading a datasets with `load_dataset` and `streaming=True` returns `AttributeError: '_io.BufferedReader' object has no attribute 'loc'`. Notice that loading with `streaming=False` works fine.\r\n\r\nIn the following steps we load parquet files but the same happens with pickle files. The problem seems to come from `fsspec` lib, I put in the environment info also `s3fs` and `fsspec` versions since I'm loading from an s3 bucket.\r\n\r\n## Steps to reproduce the bug\r\n```python\r\nfrom datasets import load_dataset\r\n# path is the path to parquet files\r\ndata_files = {\"train\": path + \"meta_train.parquet.gzip\", \"test\": path + \"meta_test.parquet.gzip\"}\r\ndataset = load_dataset(\"parquet\", data_files=data_files, streaming=True)\r\n```\r\n\r\n## Expected results\r\nA dataset object `datasets.dataset_dict.DatasetDict`\r\n\r\n## Actual results\r\n```\r\nAttributeError Traceback (most recent call last)\r\n<command-562086> in <module>\r\n 11 \r\n 12 data_files = {\"train\": path + \"meta_train.parquet.gzip\", \"test\": path + \"meta_test.parquet.gzip\"}\r\n---> 13 dataset = load_dataset(\"parquet\", data_files=data_files, streaming=True)\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)\r\n 1679 if streaming:\r\n 1680 extend_dataset_builder_for_streaming(builder_instance, use_auth_token=use_auth_token)\r\n-> 1681 return builder_instance.as_streaming_dataset(\r\n 1682 split=split,\r\n 1683 use_auth_token=use_auth_token,\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/builder.py in as_streaming_dataset(self, split, base_path, use_auth_token)\r\n 904 )\r\n 905 self._check_manual_download(dl_manager)\r\n--> 906 splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}\r\n 907 # By default, return all splits\r\n 908 if split is None:\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/packaged_modules/parquet/parquet.py in _split_generators(self, dl_manager)\r\n 30 if not self.config.data_files:\r\n 31 raise ValueError(f\"At least one data file must be specified, but got data_files={self.config.data_files}\")\r\n---> 32 data_files = dl_manager.download_and_extract(self.config.data_files)\r\n 33 if isinstance(data_files, (str, list, tuple)):\r\n 34 files = data_files\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in download_and_extract(self, url_or_urls)\r\n 798 \r\n 799 def download_and_extract(self, url_or_urls):\r\n--> 800 return self.extract(self.download(url_or_urls))\r\n 801 \r\n 802 def iter_archive(self, urlpath_or_buf: Union[str, io.BufferedReader]) -> Iterable[Tuple]:\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in extract(self, path_or_paths)\r\n 776 \r\n 777 def extract(self, path_or_paths):\r\n--> 778 urlpaths = map_nested(self._extract, path_or_paths, map_tuple=True)\r\n 779 return urlpaths\r\n 780 \r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types, disable_tqdm, desc)\r\n 312 num_proc = 1\r\n 313 if num_proc <= 1 or len(iterable) <= num_proc:\r\n--> 314 mapped = [\r\n 315 _single_map_nested((function, obj, types, None, True, None))\r\n 316 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in <listcomp>(.0)\r\n 313 if num_proc <= 1 or len(iterable) <= num_proc:\r\n 314 mapped = [\r\n--> 315 _single_map_nested((function, obj, types, None, True, None))\r\n 316 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)\r\n 317 ]\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in _single_map_nested(args)\r\n 267 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}\r\n 268 else:\r\n--> 269 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]\r\n 270 if isinstance(data_struct, list):\r\n 271 return mapped\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in <listcomp>(.0)\r\n 267 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}\r\n 268 else:\r\n--> 269 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]\r\n 270 if isinstance(data_struct, list):\r\n 271 return mapped\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in _single_map_nested(args)\r\n 249 # Singleton first to spare some computation\r\n 250 if not isinstance(data_struct, dict) and not isinstance(data_struct, types):\r\n--> 251 return function(data_struct)\r\n 252 \r\n 253 # Reduce logging to keep things readable in multiprocessing with tqdm\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _extract(self, urlpath)\r\n 781 def _extract(self, urlpath: str) -> str:\r\n 782 urlpath = str(urlpath)\r\n--> 783 protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)\r\n 784 if protocol is None:\r\n 785 # no extraction\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _get_extraction_protocol(urlpath, use_auth_token)\r\n 371 urlpath, kwargs = urlpath, {}\r\n 372 with fsspec.open(urlpath, **kwargs) as f:\r\n--> 373 return _get_extraction_protocol_with_magic_number(f)\r\n 374 \r\n 375 \r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _get_extraction_protocol_with_magic_number(f)\r\n 335 def _get_extraction_protocol_with_magic_number(f) -> Optional[str]:\r\n 336 \"\"\"read the magic number from a file-like object and return the compression protocol\"\"\"\r\n--> 337 prev_loc = f.loc\r\n 338 magic_number = f.read(MAGIC_NUMBER_MAX_LENGTH)\r\n 339 f.seek(prev_loc)\r\n\r\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/fsspec/implementations/local.py in __getattr__(self, item)\r\n 337 \r\n 338 def __getattr__(self, item):\r\n--> 339 return getattr(self.f, item)\r\n 340 \r\n 341 def __enter__(self):\r\n\r\nAttributeError: '_io.BufferedReader' object has no attribute 'loc'\r\n```\r\n## Environment info\r\n- `datasets` version: 2.1.0\r\n- Platform: Linux-5.4.0-1071-aws-x86_64-with-glibc2.29\r\n- Python version: 3.8.10\r\n- PyArrow version: 8.0.0\r\n- Pandas version: 1.4.2\r\n- `fsspec` version: 2021.08.1\r\n- `s3fs` version: 2021.08.1", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4310/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4310/timeline", "performed_via_github_app": null, "is_pull_request": false}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4309", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/events", "html_url": "https://github.com/huggingface/datasets/pull/4309", "id": 1231232935, "node_id": "PR_kwDODunzps43lKpm", "number": 4309, "title": "[WIP] Add TEDLIUM dataset", "user": {"login": "sanchit-gandhi", "id": 93869735, "node_id": "U_kgDOBZhWpw", "avatar_url": "https://avatars.githubusercontent.com/u/93869735?v=4", "gravatar_id": "", "url": "https://api.github.com/users/sanchit-gandhi", "html_url": "https://github.com/sanchit-gandhi", "followers_url": "https://api.github.com/users/sanchit-gandhi/followers", "following_url": "https://api.github.com/users/sanchit-gandhi/following{/other_user}", "gists_url": "https://api.github.com/users/sanchit-gandhi/gists{/gist_id}", "starred_url": "https://api.github.com/users/sanchit-gandhi/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/sanchit-gandhi/subscriptions", "organizations_url": "https://api.github.com/users/sanchit-gandhi/orgs", "repos_url": "https://api.github.com/users/sanchit-gandhi/repos", "events_url": "https://api.github.com/users/sanchit-gandhi/events{/privacy}", "received_events_url": "https://api.github.com/users/sanchit-gandhi/received_events", "type": "User", "site_admin": false}, "labels": [{"id": 2067376369, "node_id": "MDU6TGFiZWwyMDY3Mzc2MzY5", "url": "https://api.github.com/repos/huggingface/datasets/labels/dataset%20request", "name": "dataset request", "color": "e99695", "default": false, "description": "Requesting to add a new dataset"}, {"id": 2725241052, "node_id": "MDU6TGFiZWwyNzI1MjQxMDUy", "url": "https://api.github.com/repos/huggingface/datasets/labels/speech", "name": "speech", "color": "d93f0b", "default": false, "description": ""}], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652191967000, "updated_at": 1652266130000, "closed_at": null, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4309", "html_url": "https://github.com/huggingface/datasets/pull/4309", "diff_url": "https://github.com/huggingface/datasets/pull/4309.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4309.patch", "merged_at": null}, "body": "Adds the TED-LIUM dataset https://www.tensorflow.org/datasets/catalog/tedlium#tedliumrelease3 \r\n\r\nTODO:\r\n\r\n- [x] Port `tedium.py` from TF datasets using `convert_dataset.sh` script\r\n- [ ] Make `load_dataset` work\r\n- [ ] Run `datasets-cli` command to generate `dataset_infos.json`\r\n- [ ] Create dummy data for continuous testing\r\n- [ ] Dummy data tests\r\n- [ ] Real data tests\r\n- [ ] Create the metadata JSON\r\n- [ ] Close PR and add directly to the Hub under LIUM org", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4309/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4309/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4308", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/events", "html_url": "https://github.com/huggingface/datasets/pull/4308", "id": 1231217783, "node_id": "PR_kwDODunzps43lHdP", "number": 4308, "title": "Remove unused multiprocessing args from test CLI", "user": {"login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652191335000, "updated_at": 1652258731000, "closed_at": null, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4308", "html_url": "https://github.com/huggingface/datasets/pull/4308", "diff_url": "https://github.com/huggingface/datasets/pull/4308.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4308.patch", "merged_at": null}, "body": "Multiprocessing is not used in the test CLI.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4308/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4308/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4307", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/events", "html_url": "https://github.com/huggingface/datasets/pull/4307", "id": 1231175639, "node_id": "PR_kwDODunzps43k-Wo", "number": 4307, "title": "Add packaged builder configs to the documentation", "user": {"login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "closed", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652189659000, "updated_at": 1652191430000, "closed_at": 1652190954000, "author_association": "MEMBER", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4307", "html_url": "https://github.com/huggingface/datasets/pull/4307", "diff_url": "https://github.com/huggingface/datasets/pull/4307.