cerebras.modelzoo.common.pytorch_utils

General purpose Pytorch Utilities

Functions

check_checkpoint_compatibility	Checks that the checkpoint is compatible with the current version of modelzoo.
get_checkpoints	Gather checkpoints in a model directory
is_mup_run	Check if the run is configured with muP hyperparameter settings
load_from_checkpoint_file	Loads state dict from checkpoint path and checks for version compatibilty.
setup_artifact_dir	Create a unique subdirectory for this run by generating a time stamp so that parallel runs using the same model_dir don't overwrite common files.
setup_logging	Configure default logging format
to_cpu	Move tensor from device to cpu
to_tensor	If the provided value is a Python int or float, it converts them into PyTorch Tensors of type int32 and float32 respectively.
visit_structure	Recursively traverse nested structure and return the items accepted by the selector.

Classes

BufferedShuffleDataset	Dataset shuffled from the original dataset.
IterableDatasetSampler	This sampler can be used with a multi-worker distributed dataloader.
RunConfigParamsValidator	Validate Run Configs
SampleGenerator	Iterator which returns multiple samples of a given input data.

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