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author | S. Solomon Darnell | 2025-03-28 21:52:21 -0500 |
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committer | S. Solomon Darnell | 2025-03-28 21:52:21 -0500 |
commit | 4a52a71956a8d46fcb7294ac71734504bb09bcc2 (patch) | |
tree | ee3dc5af3b6313e921cd920906356f5d4febc4ed /.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py | |
parent | cc961e04ba734dd72309fb548a2f97d67d578813 (diff) | |
download | gn-ai-master.tar.gz |
Diffstat (limited to '.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py')
-rw-r--r-- | .venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py | 425 |
1 files changed, 425 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py b/.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py new file mode 100644 index 00000000..e75eba2a --- /dev/null +++ b/.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py @@ -0,0 +1,425 @@ +import json +import os +from pathlib import Path +from pickle import DEFAULT_PROTOCOL, PicklingError +from typing import Any, Dict, List, Optional, Union + +from packaging import version + +from huggingface_hub import constants, snapshot_download +from huggingface_hub.hf_api import HfApi +from huggingface_hub.utils import ( + SoftTemporaryDirectory, + get_fastai_version, + get_fastcore_version, + get_python_version, +) + +from .utils import logging, validate_hf_hub_args +from .utils._runtime import _PY_VERSION # noqa: F401 # for backward compatibility... + + +logger = logging.get_logger(__name__) + + +def _check_fastai_fastcore_versions( + fastai_min_version: str = "2.4", + fastcore_min_version: str = "1.3.27", +): + """ + Checks that the installed fastai and fastcore versions are compatible for pickle serialization. + + Args: + fastai_min_version (`str`, *optional*): + The minimum fastai version supported. + fastcore_min_version (`str`, *optional*): + The minimum fastcore version supported. + + <Tip> + Raises the following error: + + - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError) + if the fastai or fastcore libraries are not available or are of an invalid version. + + </Tip> + """ + + if (get_fastcore_version() or get_fastai_version()) == "N/A": + raise ImportError( + f"fastai>={fastai_min_version} and fastcore>={fastcore_min_version} are" + f" required. Currently using fastai=={get_fastai_version()} and" + f" fastcore=={get_fastcore_version()}." + ) + + current_fastai_version = version.Version(get_fastai_version()) + current_fastcore_version = version.Version(get_fastcore_version()) + + if current_fastai_version < version.Version(fastai_min_version): + raise ImportError( + "`push_to_hub_fastai` and `from_pretrained_fastai` require a" + f" fastai>={fastai_min_version} version, but you are using fastai version" + f" {get_fastai_version()} which is incompatible. Upgrade with `pip install" + " fastai==2.5.6`." + ) + + if current_fastcore_version < version.Version(fastcore_min_version): + raise ImportError( + "`push_to_hub_fastai` and `from_pretrained_fastai` require a" + f" fastcore>={fastcore_min_version} version, but you are using fastcore" + f" version {get_fastcore_version()} which is incompatible. Upgrade with" + " `pip install fastcore==1.3.27`." + ) + + +def _check_fastai_fastcore_pyproject_versions( + storage_folder: str, + fastai_min_version: str = "2.4", + fastcore_min_version: str = "1.3.27", +): + """ + Checks that the `pyproject.toml` file in the directory `storage_folder` has fastai and fastcore versions + that are compatible with `from_pretrained_fastai` and `push_to_hub_fastai`. If `pyproject.toml` does not exist + or does not contain versions for fastai and fastcore, then it logs a warning. + + Args: + storage_folder (`str`): + Folder to look for the `pyproject.toml` file. + fastai_min_version (`str`, *optional*): + The minimum fastai version supported. + fastcore_min_version (`str`, *optional*): + The minimum fastcore version supported. + + <Tip> + Raises the following errors: + + - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError) + if the `toml` module is not installed. + - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError) + if the `pyproject.toml` indicates a lower than minimum supported version of fastai or fastcore. + + </Tip> + """ + + try: + import toml + except ModuleNotFoundError: + raise ImportError( + "`push_to_hub_fastai` and `from_pretrained_fastai` require the toml module." + " Install it with `pip install toml`." + ) + + # Checks that a `pyproject.toml`, with `build-system` and `requires` sections, exists in the repository. If so, get a list of required packages. + if not os.path.isfile(f"{storage_folder}/pyproject.toml"): + logger.warning( + "There is no `pyproject.toml` in the repository that contains the fastai" + " `Learner`. The `pyproject.toml` would allow us to verify that your fastai" + " and fastcore versions are compatible with those of the model you want to" + " load." + ) + return + pyproject_toml = toml.load(f"{storage_folder}/pyproject.toml") + + if "build-system" not in pyproject_toml.keys(): + logger.warning( + "There is no `build-system` section in the pyproject.toml of the repository" + " that contains the fastai `Learner`. The `build-system` would allow us to" + " verify that your fastai and fastcore versions are compatible