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4307.patch", "merged_at": 1652190954000}, "body": "Add the packaged builders configurations to the docs reference is useful to show the list of all parameters one can use when loading data in many formats: CSV, JSON, etc.", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4307/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4307/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"url": "https://api.github.com/repos/huggingface/datasets/issues/4305", "repository_url": "https://api.github.com/repos/huggingface/datasets", "labels_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/labels{/name}", "comments_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/comments", "events_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/events", "html_url": "https://github.com/huggingface/datasets/pull/4305", "id": 1231099934, "node_id": "PR_kwDODunzps43kt4P", "number": 4305, "title": "Fixes FrugalScore", "user": {"login": "moussaKam", "id": 28675016, "node_id": "MDQ6VXNlcjI4Njc1MDE2", "avatar_url": "https://avatars.githubusercontent.com/u/28675016?v=4", "gravatar_id": "", "url": "https://api.github.com/users/moussaKam", "html_url": "https://github.com/moussaKam", "followers_url": "https://api.github.com/users/moussaKam/followers", "following_url": "https://api.github.com/users/moussaKam/following{/other_user}", "gists_url": "https://api.github.com/users/moussaKam/gists{/gist_id}", "starred_url": "https://api.github.com/users/moussaKam/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/moussaKam/subscriptions", "organizations_url": "https://api.github.com/users/moussaKam/orgs", "repos_url": "https://api.github.com/users/moussaKam/repos", "events_url": "https://api.github.com/users/moussaKam/events{/privacy}", "received_events_url": "https://api.github.com/users/moussaKam/received_events", "type": "User", "site_admin": false}, "labels": [], "state": "open", "locked": false, "assignee": null, "assignees": [], "milestone": null, "comments": ["Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."], "created_at": 1652186646000, "updated_at": 1652263399000, "closed_at": null, "author_association": "CONTRIBUTOR", "active_lock_reason": null, "draft": false, "pull_request": {"url": "https://api.github.com/repos/huggingface/datasets/pulls/4305", "html_url": "https://github.com/huggingface/datasets/pull/4305", "diff_url": "https://github.com/huggingface/datasets/pull/4305.diff", "patch_url": "https://github.com/huggingface/datasets/pull/4305.patch", "merged_at": null}, "body": "There are two minor modifications in this PR:\r\n1) `predictions` and `references` are swapped. Basically Frugalscore is commutative, however some tiny differences can occur if we swap the references and the predictions. I decided to swap them just to obtain the exact results as reported in the paper.\r\n2) I switched to dynamic padding that was was used in the training, forcing the padding to `max_length` introduces errors for some reason that I ignore.\r\n\r\n@lhoestq ", "reactions": {"url": "https://api.github.com/repos/huggingface/datasets/issues/4305/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}, "timeline_url": "https://api.github.com/repos/huggingface/datasets/issues/4305/timeline", "performed_via_github_app": null, "is_pull_request": true}
|
{"review": "plot : two teen couples go to a church party , drink and then drive .\nthey get into an accident .\none of the guys dies , but his girlfriend continues to see him in her life , and has nightmares .\nwhat 's the deal ?\nwatch the movie and \" sorta \" find out . . .\ncritique : a mind - fuck movie for the teen generation that touches on a very cool idea , but presents it in a very bad package .\nwhich is what makes this review an even harder one to write , since i generally applaud films which attempt to break the mold , mess with your head and such ( lost highway & memento ) , but there are good and bad ways of making all types of films , and these folks just did n't snag this one correctly\n.\nthey seem to have taken this pretty neat concept , but executed it terribly .\nso what are the problems with the movie ?\nwell , its main problem is that it 's simply too jumbled\n.\nit starts off \" normal \" but then downshifts into this \" fantasy \" world in which you , as an audience member ,\nhave no idea what 's going on\n.\nthere are dreams , there are characters coming back from the dead , there are others who look like the dead , there are strange apparitions , there are disappearances , there are a looooot of chase scenes , there are tons of weird things that happen , and most of it is simply not explained .\nnow i personally do n't mind trying to unravel a film every now and then , but when all it does is give me the same clue over and over again , i get kind of fed up after a while , which is this film 's biggest problem .\nit 's obviously got this big secret to hide , but it seems to want to hide it completely until its final five minutes .\nand do they make things entertaining , thrilling or even engaging , in the meantime ?\nnot really .\nthe sad part is that the arrow and i both dig on flicks like this , so we actually figured most of it out by the half - way point , so all of the strangeness after that did start to make a little bit of sense , but it still did n't the make the film all that more entertaining .\ni guess the bottom line with movies like this is that you should always make sure that the audience is \" into it \" even before they are given the secret password to enter your world of understanding .\ni mean , showing melissa sagemiller running away from visions for about 20 minutes throughout the movie is just plain lazy ! !\nokay , we get it .\n. .\nthere are people chasing her and we do n't know who they are .\ndo we really need to see it over and over again ?\nhow about giving us different scenes offering further insight into all of the strangeness going down in the movie ?\napparently , the studio took this film away from its director and chopped it up themselves , and it shows .\nthere might 've been a pretty decent teen mind - fuck movie in here somewhere , but i guess \" the suits \" decided that turning it into a music video with little edge , would make more sense .\nthe actors are pretty good for the most part , although wes bentley just seemed to be playing the exact same character that he did in american beauty , only in a new neighborhood .\nbut my biggest kudos go out to sagemiller , who holds her own throughout the entire film , and actually has you feeling her character 's unraveling .\noverall , the film does n't stick\nbecause it does n't entertain , it 's confusing , it rarely excites and\nit feels pretty redundant for most of its runtime , despite a pretty cool ending and explanation to all of the craziness that came before it .\noh ,\nand by the way , this is not a horror or teen slasher flick . . .\nit 's just packaged to look that way because someone is apparently assuming that the genre is still hot with the kids .\nit also wrapped production two years ago and has been sitting on the shelves ever since .\nwhatever . .\n. skip it !\nwhere 's joblo coming from ?\na nightmare of elm street 3 ( 7/10 ) - blair witch 2 ( 7/10 ) - the crow ( 9/10 ) - the crow : salvation ( 4/10 )\n- lost highway ( 10/10 ) - memento ( 10/10 ) - the others ( 9/10 ) - stir of echoes ( 8/10 )", "label": 0, "evidences": ["mind - fuck movie", "the sad part is", "downshifts into this \" fantasy \" world", "i get kind of fed up after a while", "pretty redundant", "it 's simply too jumbled", "have no idea what 's going on", "just did n't snag this one correctly", "do we really need to see it over and over again ?", "a very bad package", "the film does n't stick", "it does n't entertain , it 's confusing , it rarely excites", "what 's the deal ?", "executed it terribly", "not really", "skip it !"]}
|
{"review": "the happy bastard 's quick movie review damn\nthat y2k bug .\nit 's got a head start in this movie starring jamie lee curtis and another baldwin brother ( william this time ) in a story regarding a crew of a tugboat that comes across a deserted russian tech ship that has a strangeness to it when they kick the power back on .\nlittle do they know the power within . . .\ngoing for the gore and bringing on a few action sequences here and there , virus\nstill feels very empty , like a movie going for all flash and no substance .\nwe do n't know why the crew was really out in the middle of nowhere , we do n't know the origin of what took over the ship ( just that a big pink flashy thing hit the mir ) , and , of course , we do n't know why donald sutherland is stumbling around drunkenly throughout .\nhere , it 's just\n\" hey , let 's chase these people around with some robots \" .\nthe acting is below average , even from the likes of curtis .\nyou 're more likely to get a kick out of her work in halloween h20 .\nsutherland is wasted and baldwin , well , he 's acting like a baldwin , of course .\nthe real star here are stan winston 's robot design , some schnazzy cgi , and the occasional good gore shot , like picking into someone 's brain .\nso , if robots and body parts really turn you on , here 's your movie .\notherwise , it 's pretty much a sunken ship of a movie .", "label": 0, "evidences": ["it 's pretty much a sunken ship", "sutherland is wasted", "still feels very empty", "the acting is below average"]}
|
