o xi@sdZddlmZddlZddlmZddlmZzddlmZWne y/ddl mZYnwddl Z ddl m Z er@ddlZed Zda   d"d#ddZ d$d%d d!ZdS)&zwatch.) annotationsN)Sequence) TYPE_CHECKING)Literal) telemetrywandb gradientsFrun wandb.Runmodels+torch.nn.Module | Sequence[torch.nn.Module] criteriontorch.F | Nonelog0Literal['gradients', 'parameters', 'all'] | Nonelog_freqintidx int | None log_graphboolcCs@t }d|j_Wdn1swYtd|dvr%td|dv}|dv} t|tt fs7|f}t j j dd d } |D]} t| | j jsStd t| qAg} d } |dur^t}t|D];\}} ||}td 7a|dkrwd|} |r|jj| | |d| r|jj| | |d|r|jj| ||d}| |qb| S)aRHooks into the given PyTorch model(s) to monitor gradients and the model's computational graph. This function can track parameters, gradients, or both during training. It should be extended to support arbitrary machine learning models in the future. Args: run (wandb.Run): The run object to log to. models (Union[torch.nn.Module, Sequence[torch.nn.Module]]): A single model or a sequence of models to be monitored. criterion (Optional[torch.F]): The loss function being optimized (optional). log (Optional[Literal["gradients", "parameters", "all"]]): Specifies whether to log "gradients", "parameters", or "all". Set to None to disable logging. (default="gradients") log_freq (int): Frequency (in batches) to log gradients and parameters. (default=1000) idx (Optional[int]): Index used when tracking multiple models with `wandb.watch`. (default=None) log_graph (bool): Whether to log the model's computational graph. (default=False) Returns: wandb.Graph: The graph object, which will be populated after the first backward pass. Raises: ValueError: If `wandb.init` has not been called. TypeError: If any of the models are not instances of `torch.nn.Module`. TNWatching>Nallr parameterszrr>rr torchz;wandb.watch only works with pytorch, couldn't import torch.)requiredz5Expected a pytorch model (torch.nn.Module). Received rrgraph_)prefixr) graph_idx)rcontextfeaturewatchloggerinfo ValueError isinstancetuplelistrutil get_modulennModule TypeErrortype_global_watch_idx enumerate_torchadd_log_parameters_hookadd_log_gradients_hook hook_torchappend)r r rrrrrtellog_parameters log_gradientsrmodelgraphsr local_idx global_idxgraphr@I/home/ubuntu/.local/lib/python3.10/site-packages/wandb/sdk/wandb_watch.py_watchsZ (     rB2torch.nn.Module | Sequence[torch.nn.Module] | NonereturnNonecCsr|r2t|ttfs |f}|D]!}t|dst|dq|jD]}|j|q!t |dqdS|j dS)aRemove pytorch model topology, gradient and parameter hooks. Args: run (wandb.Run): The run object to log to. models (torch.nn.Module | Sequence[torch.nn.Module]): Optional list of pytorch models that have had watch called on them _wandb_hook_namesz model has not been watchedN) r(r)r*hasattrrtermwarnrFr3unhookdelattr unhook_all)r r r;namer@r@rA_unwatch{s     rM)Nr r NF)r r r rrrrrrrrrrr)N)r r r rCrDrE)__doc__ __future__rloggingcollections.abcrtypingrr ImportErrortyping_extensionsrlibrr getLoggerr%r1rBrMr@r@r@rAs0       b