with those" + " of the model you want to load." + ) + return + build_system_toml = pyproject_toml["build-system"] + + if "requires" not in build_system_toml.keys(): + logger.warning( + "There is no `requires` section in the pyproject.toml of the repository" + " that contains the fastai `Learner`. The `requires` would allow us to" + " verify that your fastai and fastcore versions are compatible with those" + " of the model you want to load." + ) + return + package_versions = build_system_toml["requires"] + + # Extracts contains fastai and fastcore versions from `pyproject.toml` if available. + # If the package is specified but not the version (e.g. "fastai" instead of "fastai=2.4"), the default versions are the highest. + fastai_packages = [pck for pck in package_versions if pck.startswith("fastai")] + if len(fastai_packages) == 0: + logger.warning("The repository does not have a fastai version specified in the `pyproject.toml`.") + # fastai_version is an empty string if not specified + else: + fastai_version = str(fastai_packages[0]).partition("=")[2] + if fastai_version != "" and version.Version(fastai_version) < version.Version(fastai_min_version): + raise ImportError( + "`from_pretrained_fastai` requires" + f" fastai>={fastai_min_version} version but the model to load uses" + f" {fastai_version} which is incompatible." + ) + + fastcore_packages = [pck for pck in package_versions if pck.startswith("fastcore")] + if len(fastcore_packages) == 0: + logger.warning("The repository does not have a fastcore version specified in the `pyproject.toml`.") + # fastcore_version is an empty string if not specified + else: + fastcore_version = str(fastcore_packages[0]).partition("=")[2] + if fastcore_version != "" and version.Version(fastcore_version) < version.Version(fastcore_min_version): + raise ImportError( + "`from_pretrained_fastai` requires" + f" fastcore>={fastcore_min_version} version, but you are using fastcore" + f" version {fastcore_version} which is incompatible." + ) + + +README_TEMPLATE = """--- +tags: +- fastai +--- + +# Amazing! + +🥳 Congratulations on hosting your fastai model on the Hugging Face Hub! + +# Some next steps +1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))! + +2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([documentation here](https://huggingface.co/docs/hub/spaces)). + +3. Join the fastai community on the [Fastai Discord](https://discord.com/invite/YKrxeNn)! + +Greetings fellow fastlearner 🤝! Don't forget to delete this content from your model card. + + +--- + + +# Model card + +## Model description +More information needed + +## Intended uses & limitations +More information needed + +## Training and evaluation data +More information needed +""" + +PYPROJECT_TEMPLATE = f"""[build-system] +requires = ["setuptools>=40.8.0", "wheel", "python={get_python_version()}", "fastai={get_fastai_version()}", "fastcore={get_fastcore_version()}"] +build-backend = "setuptools.build_meta:__legacy__" +""" + + +def _create_model_card(repo_dir: Path): + """ + Creates a model card for the repository. + + Args: + repo_dir (`Path`): + Directory where model card is created. + """ + readme_path = repo_dir / "README.md" + + if not readme_path.exists(): + with readme_path.open("w", encoding="utf-8") as f: + f.write(README_TEMPLATE) + + +def _create_model_pyproject(repo_dir: Path): + """ + Creates a `pyproject.toml` for the repository. + + Args: + repo_dir (`Path`): + Directory where `pyproject.toml` is created. + """ + pyproject_path = repo_dir / "pyproject.toml" + + if not pyproject_path.exists(): + with pyproject_path.open("w", encoding="utf-8") as f: + f.write(PYPROJECT_TEMPLATE) + + +def _save_pretrained_fastai( + learner, + save_directory: Union[str, Path], + config: Optional[Dict[str, Any]] = None, +): + """ + Saves a fastai learner to `save_directory` in pickle format using the default pickle protocol for the version of python used. + + Args: + learner (`Learner`): + The `fastai.Learner` you'd like to save. + save_directory (`str` or `Path`): + Specific directory in which you want to save the fastai learner. + config (`dict`, *optional*): + Configuration object. Will be uploaded as a .json file. Example: 'https://huggingface.co/espejelomar/fastai-pet-breeds-classification/blob/main/config.json'. + + <Tip> + + Raises the following error: + + - [`RuntimeError`](https://docs.python.org/3/library/exceptions.html#RuntimeError) + if the config file provided is not a dictionary. + + </Tip> + """ + _check_fastai_fastcore_versions() + + os.makedirs(save_directory, exist_ok=True) + + # if the user provides config then we update it with the fastai and fastcore versions in CONFIG_TEMPLATE. + if config is not None: + if not isinstance(config, dict): + raise RuntimeError(f"Provided config should be a dict. Got: '{type(config)}'") + path = os.path.join(save_directory, constants.CONFIG_NAME) + with open(path, "w") as f: + json.dump(config, f) + + _create_model_card(Path(save_directory)) + _create_model_pyproject(Path(save_directory)) + + # learner.export saves the model in `self.path`. + learner.path = Path(save_directory) + os.makedirs(save_directory, exist_ok=True) + try: + learner.export( + fname="model.pkl", + pickle_protocol=DEFAULT_PROTOCOL, + ) + except PicklingError: + raise PicklingError( + "You are