{"review": "it is movies like these that make a jaded movie viewer thankful for the invention of the timex indiglo watch .\nbased on the late 1960 's television show by the same name , the mod squad tells the tale of three reformed criminals under the employ of the police to go undercover .\nhowever , things go wrong as evidence gets stolen and they are immediately under suspicion .\nof course , the ads make it seem like so much more .\nquick cuts , cool music , claire dane 's nice hair and cute outfits , car chases , stuff blowing up , and the like . sounds like a cool movie ,\ndoes it not ?\nafter the first fifteen minutes , it quickly becomes apparent that it is not .\nthe mod squad is certainly a slick looking production , complete with nice hair and costumes , but that simply is n't enough .\nthe film is best described as a cross between an hour - long cop show and a music video , both stretched out into the span of an hour and a half . and\nwith it comes every single clich ?\n.\nit does n't really matter that the film is based on a television show , as most of the plot elements have been recycled from everything we 've already seen .\nthe characters and acting is nothing spectacular , sometimes even bordering on wooden .\nclaire danes and omar epps deliver their lines as if they are bored , which really transfers onto the audience .\nthe only one to escape relatively unscathed is giovanni ribisi , who plays the resident crazy man , ultimately being the only thing worth watching .\nunfortunately , even he 's not enough to save this convoluted mess , as\nall the characters do n't do much apart from occupying screen time .\nwith the young cast , cool clothes , nice hair , and hip soundtrack , it appears that the film is geared towards the teenage mindset .\ndespite an american ' r ' rating ( which the content does not justify ) , the film is way too juvenile for the older mindset .\ninformation on the characters is literally spoon - fed to the audience ( would it be that hard to show us instead of telling us ? ) , dialogue is poorly written , and the plot is extremely predictable .\nthe way the film progresses , you likely wo n't even care if the heroes are in any jeopardy , because you 'll know they are n't . basing the show on a 1960 's television show that nobody remembers is of questionable wisdom , especially when one considers the target audience and the fact that the number of memorable films based on television shows can be counted on one hand ( even one that 's missing a finger or two ) .\nthe number of times that i checked my watch ( six ) is a clear indication that this film is not one of them .\nit is clear that the film is nothing more than an attempt to cash in on the teenage spending dollar , judging from the rash of really awful teen - flicks that we 've been seeing as of late . avoid this film at all costs .", "label": 0, "evidences": ["the characters and acting is nothing spectacular", "as if they are bored", "that simply is n't enough", "bordering on wooden", "the plot is extremely predictable", "with it comes every single clich ?", "all the characters do n't do much apart from occupying screen time", "avoid this film at all costs", "dialogue is poorly written", "nothing more than an attempt to cash in on the teenage spending dollar", "the film is way too juvenile", "even he 's not enough to save this convoluted mess", "it quickly becomes apparent that it is not"]}
|
{"review": "\" quest for camelot \" is warner bros . '\nfirst feature - length , fully - animated attempt to steal clout from disney 's cartoon empire , but the mouse has no reason to be worried .\nthe only other recent challenger to their throne was last fall 's promising , if flawed , 20th century fox production \" anastasia , \" but disney 's \" hercules , \" with its lively cast and colorful palate , had her beat hands - down when it came time to crown 1997 's best piece of animation .\nthis year , it 's no contest , as \" quest for camelot \" is pretty much dead on arrival .\neven the magic kingdom at its most mediocre\n-- that 'd be \" pocahontas \" for those of you keeping score -- is n't nearly as dull as this .\nthe story revolves around the adventures of free - spirited kayley ( voiced by jessalyn gilsig ) , the early - teen daughter of a belated knight from king arthur 's round table .\nkayley 's only dream is to follow in her father 's footsteps , and she gets her chance when evil warlord ruber ( gary oldman ) , an ex - round table member - gone - bad , steals arthur 's magical sword excalibur and accidentally loses it in a dangerous , booby - trapped forest .\nwith the help of hunky , blind timberland - dweller garrett ( carey elwes ) and a two - headed dragon ( eric idle and don rickles ) that 's always arguing with itself , kayley just might be able to break the medieval sexist mold and prove her worth as a fighter on arthur 's side .\n\" quest for camelot \" is missing pure showmanship , an essential element if it 's ever expected to climb to the high ranks of disney .\nthere 's nothing here\nthat differentiates \" quest \" from something you 'd see on any given saturday morning cartoon -- subpar animation , instantly forgettable songs , poorly - integrated computerized footage .\n( compare kayley and garrett 's run -\nin with the angry ogre\nto herc 's battle with the hydra .\ni rest my case . )\neven the characters stink -- none of them are remotely interesting , so much that the film becomes a race to see which one can out - bland the others .\nin the end , it 's a tie -- they all win .\nthat dragon 's comedy shtick is awfully cloying , but at least it shows signs of a pulse .\nat least fans of the early-'90s tgif television line - up will be thrilled to find jaleel \" urkel \" white and bronson \" balki \" pinchot sharing the same footage .\na few scenes are nicely realized ( though i 'm at a loss to recall enough to be specific ) , and the actors providing the voice talent are enthusiastic ( though most are paired up with singers who do n't sound a thing like them for their big musical moments -- jane seymour and celine dion ? ? ? ) .\nbut one must strain through too much of this mess to find the good . aside from the fact that children will probably be as bored watching this as adults , \" quest for camelot\n\" 's most grievous error is its complete lack of personality .\nand personality , we learn from this mess , goes a very long way .", "label": 0, "evidences": ["dead on arrival", "the characters stink", "subpar animation , instantly forgettable songs , poorly - integrated computerized footage", "complete lack of personality", "missing pure showmanship", "will probably be as bored watching", "this mess", "one must strain through too much of this mess", "is n't nearly as dull as this"]}
|
{"review": "synopsis : a mentally unstable man undergoing psychotherapy saves a boy from a potentially fatal accident and then falls in love with the boy 's mother , a fledgling restauranteur .\nunsuccessfully attempting to gain the woman 's favor , he takes pictures of her and kills a number of people in his way .\ncomments : stalked is yet another in a seemingly endless string of spurned - psychos - getting - their - revenge type movies which are a stable category in the 1990s film industry , both theatrical and direct - to - video .\ntheir proliferation may be due in part to the fact that they 're typically inexpensive to produce ( no special effects , no big name stars ) and serve as vehicles to flash nudity ( allowing them to frequent late - night cable television ) .\nstalked wavers slightly from the norm in one respect : the psycho never actually has an affair ; on the contrary , he 's rejected rather quickly ( the psycho typically is an ex - lover , ex - wife , or ex - husband ) .\nother than that , stalked is just another redundant entry doomed to collect dust on video shelves and viewed after midnight on cable .\nstalked does not provide much suspense , though that is what it sets out to do .\ninterspersed throughout the opening credits , for instance , a serious - sounding narrator spouts statistics about stalkers and ponders what may cause a man to stalk ( it 's implicitly implied that all stalkers are men ) while pictures of a boy are shown on the screen .\nafter these credits , a snapshot of actor jay underwood appears .\nthe narrator states that \" this is the story of daryl gleason \" and tells the audience that he is the stalker .\nof course , really , this is the story of restauranteur brooke daniels .\nif the movie was meant to be about daryl , then it should have been called stalker not stalked .\nokay .\nso we know who the stalker is even before the movie starts ; no guesswork required .\nstalked proceeds , then , as it begins : obvious , obvious , obvious .\nthe opening sequence , contrived quite a bit , brings daryl and brooke ( the victim ) together .\ndaryl obsesses over brooke , follows her around , and tries to woo her .\nultimately rejected by her , his plans become more and more desperate and elaborate .\nthese plans include the all - time , psycho - in - love , cliche : the murdered pet .\nfor some reason , this genre 's films require a dead pet to be found by the victim stalked .\nstalked is no exception ( it 's a cat this time -- found in the shower ) .\nevents like these lead to the inevitable showdown between stalker and stalked , where only one survives ( guess who it invariably always is and you 'll guess the conclusion to this turkey ) .\nstalked 's cast is uniformly adequate : not anything to write home about but also not all that bad either .\njay underwood , as the stalker , turns toward melodrama a bit too much .\nhe overdoes it , in other words , but he still manages to be creepy enough to pass as the type of stalker the story demands .\nmaryam d'abo , about the only actor close to being a star here\n( she played the bond chick in the living daylights ) , is equally adequate as the \" stalked \" of the title , even though she seems too ditzy at times to be a strong , independent business - owner .\nbrooke ( d'abo ) needs to be ditzy , however , for the plot to proceed .\ntoward the end , for example , brooke has her suspicions about daryl .\nto ensure he wo n't use it as another excuse to see her , brooke decides to return a toolbox he had left at her place to his house .\ndoes she just leave the toolbox at the door when no one answers ?\nof course not .\nshe tries the door , opens it , and wanders around the house .\nwhen daryl returns , he enters the house , of course , so our heroine is in danger .\nsomehow , even though her car is parked at the front of the house , right by the front door , daryl is oblivious to her presence inside .\nthe whole episode places an incredible strain on the audience 's suspension of disbelief and questions the validity of either character 's intelligence .\nstalked receives two stars because , even though\nit is highly derivative and somewhat boring\n, it is not so bad that it can not be watched .\nrated r mostly for several murder scenes and brief nudity in a strip bar , it is not as offensive as many other thrillers in this genre are .\nif you 're in the mood for a good suspense film , though , stake out something else .", "label": 0, "evidences": ["it is highly derivative and somewhat boring", "does not provide much suspense", "just another redundant entry doomed to collect dust on video shelves and viewed after midnight on cable", "obvious , obvious , obvious", "questions the validity of either character 's intelligence", "stake out something else", "incredible strain on the audience 's suspension of disbelief", "cliche"]}
