Spaces:
Sleeping
Sleeping
File size: 3,322 Bytes
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import io
from huggingface_hub import HfApi
from autotrain.backends.base import BaseBackend
from autotrain.trainers.generic.params import GenericParams
_DOCKERFILE = """
FROM huggingface/autotrain-advanced:latest
CMD pip uninstall -y autotrain-advanced && pip install -U autotrain-advanced && autotrain api --port 7860 --host 0.0.0.0
"""
# format _DOCKERFILE
_DOCKERFILE = _DOCKERFILE.replace("\n", " ").replace(" ", "\n").strip()
class SpaceRunner(BaseBackend):
"""
SpaceRunner is a backend class responsible for creating and managing training jobs on Hugging Face Spaces.
Methods
-------
_create_readme():
Creates a README.md file content for the space.
_add_secrets(api, space_id):
Adds necessary secrets to the space repository.
create():
Creates a new space repository, adds secrets, and uploads necessary files.
"""
def _create_readme(self):
_readme = "---\n"
_readme += f"title: {self.params.project_name}\n"
_readme += "emoji: 🚀\n"
_readme += "colorFrom: green\n"
_readme += "colorTo: indigo\n"
_readme += "sdk: docker\n"
_readme += "pinned: false\n"
_readme += "tags:\n"
_readme += "- autotrain\n"
_readme += "duplicated_from: autotrain-projects/autotrain-advanced\n"
_readme += "---\n"
_readme = io.BytesIO(_readme.encode())
return _readme
def _add_secrets(self, api, space_id):
if isinstance(self.params, GenericParams):
for k, v in self.params.env.items():
api.add_space_secret(repo_id=space_id, key=k, value=v)
self.params.env = {}
api.add_space_secret(repo_id=space_id, key="HF_TOKEN", value=self.params.token)
api.add_space_secret(repo_id=space_id, key="AUTOTRAIN_USERNAME", value=self.username)
api.add_space_secret(repo_id=space_id, key="PROJECT_NAME", value=self.params.project_name)
api.add_space_secret(repo_id=space_id, key="TASK_ID", value=str(self.task_id))
api.add_space_secret(repo_id=space_id, key="PARAMS", value=self.params.model_dump_json())
api.add_space_secret(repo_id=space_id, key="DATA_PATH", value=self.params.data_path)
if not isinstance(self.params, GenericParams):
api.add_space_secret(repo_id=space_id, key="MODEL", value=self.params.model)
def create(self):
api = HfApi(token=self.params.token)
space_id = f"{self.username}/autotrain-{self.params.project_name}"
api.create_repo(
repo_id=space_id,
repo_type="space",
space_sdk="docker",
space_hardware=self.available_hardware[self.backend],
private=True,
)
self._add_secrets(api, space_id)
api.set_space_sleep_time(repo_id=space_id, sleep_time=604800)
readme = self._create_readme()
api.upload_file(
path_or_fileobj=readme,
path_in_repo="README.md",
repo_id=space_id,
repo_type="space",
)
_dockerfile = io.BytesIO(_DOCKERFILE.encode())
api.upload_file(
path_or_fileobj=_dockerfile,
path_in_repo="Dockerfile",
repo_id=space_id,
repo_type="space",
)
return space_id
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