using a lambda function, i.e., an anonymous function. `pickle`" + " cannot pickle function objects and requires that all functions have" + " names. One possible solution is to name the function." + ) + + +@validate_hf_hub_args +def from_pretrained_fastai( + repo_id: str, + revision: Optional[str] = None, +): + """ + Load pretrained fastai model from the Hub or from a local directory. + + Args: + repo_id (`str`): + The location where the pickled fastai.Learner is. It can be either of the two: + - Hosted on the Hugging Face Hub. E.g.: 'espejelomar/fatai-pet-breeds-classification' or 'distilgpt2'. + You can add a `revision` by appending `@` at the end of `repo_id`. E.g.: `dbmdz/bert-base-german-cased@main`. + Revision is the specific model version to use. Since we use a git-based system for storing models and other + artifacts on the Hugging Face Hub, it can be a branch name, a tag name, or a commit id. + - Hosted locally. `repo_id` would be a directory containing the pickle and a pyproject.toml + indicating the fastai and fastcore versions used to build the `fastai.Learner`. E.g.: `./my_model_directory/`. + revision (`str`, *optional*): + Revision at which the repo's files are downloaded. See documentation of `snapshot_download`. + + Returns: + The `fastai.Learner` model in the `repo_id` repo. + """ + _check_fastai_fastcore_versions() + + # Load the `repo_id` repo. + # `snapshot_download` returns the folder where the model was stored. + # `cache_dir` will be the default '/root/.cache/huggingface/hub' + if not os.path.isdir(repo_id): + storage_folder = snapshot_download( + repo_id=repo_id, + revision=revision, + library_name="fastai", + library_version=get_fastai_version(), + ) + else: + storage_folder = repo_id + + _check_fastai_fastcore_pyproject_versions(storage_folder) + + from fastai.learner import load_learner # type: ignore + + return load_learner(os.path.join(storage_folder, "model.pkl")) + + +@validate_hf_hub_args +def push_to_hub_fastai( + learner, + *, + repo_id: str, + commit_message: str = "Push FastAI model using huggingface_hub.", + private: Optional[bool] = None, + token: Optional[str] = None, + config: Optional[dict] = None, + branch: Optional[str] = None, + create_pr: Optional[bool] = None, + allow_patterns: Optional[Union[List[str], str]] = None, + ignore_patterns: Optional[Union[List[str], str]] = None, + delete_patterns: Optional[Union[List[str], str]] = None, + api_endpoint: Optional[str] = None, +): + """ + Upload learner checkpoint files to the Hub. + + Use `allow_patterns` and `ignore_patterns` to precisely filter which files should be pushed to the hub. Use + `delete_patterns` to delete existing remote files in the same commit. See [`upload_folder`] reference for more + details. + + Args: + learner (`Learner`): + The `fastai.Learner' you'd like to push to the Hub. + repo_id (`str`): + The repository id for your model in Hub in the format of "namespace/repo_name". The namespace can be your individual account or an organization to which you have write access (for example, 'stanfordnlp/stanza-de'). + commit_message (`str`, *optional*): + Message to commit while pushing. Will default to :obj:`"add model"`. + private (`bool`, *optional*): + Whether or not the repository created should be private. + If `None` (default), will default to been public except if the organization's default is private. + token (`str`, *optional*): + The Hugging Face account token to use as HTTP bearer authorization for remote files. If :obj:`None`, the token will be asked by a prompt. + config (`dict`, *optional*): + Configuration object to be saved alongside the model weights. + branch (`str`, *optional*): + The git branch on which to push the model. This defaults to + the default branch as specified in your repository, which + defaults to `"main"`. + create_pr (`boolean`, *optional*): + Whether or not to create a Pull Request from `branch` with that commit. + Defaults to `False`. + api_endpoint (`str`, *optional*): + The API endpoint to use when pushing the model to the hub. + allow_patterns (`List[str]` or `str`, *optional*): + If provided, only files matching at least one pattern are pushed. + ignore_patterns (`List[str]` or `str`, *optional*): + If provided, files matching any of the patterns are not pushed. + delete_patterns (`List[str]` or `str`, *optional*): + If provided, remote files matching any of the patterns will be deleted from the repo. + + Returns: + The url of the commit of your model in the given repository. + + <Tip> + + Raises the following error: + + - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError) + if the user is not log on to the Hugging Face Hub. + + </Tip> + """ + _check_fastai_fastcore_versions() + api = HfApi(endpoint=api_endpoint) + repo_id = api.create_repo(repo_id=repo_id, token=token, private=private, exist_ok=True).repo_id + + # Push the files to the repo in a single commit + with SoftTemporaryDirectory() as tmp: + saved_path = Path(tmp) / repo_id + _save_pretrained_fastai(learner, saved_path, config=config) + return api.upload_folder( + repo_id=repo_id, + token=token, + folder_path=saved_path, + commit_message=commit_message, + revision=branch, + create_pr=create_pr, + allow_patterns=allow_patterns, + ignore_patterns=ignore_patterns, + delete_patterns=delete_patterns, + ) |