|
{"review": "capsule : in 2176 on the planet mars police taking into custody an accused murderer face the title menace .\nthere is a lot of fighting and not a whole lot of story otherwise .\njohn carpenter reprises so many ideas from his previous films , especially assault on precinct 13 , that the new film comes off as his homage to himself .\n, 0 ( -4 to +4 ) .\njohn carpenter apparently believes that action scenes in which people fight something horrible are the same as horror scenes .\nfor a writer and director of horror films , supposedly an expert on horror ,\nit is a very bad mistake to make .\nghosts of mars is called a horror movie , but it is more just a drawn out fight between humans and a surprisingly low - powered alien menace .\nin addition if anybody but john carpenter had made ghosts of mars , carpenter would have grounds to sue .\nthis film is just chock full of pieces taken from assault on precinct 13 , the thing , and prince of darkness .\nit is , in fact , surprising that carpenter managed to fit so many pieces of his previous work into this film in such an admittedly novel way .\nbut that still does not make for a really good science fiction experience .\nghosts of mars takes place in the year 2176 .\nmars has been mostly terraformed so that humans can walk on the surface without breathing gear ( which is good for the film 's budget ) .\nit is never mentioned , but the gravity on mars has been increased somehow to earth - normal , again making it easier to film .\nsociety has changed a bit by that time , but it has advanced surprisingly little .\napparently the culture has changed so that women are much more in positions of control .\nand from carpenter 's view , women have really made a mess of things .\nsociety has stagnated under female control so that beyond some minor technological advances society has changed less in 175 years than we might expect it to change in ten .\nthe basic plot of ghosts of mars has much in common with that of assault on precinct 13 except that precinct 9 ( yes , precinct 9 ) has been replaced by a somewhat tacky looking rundown martian mining colony .\ninstead of having the criminal \" napolean \" wilson , this film has the criminal \" desolation \" williams .\ninstead of facing hoodlums with automatic weapons the police face , well , ghosts of mars .\nbecause the ghosts are somewhat alien in nature they should behave in some alien manner , but they essentially behave as human savages , in another lapse of imagination .\nthe story is told in flashback , flashback within flashback , and flashback within flashback within flashback .\nghosts of mars takes place entirely at night and is filmed almost entirely in tones of red , yellow , and black .\ncarpenter manages to give us a powerful opening scene , showing a mining train rushing through the martian night to the sound of music with a heavy beat .\nsadly what follows is not really up to the buildup .\nthe terror he creates looks a little too much like fugitive wannabes from the rock band kiss .\nhis idea of building suspense is having a bunch of sudden jump scenes that sucker the viewer into thinking something scary is happening and then prove to be just something boring .\nthese are standard haunted house film shock effects that require no great talent to give the audience .\nsomewhat newer but also unimpressive\nare the cgi digital decapitations in some of the fights .\nwithin a short stretch of time we have seen the release of mission to mars , red planet , and ghosts of mars .\nafter mission to mars was panned by too many reviewers it looks better and better and better as time goes by .\ni rate ghosts of mars a 4 on the 0 to 10 scale and a 0 on the -4 to +4 scale .\nfollowing the movie i showed my wife , who liked ghosts of mars moderately more than i did , carpenter 's classic assault on precinct 13 .\nher comment is that it was seeing the same film twice .", "label": 0, "evidences": ["sadly what follows is not really up to the buildup", "these are standard haunted house film shock effects", "it is a very bad mistake to make", "tacky looking rundown martian mining colony", "that still does not make for a really good science fiction experience", "also unimpressive"]}
|
{"review": "so ask yourself what \" 8 mm \" ( \" eight millimeter \" ) is really all about .\nis it about a wholesome surveillance man who loses sight of his values after becoming enmeshed in the seedy , sleazy underworld of hardcore pornography ?\nis it about the business itself ,\nhow , bubbling just beneath the surface of big - town americana , there 's a sordid world of sick and depraved people who wo n't necessarily stop short of murder in order to satisfy their sick and twisted desires ?\nor is it about those who can , those who are in a position to influence the making of the kinds of films sick and demented people want to see ?\ni 'm not talking about snuff films , supposed \" documentaries \" of victims being brutalized and killed on camera .\ni 'm talking about films like \" 8 mm \" and its director , joel schumacher .\nwith a recent run of big budget movies to his credit-- \" batman & robin , \" \" a time to kill , \" \" batman forever , \" \" the client\n\" --schumacher certainly has that kind of influence .\nis \" 8 mm \" something you really want to see ? probably not .\nthe first two - thirds of \" 8 mm \" unwind as a fairly conventional missing persons drama , albeit with a particularly unsavory core .\nthen , as it 's been threatening all along , the film explodes into violence .\nand just when you think it 's finally over , schumacher tags on a ridiculous self - righteous finale that drags the whole unpleasant experience down even further . trust me .\nthere are better ways to waste two hours of your life .\nnicolas ' \" snake eyes \" ' cage plays private investigator tom welles who is hired by a wealthy philadelphia widow to determine whether a reel of film found in her late husband 's safe documents a young girl 's murder .\nwelles goes about his assignment rather matter - of - factly , and the pieces of the puzzle fall into place rather neatly , almost as if you do n't need any specialized skills or training to do this .\nwelles certainly makes it look easy .\nand cops , obviously , never look in toilet tanks for clues .\nthe deeper welles digs into his investigation the more obsessed he becomes , like george c .\nscott in paul schrader 's \" hardcore .\n\"\noccasionally , a little flickering sound whirs in his head like sprockets winding through a film projector , reminding him of his unpleasant task .\nthere are hints that this is taking its toll on his lovely wife , played by catherine keener , who is frustrated by her husband spending all of his time in cleveland rather than in their ugly split - level home in harrisburg , pa .\n\"\n8 mm \" does n't condemn or condone its subject matter , it just exploits it .\nthe irony , of course , is that schumacher and \" seven \" scribe andrew kevin walker 's vision of life in the snuff lane is limited by what they can show in an r - rated , first - run hollywood product .\nso we only see snippets of snuff , and a lot more footage of nicolas cage covering his face in horror .\nlater it 's the turn of joaquin phoenix ( who 's quite good and by far the film 's most interesting character as adult bookstore flunky max california ) to cover his face as the horrid thing is screened over and over again .\nall this to get to the familiar yet offensive \" revelation \" that sexual deviants are not , indeed , monsters but everyday people like you and me .\nneither super nor standard , \" 8 mm \" is shocking only in its banality .", "label": 0, "evidences": ["probably not", "tags on a ridiculous self - righteous finale that drags the whole unpleasant experience down even further", "there are better ways to waste two hours of your life", "shocking only in its banality", "a fairly conventional missing persons drama"]}
|
{"review": "that 's exactly how long the movie felt to me .\nthere were n't even nine laughs in nine months .\nit 's a terrible mess of a movie starring a terrible mess of a man , mr . hugh grant , a huge dork .\nit 's not the whole oral - sex / prostitution thing ( referring to grant , not me ) that bugs me , it 's the fact that grant is annoying .\nnot just adam sandler - annoying , we 're talking jim carrey - annoying .\nsince when do\neye flutters and nervous smiles pass for acting ?\nbut , on the other hand , since when do really bad slapstick ( a fistfight in the delivery room culminating in grant 's head in joan cusack 's lap -- a scene he paid $ 60 to have included in the movie ) and obscene double entendres ( robin williams , the obstetrician , tells grant 's pregnant girlfriend she has \" a big pussy , \" referring of course to the size of the cat hairs on her coat , but nonetheless , grant paid $ 60 to have the exchange included in the movie ) pass for comedy ?\nnine months is a predictable cookie - cutter movie with\nno originality in humor or plot .\nhugh grant plays a successful child psychiatrist .\nwhy a child psychologist ?\nso the scriptwriters could inject the following unfunny exchange :\nkid : my dad 's an asshole .\ngrant ( flutters eyelashes , offers a nervous smile , then responds in his annoying english accent and i - think - i - actually - have- talent attitude ) : could you possibly elaborate on that ?\nkid :\nmy dad 's a _ huge _ asshole .\nmore like a hugh asshole , but that 's beside the point , which is : nine months includes too many needlessly stupid jokes that get laughs from the ten year olds in the audience while everyone else shakes his or her head in disbelief .\nso , anyway , grant finds out his girlfriend is pregnant and does his usual reaction ( fluttered eyelashes , nervous smiles ) .\nthis paves the way for every possible pregnancy / child birth gag in the book , especially since grant 's equally annoying friend 's wife is also pregnant .\nthe annoying friend is played by tom arnold , who provides most of the cacophonous slapstick , none of which is funny , such as a scene where arnold beats up a costumed \" arnie the dinosaur \" ( you draw your own parallels on that one ) in a toy store .\nthe only interesting character in the movie is played by jeff goldblum , who should have hid himself away somewhere after the dreadful hideaway , as an artist with a fear of ( and simultaneous longing for ) commitment .