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import os |
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import webbrowser |
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from pathlib import Path |
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from gradio_client import Client |
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from trackio import context_vars, deploy, utils |
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from trackio.imports import import_csv |
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from trackio.run import Run |
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from trackio.sqlite_storage import SQLiteStorage |
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from trackio.ui import demo |
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from trackio.utils import TRACKIO_DIR, TRACKIO_LOGO_PATH |
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__version__ = Path(__file__).parent.joinpath("version.txt").read_text().strip() |
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__all__ = ["init", "log", "finish", "show", "import_csv"] |
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config = {} |
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def init( |
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project: str, |
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name: str | None = None, |
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space_id: str | None = None, |
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dataset_id: str | None = None, |
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config: dict | None = None, |
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resume: str = "never", |
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) -> Run: |
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""" |
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Creates a new Trackio project and returns a Run object. |
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Args: |
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project: The name of the project (can be an existing project to continue tracking or a new project to start tracking from scratch). |
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name: The name of the run (if not provided, a default name will be generated). |
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space_id: If provided, the project will be logged to a Hugging Face Space instead of a local directory. Should be a complete Space name like "username/reponame" or "orgname/reponame", or just "reponame" in which case the Space will be created in the currently-logged-in Hugging Face user's namespace. If the Space does not exist, it will be created. If the Space already exists, the project will be logged to it. |
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dataset_id: If a space_id is provided, a persistent Hugging Face Dataset will be created and the metrics will be synced to it every 5 minutes. Specify a Dataset with name like "username/datasetname" or "orgname/datasetname", or "datasetname" (uses currently-logged-in Hugging Face user's namespace), or None (uses the same name as the Space but with the "_dataset" suffix). If the Dataset does not exist, it will be created. If the Dataset already exists, the project will be appended to it. |
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config: A dictionary of configuration options. Provided for compatibility with wandb.init() |
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resume: Controls how to handle resuming a run. Can be one of: |
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- "must": Must resume the run with the given name, raises error if run doesn't exist |
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- "allow": Resume the run if it exists, otherwise create a new run |
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- "never": Never resume a run, always create a new one |
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""" |
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if space_id is None and dataset_id is not None: |
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raise ValueError("Must provide a `space_id` when `dataset_id` is provided.") |
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space_id, dataset_id = utils.preprocess_space_and_dataset_ids(space_id, dataset_id) |
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url = context_vars.current_server.get() |
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if url is None: |
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if space_id is None: |
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_, url, _ = demo.launch( |
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show_api=False, |
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inline=False, |
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quiet=True, |
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prevent_thread_lock=True, |
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show_error=True, |
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) |
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else: |
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url = space_id |
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context_vars.current_server.set(url) |
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if ( |
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context_vars.current_project.get() is None |
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or context_vars.current_project.get() != project |
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): |
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print(f"* Trackio project initialized: {project}") |
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if dataset_id is not None: |
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os.environ["TRACKIO_DATASET_ID"] = dataset_id |
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print( |
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f"* Trackio metrics will be synced to Hugging Face Dataset: {dataset_id}" |
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) |
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if space_id is None: |
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print(f"* Trackio metrics logged to: {TRACKIO_DIR}") |
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utils.print_dashboard_instructions(project) |
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else: |
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deploy.create_space_if_not_exists(space_id, dataset_id) |
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print( |
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f"* View dashboard by going to: {deploy.SPACE_URL.format(space_id=space_id)}" |
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) |
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context_vars.current_project.set(project) |
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client = None |
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if not space_id: |
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client = Client(url, verbose=False) |
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if resume == "must": |
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if name is None: |
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raise ValueError("Must provide a run name when resume='must'") |
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if name not in SQLiteStorage.get_runs(project): |
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raise ValueError(f"Run '{name}' does not exist in project '{project}'") |
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elif resume == "allow": |
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if name is not None and name in SQLiteStorage.get_runs(project): |
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print(f"* Resuming existing run: {name}") |
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elif resume == "never": |
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if name is not None and name in SQLiteStorage.get_runs(project): |
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name = None |
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else: |
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raise ValueError("resume must be one of: 'must', 'allow', or 'never'") |
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run = Run( |
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url=url, |
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project=project, |
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client=client, |
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name=name, |
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config=config, |
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) |
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context_vars.current_run.set(run) |
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globals()["config"] = run.config |
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return run |
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def log(metrics: dict) -> None: |
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""" |
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Logs metrics to the current run. |
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Args: |
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metrics: A dictionary of metrics to log. |
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""" |
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if context_vars.current_run.get() is None: |
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raise RuntimeError("Call trackio.init() before log().") |
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context_vars.current_run.get().log(metrics) |
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def finish(): |
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""" |
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Finishes the current run. |
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""" |
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if context_vars.current_run.get() is None: |
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raise RuntimeError("Call trackio.init() before finish().") |
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context_vars.current_run.get().finish() |
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def show(project: str | None = None): |
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""" |
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Launches the Trackio dashboard. |
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Args: |
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project: The name of the project whose runs to show. If not provided, all projects will be shown and the user can select one. |
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""" |
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_, url, share_url = demo.launch( |
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show_api=False, |
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quiet=True, |
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inline=False, |
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prevent_thread_lock=True, |
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favicon_path=TRACKIO_LOGO_PATH, |
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allowed_paths=[TRACKIO_LOGO_PATH], |
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) |
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base_url = share_url + "/" if share_url else url |
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dashboard_url = base_url + f"?project={project}" if project else base_url |
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print(f"* Trackio UI launched at: {dashboard_url}") |
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webbrowser.open(dashboard_url) |
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utils.block_except_in_notebook() |
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