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dd	lmZ dZW n eyT   eZdZY nw Y nw er`dd	lmZ G dd deZdS )zFContains a logger to push training logs to the Hub, using Tensorboard.    )Path)TYPE_CHECKINGListOptionalUnion   )CommitScheduler)EntryNotFoundError)	ModelCard)experimental)SummaryWriterTFc                       s   e Zd ZdZed fddZdddddddd	ddd

dedee dee	e
f dedee dee dee dee deeee ef  deeee ef  dee f fddZ fddZ  ZS )HFSummaryWritera  
    Wrapper around the tensorboard's `SummaryWriter` to push training logs to the Hub.

    Data is logged locally and then pushed to the Hub asynchronously. Pushing data to the Hub is done in a separate
    thread to avoid blocking the training script. In particular, if the upload fails for any reason (e.g. a connection
    issue), the main script will not be interrupted. Data is automatically pushed to the Hub every `commit_every`
    minutes (default to every 5 minutes).

    <Tip warning={true}>

    `HFSummaryWriter` is experimental. Its API is subject to change in the future without prior notice.

    </Tip>

    Args:
        repo_id (`str`):
            The id of the repo to which the logs will be pushed.
        logdir (`str`, *optional*):
            The directory where the logs will be written. If not specified, a local directory will be created by the
            underlying `SummaryWriter` object.
        commit_every (`int` or `float`, *optional*):
            The frequency (in minutes) at which the logs will be pushed to the Hub. Defaults to 5 minutes.
        squash_history (`bool`, *optional*):
            Whether to squash the history of the repo after each commit. Defaults to `False`. Squashing commits is
            useful to avoid degraded performances on the repo when it grows too large.
        repo_type (`str`, *optional*):
            The type of the repo to which the logs will be pushed. Defaults to "model".
        repo_revision (`str`, *optional*):
            The revision of the repo to which the logs will be pushed. Defaults to "main".
        repo_private (`bool`, *optional*):
            Whether to make the repo private. If `None` (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists.
        path_in_repo (`str`, *optional*):
            The path to the folder in the repo where the logs will be pushed. Defaults to "tensorboard/".
        repo_allow_patterns (`List[str]` or `str`, *optional*):
            A list of patterns to include in the upload. Defaults to `"*.tfevents.*"`. Check out the
            [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details.
        repo_ignore_patterns (`List[str]` or `str`, *optional*):
            A list of patterns to exclude in the upload. Check out the
            [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details.
        token (`str`, *optional*):
            Authentication token. Will default to the stored token. See https://huggingface.co/settings/token for more
            details
        kwargs:
            Additional keyword arguments passed to `SummaryWriter`.

    Examples:
    ```diff
    # Taken from https://pytorch.org/docs/stable/tensorboard.html
    - from torch.utils.tensorboard import SummaryWriter
    + from huggingface_hub import HFSummaryWriter

    import numpy as np

    - writer = SummaryWriter()
    + writer = HFSummaryWriter(repo_id="username/my-trained-model")

    for n_iter in range(100):
        writer.add_scalar('Loss/train', np.random.random(), n_iter)
        writer.add_scalar('Loss/test', np.random.random(), n_iter)
        writer.add_scalar('Accuracy/train', np.random.random(), n_iter)
        writer.add_scalar('Accuracy/test', np.random.random(), n_iter)
    ```

    ```py
    >>> from huggingface_hub import HFSummaryWriter

    # Logs are automatically pushed every 15 minutes (5 by default) + when exiting the context manager
    >>> with HFSummaryWriter(repo_id="test_hf_logger", commit_every=15) as logger:
    ...     logger.add_scalar("a", 1)
    ...     logger.add_scalar("b", 2)
    ```
    returnc                    s   t stdt | S )NzvYou must have `tensorboard` installed to use `HFSummaryWriter`. Please run `pip install --upgrade tensorboardX` first.)is_summary_writer_availableImportErrorsuper__new__)clsargskwargs	__class__ R/var/www/auris/lib/python3.10/site-packages/huggingface_hub/_tensorboard_logger.pyr   y   s
   zHFSummaryWriter.__new__N   FZtensorboardz*.tfevents.*)
logdircommit_everysquash_history	repo_typerepo_revisionrepo_privatepath_in_reporepo_allow_patternsrepo_ignore_patternstokenrepo_idr   r   r   r   r   r    r!   r"   r#   r$   c       
            s.  t  jdd|i| t| jts td| j dt| j d|d u s(|dkr/t| jj}n|	dd t| jj }t
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   loadr	   datagetappendZpush_to_hub)selfr%   r   r   r   r   r   r    r!   r"   r#   r$   r   Zcardr,   r   r   r   r-      sB   

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

zHFSummaryWriter.__init__c                    s&   t  ||| | j }|  dS )zLPush to hub in a non-blocking way when exiting the logger's context manager.N)r   __exit__r4   triggerresult)r9   exc_typeexc_valexc_tbfuturer   r   r   r:      s   
zHFSummaryWriter.__exit__)r   r   )__name__
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	
<r   N)rD   pathlibr   typingr   r   r   r   Z_commit_schedulerr   errorsr	   Zrepocardr
   utilsr   ZtensorboardXr   r   r   Ztorch.utils.tensorboardobjectr   r   r   r   r   <module>   s.   
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