\nnot even robin williams , who plays a russian doctor who has recently decided to switch from veterinary medicine to obstetrics , has much humor .\nhis is a one - joke character--\nthe old foreign - guy - who - mispronounces - english stereotype ( did someone say yakov smirnov ?\nthat 's my favorite vodka , by the way ) , hence the line\n\" now it 's time to take a look at your volvo ,\n\" another nasty but unamusing joke , except this one goes right over the ten year olds ' heads , while the adults simultaneously groan .\nnine months is a complete failure , low on laughs and intelligence and high on loud , unfunny slapstick , failed jokes and other uninspired lunacy .\nhugh grant 's sunset boulevard arrest ( please , no caught - with - his - pants - down jokes ) may bring more people into the theaters , but they certainly wo n't leave with a smile on their faces , not after 90 minutes of grant 's nervous smiles .\neverything in the movie is so forced , so unauthentic that anyone with an i .\nq . over 80 ( sorry , hugh ) will know\nthey wasted their money on an unfulfilled desire .\nbut at least they did n't spend 60 bucks for it .", "label": 0, "evidences": ["nasty but unamusing joke", "is annoying", "they certainly wo n't leave with a smile", "eye flutters and nervous smiles", "no originality in humor or plot", "annoying english accent", "a huge dork", "low on laughs and intelligence and high on loud , unfunny slapstick", "failed jokes and other uninspired lunacy", "the annoying friend", "a predictable cookie - cutter movie", "everything in the movie is so forced , so unauthentic", "none of which is funny", "they wasted their money on an unfulfilled desire", "includes too many needlessly stupid jokes", "is a complete failure"]}
|
{"review": "call it a road trip for the walking wounded .\nstellan skarsg ?\nrd plays such a convincingly zombified drunken loser that it 's difficult to spend nearly two hours of screen time in his smelly , boozed - out presence .\nyet this ever - reliable swedish actor adds depth and significance to the otherwise plodding and forgettable aberdeen ,\na sentimental and painfully mundane european drama .\nplaywright august strindberg built his career on families and relationships paralyzed by secrets , unable to express their longings until the hour is far too late .\nthat 's an accurate reflection of what aberdeen strives for , focusing on the pairing of an alcoholic father , tomas ( skarsg ? rd ) and his alienated , openly hostile yuppie daughter , kaisa ( lena headey , gossip ) .\nthey have n't spoken in years , and would n't even be making the long trip from norway to aberdeen , scotland by automobile if it were n't for kaisa 's mother ( charlotte rampling , under the sand ) rotting away in a hospital bed from cancer .\nin a soap opera twist , mother has only a few days to live .\n( only in the movies , right ? )\ntoo blitzed to even step foot on a plane , tomas hits the open road with kaisa .\nloathing each other all the while , they make periodic stops for tomas to puke on the dashboard or pass out -- whenever he is n't muttering\nwhat a rotten kid she turned out to be .\ndespite his sloshed viewpoint , tomas recognizes that the apple has n't fallen very far from the tree .\nkaisa gets nosebleeds from snorting coke , sabotages her personal relationships through indifference , and is unable to restrain her quick and vindictive temper .\nai n't they a pair ? unable to find true notes of unspoken familial empathy in the one - note and repetitively bitchy dialogue , screenwriters kristin amundsen and hans petter moland fabricate a series of contrivances to propel events forward -- lost money , roving street hooligans looking for drunks to kick around , nosy cops , and flat tires all figure into the schematic and convenient narrative .\nby the time they reach the hospital , it 's time to unveil the secrets from a dark past that are not only simplistic devices that trivialize the father - daughter conflict , they 're also the mainstays of many a bad strindberg wannabe .\nthis revelation exists purely for its own sake .\naberdeen does n't know where else to go .\nweak , unimaginative casting thwarts the pivotal role of kaisa .\nif lena headey were a stronger actress , perhaps aberdeen could have been able to coast on the performances and moody , haunting cinematography ( rendering norway into its own pastoral ghost world -- the reference to a certain superior american indie flick intentional ) .\nheadey 's too busy acting , using her face and furrowed brow to convey every last twitch of insouciance .\nif she were paying any attention to skarsg ?\nrd , maybe she 'd figure out that doing less can reveal so much more .\nit 's worthwhile to compare aberdeen to an earlier film released in 2001 , jonathan nossiter 's captivating signs & wonders .\nit 's not\njust because skarsg ?\nrd and rampling played disturbed parental figures in both films\n( they 're not bound by ceremonial wedlock in aberdeen ) .\nthe differences in the way their characters were presented is significant .\nin aberdeen , rampling is a luminous diva , preening and static in her hospital bed .\ndespite skarsg ?\nrd 's solid performance as tomas , his pathetic drunk is never given much of a chance to emote anything besides catatonic sorrow .\nthere 's genuine ferocity and sexually charged frisson during their understated confrontations in signs & wonders , allowing them to suggest a gray zone of complications that accompany torn romance and years of stifled curiosity .\nnossiter 's film thoroughly explores this neurotic territory in addition to delving into the americanization of greece and the use of mysticism as an illusion to deflect pain .\nif signs & wonders sometimes feels overloaded with ideas , at least it 's willing to stretch beyond what we 've come to expect from traditional drama .\naberdeen is never half so ambitious , content to sleepwalk through the rhythms and timing of other movies .\nwhen did character driven stories stop paying attention to the complexities of real life ?\nthe depressing answer can be found in lawrence kasdan 's trite but occasionally useful grand canyon , where steve martin 's hollywood mogul pronounces , \" all of life 's riddles are answered in the movies !\n\" even foreign films are taking that advice to heart .", "label": 0, "evidences": ["a sentimental and painfully mundane european drama", "weak , unimaginative casting thwarts the pivotal role", "is never half so ambitious", "content to sleepwalk through the rhythms and timing of other movies", "stop paying attention to the complexities"]}
|
{"review": "plot : a young french boy sees his parents killed before his eyes by tim roth , oops . . .\ni mean , an evil man .\nhe vows revenge on that man and is taught the ways of the musketeer by some old dude who used to be one himself ?\nanyway , fourteen years go by and . . .\narrgh , well , you know the rest .\n. .\nswish - swish - zzzzzzz ! critique :\nthis is a pretty bad movie .\nlet 's see , where should i start ?\nokay , first of all ,\nthe story is just plain boring .\nit 's not original , is entirely predictable and lacks energy\n.\nokay , what 's next ?\nacting , you say .\nhmmmm , well , the main actor , justin chambers , is basically an uncharismatic version of chris o'donnell but with less range ( think about that ! ) , and mena suvari , is just plain off .\nnot as bad as thora birch was in dungeons & dragons , but entirely miscast , with bad deliveries , awful sequences and a piss - poor accent\nthat comes and goes .\nnow i 'm not sure if this was ms .\nsuvari 's fault or the director 's , but\ni 've definitely seen her at a much higher level than in this film .\nthe only semi - saving grace actor - wise is tim roth as the irrepressible \" bad guy \" , but once again , it 's not something that we have n't seen before . . .\na thousand times . . .\nby the same guy ! !\ntim , please . . . for the love of god , beg your agent to ask the marketplace for some modern day \" american roles \" for you as a \" nice guy \" in a romantic comedy or something .\nstretch , dude . . .\nstretch ! !\nwe all know that you can do much better than this gunk .\nalright ,\nwhat else was bad in this film ?\noh yeah , the score ! yikes , how 's about taking it down a few notches there , fellas ?\nthis thing blares in your ear whenever it feels the need to accentuate a certain scene , but actually does little more than annoy\n.\ni think it 's important for the man behind the music to recognize that this film is n't a \" real epic \" by any stretch of the imagination .\nit 's a fluffy rehashed cake - walk created by some \" shrewd \" studio heads who decided to take advantage of the whole \" kung - fu \" phenomenon in films , and test it out on an old classic .\ndudes . . .\nyou failed all around !\n( keep reading )\nthe editing is also pretty shoddy in this movie , the dialogue banal and stilted and the plot problems . . .\nplentiful !\n( why does the guy on top of the horse carriage just stand there when his opponent takes forever scampering his way back to the top ?\nwhy do n't they just cut the mouseketeer 's rope at the top of the tower , instead of jumping down on their own chords and fighting him while hanging ?\nwhy does n't anybody look a day older , when the sequence says \" 14 years later \" ?\n( at least . . . change your shirt , man ! )\nkeep in mind that i have never strayed away from championing certain movies that are created simply for the sake of a \" fun time \" , but this flick just did n't cut it for me .\nit was boring for stretches ,\nthe acting was atrocious at times\n( the \" romantic \" scene between suvari and chambers next to the lake reminded me of plays in high school which made you cringe ) , there was little reason to care for anyone and since when were the musketeers fat ?\ni will give the movie this much , and that is that its main reason for being ( its \" raison - d'etre \" , as the french would say ) , its fight sequences , do come through despite the lack of their numbers in the film .\ni was hoping that the movie would be packed with cool stuntwork as promoted in its trailer , but what you see there , are essentially the snippets from the two major ( and cool ) swashbuckling sequences from the film .\nthe first comes right at the beginning of the movie , while the other essentially finishes the film off , hanging from the tower and juggling off ladders .\nthe ladder sequence itself is a definite keeper but unfortunately the rest of the movie is just regurgitated crap .\nand can anyone please tell me how catherine deneuve got her name placed at the top of this film 's credits ?\nhullo ?\nthe film is called the musketeer and stars a dude name justin chambers .\ndeneuve is barely in this movie !\nugh , just another small thing that annoyed me about this trash .\nnow say it together , gang : \" all for one , and one for all . . .\nwe vow to stay away from it all ! !\n\" thank me later .\nwhere 's joblo coming from ?\na knight 's tale ( 7/10 ) - american outlaws ( 5/10 ) - crouching tiger , hidden dragon ( 7/10 ) - the matrix ( 8/10 ) - the replacement killers ( 6/10 )\n- romeo must die ( 3/10 )\n- shanghai noon ( 6/10 )", "label": 0, "evidences": ["it 's not original , is entirely predictable and lacks energy", "unfortunately the rest of the movie is just regurgitated crap", "does little more than annoy", "awful sequences and a piss - poor accent", "blares in your ear", "the editing is also pretty shoddy in this movie , the dialogue banal and stilted and the plot problems", "we vow to stay away from it all ! !", "an uncharismatic version", "it was boring for stretches", "what else was bad in this film ?", "entirely miscast", "the story is just plain boring", "is just plain off", "this is a pretty bad movie", "yikes , how 's about taking it down a few notches there , fellas ?", "you failed all around !", "the acting was atrocious at times", "bad deliveries", "another small thing that annoyed me about this trash"]}
|
{"code": "from django import forms\nfrom django.core.exceptions import ValidationError\nfrom django.core.validators import validate_slug\nfrom django.db import models\nfrom django.utils import simplejson as json\nfrom django.utils.text import capfirst\nfrom django.utils.translation import ugettext_lazy as _\n\nfrom philo.forms.fields import JSONFormField\nfrom philo.utils.registry import RegistryIterator\nfrom philo.validators import TemplateValidator, json_validator\n#from philo.models.fields.entities import *\n\n\nclass TemplateField(models.TextField):\n\t\"\"\"A :class:`TextField` which is validated with a :class:`.TemplateValidator`. ``allow``, ``disallow``, and ``secure`` will be passed into the validator's construction.\"\"\"\n\tdef __init__(self, allow=None, disallow=None, secure=True, *args, **kwargs):\n\t\tsuper(TemplateField, self).__init__(*args, **kwargs)\n\t\tself.validators.append(TemplateValidator(allow, disallow, secure))\n\n\nclass JSONDescriptor(object):\n\tdef __init__(self, field):\n\t\tself.field = field\n\t\n\tdef __get__(self, instance, owner):\n\t\tif instance is None:\n\t\t\traise AttributeError # ?\n\t\t\n\t\tif self.field.name not in instance.__dict__:\n\t\t\tjson_string = getattr(instance, self.field.attname)\n\t\t\tinstance.__dict__[self.field.name] = json.loads(json_string)\n\t\t\n\t\treturn instance.__dict__[self.field.name]\n\t\n\tdef __set__(self, instance, value):\n\t\tinstance.__dict__[self.field.name] = value\n\t\tsetattr(instance, self.field.attname, json.dumps(value))\n\t\n\tdef __delete__(self, instance):\n\t\tdel(instance.__dict__[self.field.name])\n\t\tsetattr(instance, self.field.attname, json.dumps(None))\n\n\nclass JSONField(models.TextField):\n\t\"\"\"A :class:`TextField` which stores its value on the model instance as a python object and stores its value in the database as JSON. Validated with :func:`.json_validator`.\"\"\"\n\tdefault_validators = [json_validator]\n\t\n\tdef get_attname(self):\n\t\treturn \"%s_json\" % self.name\n\t\n\tdef contribute_to_class(self, cls, name):\n\t\tsuper(JSONField, self).contribute_to_class(cls, name)\n\t\tsetattr(cls, name, JSONDescriptor(self))\n\t\tmodels.signals.pre_init.connect(self.fix_init_kwarg, sender=cls)\n\t\n\tdef fix_init_kwarg(self, sender, args, kwargs, **signal_kwargs):\n\t\t# Anything passed in as self.name is assumed to come from a serializer and\n\t\t# will be treated as a json string.\n\t\tif self.name in kwargs:\n\t\t\tvalue = kwargs.pop(self.name)\n\t\t\t\n\t\t\t# Hack to handle the xml serializer's handling of \"null\"\n\t\t\tif value is None:\n\t\t\t\tvalue = 'null'\n\t\t\t\n\t\t\tkwargs[self.attname] = value\n\t\n\tdef formfield(self, *args, **kwargs):\n\t\tkwargs[\"form_class\"] = JSONFormField\n\t\treturn super(JSONField, self).formfield(*args, **kwargs)\n\n\nclass SlugMultipleChoiceField(models.Field):\n\t\"\"\"Stores a selection of multiple items with unique slugs in the form of a comma-separated list. Also knows how to correctly handle :class:`RegistryIterator`\\ s passed in as choices.\"\"\"\n\t__metaclass__ = models.SubfieldBase\n\tdescription = _(\"Comma-separated slug field\")\n\t\n\tdef get_internal_type(self):\n\t\treturn \"TextField\"\n\t\n\tdef to_python(self, value):\n\t\tif not value:\n\t\t\treturn []\n\t\t\n\t\tif isinstance(value, list):\n\t\t\treturn value\n\t\t\n\t\treturn value.split(',')\n\t\n\tdef get_prep_value(self, value):\n\t\treturn ','.join(value)\n\t\n\tdef formfield(self, **kwargs):\n\t\t# This is necessary because django hard-codes TypedChoiceField for things with choices.\n\t\tdefaults = {\n\t\t\t'widget': forms.CheckboxSelectMultiple,\n\t\t\t'choices': self.get_choices(include_blank=False),\n\t\t\t'label': capfirst(self.verbose_name),\n\t\t\t'required': not self.blank,\n\t\t\t'help_text': self.help_text\n\t\t}\n\t\tif self.has_default():\n\t\t\tif callable(self.default):\n\t\t\t\tdefaults['initial'] = self.default\n\t\t\t\tdefaults['show_hidden_initial'] = True\n\t\t\telse:\n\t\t\t\tdefaults['initial'] = self.get_default()\n\t\t\n\t\tfor k in kwargs.keys():\n\t\t\tif k not in ('coerce', 'empty_value', 'choices', 'required',\n\t\t\t\t\t\t 'widget', 'label', 'initial', 'help_text',\n\t\t\t\t\t\t 'error_messages', 'show_hidden_initial'):\n\t\t\t\tdel kwargs[k]\n\t\t\n\t\tdefaults.update(kwargs)\n\t\tform_class = forms.TypedMultipleChoiceField\n\t\treturn form_class(**defaults)\n\t\n\tdef validate(self, value, model_instance):\n\t\tinvalid_values = []\n\t\tfor val in value:\n\t\t\ttry:\n\t\t\t\tvalidate_slug(val)\n\t\t\texcept ValidationError:\n\t\t\t\tinvalid_values.append(val)\n\t\t\n\t\tif invalid_values:\n\t\t\t# should really make a custom message.\n\t\t\traise ValidationError(self.error_messages['invalid_choice'] % invalid_values)\n\t\n\tdef _get_choices(self):\n\t\tif isinstance(self._choices, RegistryIterator):\n\t\t\treturn self._choices.copy()\n\t\telif hasattr(self._choices, 'next'):\n\t\t\tchoices, self._choices = itertools.tee(self._choices)\n\t\t\treturn choices\n\t\telse:\n\t\t\treturn self._choices\n\tchoices = property(_get_choices)\n\n\ntry:\n\tfrom south.modelsinspector import add_introspection_rules\nexcept ImportError:\n\tpass\nelse:\n\tadd_introspection_rules([], [\"^philo\\.models\\.fields\\.SlugMultipleChoiceField\"])\n\tadd_introspection_rules([], [\"^philo\\.models\\.fields\\.TemplateField\"])\n\tadd_introspection_rules([], [\"^philo\\.models\\.fields\\.JSONField\"])", "repo_name": "ithinksw/philo", "path": "philo/models/fields/__init__.py", "language": "Python", "license": "isc", "size": 4971}
|
{"code": "import hashlib\nimport json\nimport logging\nimport os\nimport subprocess\nimport sys\nimport time\nfrom collections import defaultdict\n\nfrom shutil import copy\nfrom shutil import copyfile\nfrom shutil import copystat\nfrom shutil import copytree\nfrom tempfile import mkdtemp\n\nimport boto3\nimport botocore\nimport yaml\nimport sys\n\nfrom .helpers import archive\nfrom .helpers import get_environment_variable_value\nfrom .helpers import LambdaContext\nfrom .helpers import mkdir\nfrom .helpers import read\nfrom .helpers import timestamp\n\n\nARN_PREFIXES = {\n \"cn-north-1\": \"aws-cn\",\n \"cn-northwest-1\": \"aws-cn\",\n \"us-gov-west-1\": \"aws-us-gov\",\n}\n\nlog = logging.getLogger(__name__)\n\n\ndef load_source(module_name, module_path):\n \"\"\"Loads a python module from the path of the corresponding file.\"\"\"\n\n if sys.version_info[0] == 3 and sys.version_info[1] >= 5:\n import importlib.util\n spec = importlib.util.spec_from_file_location(module_name, module_path)\n module = importlib.util.module_from_spec(spec)\n spec.loader.exec_module(module)\n elif sys.version_info[0] == 3 and sys.version_info[1] < 5:\n import importlib.machinery\n loader = importlib.machinery.SourceFileLoader(module_name, module_path)\n module = loader.load_module()\n return module\n\n\ndef cleanup_old_versions(\n src, keep_last_versions, config_file=\"config.yaml\", profile_name=None,\n):\n \"\"\"Deletes old deployed versions of the function in AWS Lambda.\n\n Won't delete $Latest and any aliased version\n\n :param str src:\n The path to your Lambda ready project (folder must contain a valid\n config.yaml and handler module (e.g.: service.py).\n :param int keep_last_versions:\n The number of recent versions to keep and not delete\n \"\"\"\n if keep_last_versions <= 0:\n print(\"Won't delete all versions. Please do this manually\")\n else:\n path_to_config_file = os.path.join(src, config_file)\n cfg = read_cfg(path_to_config_file, profile_name)\n\n profile_name = cfg.get(\"profile\")\n aws_access_key_id = cfg.get(\"aws_access_key_id\")\n aws_secret_access_key = cfg.get(\"aws_secret_access_key\")\n\n client = get_client(\n \"lambda\",\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n cfg.get(\"region\"),\n )\n\n response = client.list_versions_by_function(\n FunctionName=cfg.get(\"function_name\"),\n )\n versions = response.get(\"Versions\")\n if len(response.get(\"Versions\")) < keep_last_versions:\n print(\"Nothing to delete. (Too few versions published)\")\n else:\n version_numbers = [\n elem.get(\"Version\") for elem in versions[1:-keep_last_versions]\n ]\n for version_number in version_numbers:\n try:\n client.delete_function(\n FunctionName=cfg.get(\"function_name\"),\n Qualifier=version_number,\n )\n except botocore.exceptions.ClientError as e:\n print(f\"Skipping Version {version_number}: {e}\")\n\n\ndef deploy(\n src,\n requirements=None,\n local_package=None,\n config_file=\"config.yaml\",\n profile_name=None,\n preserve_vpc=False,\n):\n \"\"\"Deploys a new function to AWS Lambda.\n\n :param str src:\n The path to your Lambda ready project (folder must contain a valid\n config.yaml and handler module (e.g.: service.py).\n :param str local_package:\n The path to a local package with should be included in the deploy as\n well (and/or is not available on PyPi)\n \"\"\"\n # Load and parse the config file.\n path_to_config_file = os.path.join(src, config_file)\n cfg = read_cfg(path_to_config_file, profile_name)\n\n # Copy all the pip dependencies required to run your code into a temporary\n # folder then add the handler file in the root of this directory.\n # Zip the contents of this folder into a single file and output to the dist\n # directory.\n path_to_zip_file = build(\n src,\n config_file=config_file,\n requirements=requirements,\n local_package=local_package,\n )\n\n existing_config = get_function_config(cfg)\n if existing_config:\n update_function(\n cfg, path_to_zip_file, existing_config, preserve_vpc=preserve_vpc\n )\n else:\n create_function(cfg, path_to_zip_file)\n\n\ndef deploy_s3(\n src,\n requirements=None,\n local_package=None,\n config_file=\"config.yaml\",\n profile_name=None,\n preserve_vpc=False,\n):\n \"\"\"Deploys a new function via AWS S3.\n\n :param str src:\n The path to your Lambda ready project (folder must contain a valid\n config.yaml and handler module (e.g.: service.py).\n :param str local_package:\n The path to a local package with should be included in the deploy as\n well (and/or is not available on PyPi)\n \"\"\"\n # Load and parse the config file.\n path_to_config_file = os.path.join(src, config_file)\n cfg = read_cfg(path_to_config_file, profile_name)\n\n # Copy all the pip dependencies required to run your code into a temporary\n # folder then add the handler file in the root of this directory.\n # Zip the contents of this folder into a single file and output to the dist\n # directory.\n path_to_zip_file = build(\n src,\n config_file=config_file,\n requirements=requirements,\n local_package=local_package,\n )\n\n use_s3 = True\n s3_file = upload_s3(cfg, path_to_zip_file, use_s3)\n existing_config = get_function_config(cfg)\n if existing_config:\n update_function(\n cfg,\n path_to_zip_file,\n existing_config,\n use_s3=use_s3,\n s3_file=s3_file,\n preserve_vpc=preserve_vpc,\n )\n else:\n create_function(cfg, path_to_zip_file, use_s3=use_s3, s3_file=s3_file)\n\n\ndef upload(\n src,\n requirements=None,\n local_package=None,\n config_file=\"config.yaml\",\n profile_name=None,\n):\n \"\"\"Uploads a new function to AWS S3.\n\n :param str src:\n The path to your Lambda ready project (folder must contain a valid\n config.yaml and handler module (e.g.: service.py).\n :param str local_package:\n The path to a local package with should be included in the deploy as\n well (and/or is not available on PyPi)\n \"\"\"\n # Load and parse the config file.\n path_to_config_file = os.path.join(src, config_file)\n cfg = read_cfg(path_to_config_file, profile_name)\n\n # Copy all the pip dependencies required to run your code into a temporary\n # folder then add the handler file in the root of this directory.\n # Zip the contents of this folder into a single file and output to the dist\n # directory.\n path_to_zip_file = build(\n src,\n config_file=config_file,\n requirements=requirements,\n local_package=local_package,\n )\n\n upload_s3(cfg, path_to_zip_file)\n\n\ndef invoke(\n src,\n event_file=\"event.json\",\n config_file=\"config.yaml\",\n profile_name=None,\n verbose=False,\n):\n \"\"\"Simulates a call to your function.\n\n :param str src:\n The path to your Lambda ready project (folder must contain a valid\n config.yaml and handler module (e.g.: service.py).\n :param str alt_event:\n An optional argument to override which event file to use.\n :param bool verbose:\n Whether to print out verbose details.\n \"\"\"\n # Load and parse the config file.\n path_to_config_file = os.path.join(src, config_file)\n cfg = read_cfg(path_to_config_file, profile_name)\n\n # Set AWS_PROFILE environment variable based on `--profile` option.\n if profile_name:\n os.environ[\"AWS_PROFILE\"] = profile_name\n\n # Load environment variables from the config file into the actual\n # environment.\n env_vars = cfg.get(\"environment_variables\")\n if env_vars:\n for key, value in env_vars.items():\n os.environ[key] = get_environment_variable_value(value)\n\n # Load and parse event file.\n path_to_event_file = os.path.join(src, event_file)\n event = read(path_to_event_file, loader=json.loads)\n\n # Tweak to allow module to import local modules\n try:\n sys.path.index(src)\n except ValueError:\n sys.path.append(src)\n\n handler = cfg.get(\"handler\")\n # Inspect the handler string (<module>.<function name>) and translate it\n # into a function we can execute.\n fn = get_callable_handler_function(src, handler)\n\n timeout = cfg.get(\"timeout\")\n if timeout:\n context = LambdaContext(cfg.get(\"function_name\"), timeout)\n else:\n context = LambdaContext(cfg.get(\"function_name\"))\n\n start = time.time()\n results = fn(event, context)\n end = time.time()\n\n print(\"{0}\".format(results))\n if verbose:\n print(\n \"\\nexecution time: {:.8f}s\\nfunction execution \"\n \"timeout: {:2}s\".format(end - start, cfg.get(\"timeout\", 15))\n )\n\n\ndef init(src, minimal=False):\n \"\"\"Copies template files to a given directory.\n\n :param str src:\n The path to output the template lambda project files.\n :param bool minimal:\n Minimal possible template files (excludes event.json).\n \"\"\"\n\n templates_path = os.path.join(\n os.path.dirname(os.path.abspath(__file__)), \"project_templates\",\n )\n for filename in os.listdir(templates_path):\n if (minimal and filename == \"event.json\") or filename.endswith(\".pyc\"):\n continue\n dest_path = os.path.join(templates_path, filename)\n\n if not os.path.isdir(dest_path):\n copy(dest_path, src)\n\n\ndef build(\n src,\n requirements=None,\n local_package=None,\n config_file=\"config.yaml\",\n profile_name=None,\n):\n \"\"\"Builds the file bundle.\n\n :param str src:\n The path to your Lambda ready project (folder must contain a valid\n config.yaml and handler module (e.g.: service.py).\n :param str local_package:\n The path to a local package with should be included in the deploy as\n well (and/or is not available on PyPi)\n \"\"\"\n # Load and parse the config file.\n path_to_config_file = os.path.join(src, config_file)\n cfg = read_cfg(path_to_config_file, profile_name)\n\n # Get the absolute path to the output directory and create it if it doesn't\n # already exist.\n dist_directory = cfg.get(\"dist_directory\", \"dist\")\n path_to_dist = os.path.join(src, dist_directory)\n mkdir(path_to_dist)\n\n # Combine the name of the Lambda function with the current timestamp to use\n # for the output filename.\n function_name = cfg.get(\"function_name\")\n output_filename = \"{0}-{1}.zip\".format(timestamp(), function_name)\n\n path_to_temp = mkdtemp(prefix=\"aws-lambda\")\n pip_install_to_target(\n path_to_temp, requirements=requirements, local_package=local_package,\n )\n\n # Hack for Zope.\n if \"zope\" in os.listdir(path_to_temp):\n print(\n \"Zope packages detected; fixing Zope package paths to \"\n \"make them importable.\",\n )\n # Touch.\n with open(os.path.join(path_to_temp, \"zope/__init__.py\"), \"wb\"):\n pass\n\n # Gracefully handle whether \".zip\" was included in the filename or not.\n output_filename = (\n \"{0}.zip\".format(output_filename)\n if not output_filename.endswith(\".zip\")\n else output_filename\n )\n\n # Allow definition of source code directories we want to build into our\n # zipped package.\n build_config = defaultdict(**cfg.get(\"build\", {}))\n build_source_directories = build_config.get(\"source_directories\", \"\")\n build_source_directories = (\n build_source_directories\n if build_source_directories is not None\n else \"\"\n )\n source_directories = [\n d.strip() for d in build_source_directories.split(\",\")\n ]\n\n files = []\n for filename in os.listdir(src):\n if os.path.isfile(filename):\n if filename == \".DS_Store\":\n continue\n if filename == config_file:\n continue\n print(\"Bundling: %r\" % filename)\n files.append(os.path.join(src, filename))\n elif os.path.isdir(filename) and filename in source_directories:\n print(\"Bundling directory: %r\" % filename)\n files.append(os.path.join(src, filename))\n\n # \"cd\" into `temp_path` directory.\n os.chdir(path_to_temp)\n for f in files:\n if os.path.isfile(f):\n _, filename = os.path.split(f)\n\n # Copy handler file into root of the packages folder.\n copyfile(f, os.path.join(path_to_temp, filename))\n copystat(f, os.path.join(path_to_temp, filename))\n elif os.path.isdir(f):\n src_path_length = len(src) + 1\n destination_folder = os.path.join(\n path_to_temp, f[src_path_length:]\n )\n copytree(f, destination_folder)\n\n # Zip them together into a single file.\n # TODO: Delete temp directory created once the archive has been compiled.\n path_to_zip_file = archive(\"./\", path_to_dist, output_filename)\n return path_to_zip_file\n\n\ndef get_callable_handler_function(src, handler):\n \"\"\"Translate a string of the form \"module.function\" into a callable\n function.\n\n :param str src:\n The path to your Lambda project containing a valid handler file.\n :param str handler:\n A dot delimited string representing the `<module>.<function name>`.\n \"\"\"\n\n # \"cd\" into `src` directory.\n os.chdir(src)\n\n module_name, function_name = handler.split(\".\")\n filename = get_handler_filename(handler)\n\n path_to_module_file = os.path.join(src, filename)\n module = load_source(module_name, path_to_module_file)\n return getattr(module, function_name)\n\n\ndef get_handler_filename(handler):\n \"\"\"Shortcut to get the filename from the handler string.\n\n :param str handler:\n A dot delimited string representing the `<module>.<function name>`.\n \"\"\"\n module_name, _ = handler.split(\".\")\n return \"{0}.py\".format(module_name)\n\n\ndef _install_packages(path, packages):\n \"\"\"Install all packages listed to the target directory.\n\n Ignores any package that includes Python itself and python-lambda as well\n since its only needed for deploying and not running the code\n\n :param str path:\n Path to copy installed pip packages to.\n :param list packages:\n A list of packages to be installed via pip.\n \"\"\"\n\n def _filter_blacklist(package):\n blacklist = [\"-i\", \"#\", \"Python==\", \"python-lambda==\"]\n return all(package.startswith(entry) is False for entry in blacklist)\n\n filtered_packages = filter(_filter_blacklist, packages)\n for package in filtered_packages:\n if package.startswith(\"-e \"):\n package = package.replace(\"-e \", \"\")\n\n print(\"Installing {package}\".format(package=package))\n subprocess.check_call(\n [\n sys.executable,\n \"-m\",\n \"pip\",\n \"install\",\n package,\n \"-t\",\n path,\n \"--ignore-installed\",\n ]\n )\n print(\n \"Install directory contents are now: {directory}\".format(\n directory=os.listdir(path)\n )\n )\n\n\ndef pip_install_to_target(path, requirements=None, local_package=None):\n \"\"\"For a given active virtualenv, gather all installed pip packages then\n copy (re-install) them to the path provided.\n\n :param str path:\n Path to copy installed pip packages to.\n :param str requirements:\n If set, only the packages in the supplied requirements file are\n installed.\n If not set then installs all packages found via pip freeze.\n :param str local_package:\n The path to a local package with should be included in the deploy as\n well (and/or is not available on PyPi)\n \"\"\"\n packages = []\n if not requirements:\n print(\"Gathering pip packages\")\n pkgStr = subprocess.check_output(\n [sys.executable, \"-m\", \"pip\", \"freeze\"]\n )\n packages.extend(pkgStr.decode(\"utf-8\").splitlines())\n else:\n if os.path.exists(requirements):\n print(\"Gathering requirement packages\")\n data = read(requirements)\n packages.extend(data.splitlines())\n\n if not packages:\n print(\"No dependency packages installed!\")\n\n if local_package is not None:\n if not isinstance(local_package, (list, tuple)):\n local_package = [local_package]\n for l_package in local_package:\n packages.append(l_package)\n _install_packages(path, packages)\n\n\ndef get_role_name(region, account_id, role):\n \"\"\"Shortcut to insert the `account_id` and `role` into the iam string.\"\"\"\n prefix = ARN_PREFIXES.get(region, \"aws\")\n return \"arn:{0}:iam::{1}:role/{2}\".format(prefix, account_id, role)\n\n\ndef get_account_id(\n profile_name, aws_access_key_id, aws_secret_access_key, region=None,\n):\n \"\"\"Query STS for a users' account_id\"\"\"\n client = get_client(\n \"sts\", profile_name, aws_access_key_id, aws_secret_access_key, region,\n )\n return client.get_caller_identity().get(\"Account\")\n\n\ndef get_client(\n client,\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n region=None,\n):\n \"\"\"Shortcut for getting an initialized instance of the boto3 client.\"\"\"\n\n boto3.setup_default_session(\n profile_name=profile_name,\n aws_access_key_id=aws_access_key_id,\n aws_secret_access_key=aws_secret_access_key,\n region_name=region,\n )\n return boto3.client(client)\n\n\ndef create_function(cfg, path_to_zip_file, use_s3=False, s3_file=None):\n \"\"\"Register and upload a function to AWS Lambda.\"\"\"\n\n print(\"Creating your new Lambda function\")\n byte_stream = read(path_to_zip_file, binary_file=True)\n profile_name = cfg.get(\"profile\")\n aws_access_key_id = cfg.get(\"aws_access_key_id\")\n aws_secret_access_key = cfg.get(\"aws_secret_access_key\")\n\n account_id = get_account_id(\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n cfg.get(\"region\",),\n )\n role = get_role_name(\n cfg.get(\"region\"),\n account_id,\n cfg.get(\"role\", \"lambda_basic_execution\"),\n )\n\n client = get_client(\n \"lambda\",\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n cfg.get(\"region\"),\n )\n\n # Do we prefer development variable over config?\n buck_name = os.environ.get(\"S3_BUCKET_NAME\") or cfg.get(\"bucket_name\")\n func_name = os.environ.get(\"LAMBDA_FUNCTION_NAME\") or cfg.get(\n \"function_name\"\n )\n print(\"Creating lambda function with name: {}\".format(func_name))\n\n if use_s3:\n kwargs = {\n \"FunctionName\": func_name,\n \"Runtime\": cfg.get(\"runtime\", \"python2.7\"),\n \"Role\": role,\n \"Handler\": cfg.get(\"handler\"),\n \"Code\": {\n \"S3Bucket\": \"{}\".format(buck_name),\n \"S3Key\": \"{}\".format(s3_file),\n },\n \"Description\": cfg.get(\"description\", \"\"),\n \"Timeout\": cfg.get(\"timeout\", 15),\n \"MemorySize\": cfg.get(\"memory_size\", 512),\n \"VpcConfig\": {\n \"SubnetIds\": cfg.get(\"subnet_ids\", []),\n \"SecurityGroupIds\": cfg.get(\"security_group_ids\", []),\n },\n \"Publish\": True,\n }\n else:\n kwargs = {\n \"FunctionName\": func_name,\n \"Runtime\": cfg.get(\"runtime\", \"python2.7\"),\n \"Role\": role,\n \"Handler\": cfg.get(\"handler\"),\n \"Code\": {\"ZipFile\": byte_stream},\n \"Description\": cfg.get(\"description\", \"\"),\n \"Timeout\": cfg.get(\"timeout\", 15),\n \"MemorySize\": cfg.get(\"memory_size\", 512),\n \"VpcConfig\": {\n \"SubnetIds\": cfg.get(\"subnet_ids\", []),\n \"SecurityGroupIds\": cfg.get(\"security_group_ids\", []),\n },\n \"Publish\": True,\n }\n\n if \"tags\" in cfg:\n kwargs.update(\n Tags={key: str(value) for key, value in cfg.get(\"tags\").items()}\n )\n\n if \"environment_variables\" in cfg:\n kwargs.update(\n Environment={\n \"Variables\": {\n key: get_environment_variable_value(value)\n for key, value in cfg.get(\"environment_variables\").items()\n },\n },\n )\n\n client.create_function(**kwargs)\n\n concurrency = get_concurrency(cfg)\n if concurrency > 0:\n client.put_function_concurrency(\n FunctionName=func_name, ReservedConcurrentExecutions=concurrency\n )\n\n\ndef update_function(\n cfg,\n path_to_zip_file,\n existing_cfg,\n use_s3=False,\n s3_file=None,\n preserve_vpc=False,\n):\n \"\"\"Updates the code of an existing Lambda function\"\"\"\n\n print(\"Updating your Lambda function\")\n byte_stream = read(path_to_zip_file, binary_file=True)\n profile_name = cfg.get(\"profile\")\n aws_access_key_id = cfg.get(\"aws_access_key_id\")\n aws_secret_access_key = cfg.get(\"aws_secret_access_key\")\n\n account_id = get_account_id(\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n cfg.get(\"region\",),\n )\n role = get_role_name(\n cfg.get(\"region\"),\n account_id,\n cfg.get(\"role\", \"lambda_basic_execution\"),\n )\n\n client = get_client(\n \"lambda\",\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n cfg.get(\"region\"),\n )\n\n # Do we prefer development variable over config?\n buck_name = os.environ.get(\"S3_BUCKET_NAME\") or cfg.get(\"bucket_name\")\n\n if use_s3:\n client.update_function_code(\n FunctionName=cfg.get(\"function_name\"),\n S3Bucket=\"{}\".format(buck_name),\n S3Key=\"{}\".format(s3_file),\n Publish=True,\n )\n else:\n client.update_function_code(\n FunctionName=cfg.get(\"function_name\"),\n ZipFile=byte_stream,\n Publish=True,\n )\n\n kwargs = {\n \"FunctionName\": cfg.get(\"function_name\"),\n \"Role\": role,\n \"Runtime\": cfg.get(\"runtime\"),\n \"Handler\": cfg.get(\"handler\"),\n \"Description\": cfg.get(\"description\", \"\"),\n \"Timeout\": cfg.get(\"timeout\", 15),\n \"MemorySize\": cfg.get(\"memory_size\", 512),\n }\n\n if preserve_vpc:\n kwargs[\"VpcConfig\"] = existing_cfg.get(\"Configuration\", {}).get(\n \"VpcConfig\"\n )\n if kwargs[\"VpcConfig\"] is None:\n kwargs[\"VpcConfig\"] = {\n \"SubnetIds\": cfg.get(\"subnet_ids\", []),\n \"SecurityGroupIds\": cfg.get(\"security_group_ids\", []),\n }\n else:\n del kwargs[\"VpcConfig\"][\"VpcId\"]\n else:\n kwargs[\"VpcConfig\"] = {\n \"SubnetIds\": cfg.get(\"subnet_ids\", []),\n \"SecurityGroupIds\": cfg.get(\"security_group_ids\", []),\n }\n\n if \"environment_variables\" in cfg:\n kwargs.update(\n Environment={\n \"Variables\": {\n key: str(get_environment_variable_value(value))\n for key, value in cfg.get(\"environment_variables\").items()\n },\n },\n )\n\n ret = client.update_function_configuration(**kwargs)\n\n concurrency = get_concurrency(cfg)\n if concurrency > 0:\n client.put_function_concurrency(\n FunctionName=cfg.get(\"function_name\"),\n ReservedConcurrentExecutions=concurrency,\n )\n elif \"Concurrency\" in existing_cfg:\n client.delete_function_concurrency(\n FunctionName=cfg.get(\"function_name\")\n )\n\n if \"tags\" in cfg:\n tags = {key: str(value) for key, value in cfg.get(\"tags\").items()}\n if tags != existing_cfg.get(\"Tags\"):\n if existing_cfg.get(\"Tags\"):\n client.untag_resource(\n Resource=ret[\"FunctionArn\"],\n TagKeys=list(existing_cfg[\"Tags\"].keys()),\n )\n client.tag_resource(Resource=ret[\"FunctionArn\"], Tags=tags)\n\n\ndef upload_s3(cfg, path_to_zip_file, *use_s3):\n \"\"\"Upload a function to AWS S3.\"\"\"\n\n print(\"Uploading your new Lambda function\")\n profile_name = cfg.get(\"profile\")\n aws_access_key_id = cfg.get(\"aws_access_key_id\")\n aws_secret_access_key = cfg.get(\"aws_secret_access_key\")\n client = get_client(\n \"s3\",\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n cfg.get(\"region\"),\n )\n byte_stream = b\"\"\n with open(path_to_zip_file, mode=\"rb\") as fh:\n byte_stream = fh.read()\n s3_key_prefix = cfg.get(\"s3_key_prefix\", \"/dist\")\n checksum = hashlib.new(\"md5\", byte_stream).hexdigest()\n timestamp = str(time.time())\n filename = \"{prefix}{checksum}-{ts}.zip\".format(\n prefix=s3_key_prefix, checksum=checksum, ts=timestamp,\n )\n\n # Do we prefer development variable over config?\n buck_name = os.environ.get(\"S3_BUCKET_NAME\") or cfg.get(\"bucket_name\")\n func_name = os.environ.get(\"LAMBDA_FUNCTION_NAME\") or cfg.get(\n \"function_name\"\n )\n kwargs = {\n \"Bucket\": \"{}\".format(buck_name),\n \"Key\": \"{}\".format(filename),\n \"Body\": byte_stream,\n }\n\n client.put_object(**kwargs)\n print(\"Finished uploading {} to S3 bucket {}\".format(func_name, buck_name))\n if use_s3:\n return filename\n\n\ndef get_function_config(cfg):\n \"\"\"Check whether a function exists or not and return its config\"\"\"\n\n function_name = cfg.get(\"function_name\")\n profile_name = cfg.get(\"profile\")\n aws_access_key_id = cfg.get(\"aws_access_key_id\")\n aws_secret_access_key = cfg.get(\"aws_secret_access_key\")\n client = get_client(\n \"lambda\",\n profile_name,\n aws_access_key_id,\n aws_secret_access_key,\n cfg.get(\"region\"),\n )\n\n try:\n return client.get_function(FunctionName=function_name)\n except client.exceptions.ResourceNotFoundException as e:\n if \"Function not found\" in str(e):\n return False\n\n\ndef get_concurrency(cfg):\n \"\"\"Return the Reserved Concurrent Executions if present in the config\"\"\"\n concurrency = int(cfg.get(\"concurrency\", 0))\n return max(0, concurrency)\n\n\ndef read_cfg(path_to_config_file, profile_name):\n cfg = read(path_to_config_file, loader=yaml.full_load)\n if profile_name is not None:\n cfg[\"profile\"] = profile_name\n elif \"AWS_PROFILE\" in os.environ:\n cfg[\"profile\"] = os.environ[\"AWS_PROFILE\"]\n return cfg\n", "repo_name": "nficano/python-lambda", "path": "aws_lambda/aws_lambda.py", "language": "Python", "license": "isc", "size": 26779}
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.