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# Helpful Utilities
Below are a variety of utility functions that 🤗 Accelerate provides, broken down by use-case.
## Constants
Constants used throughout 🤗 Accelerate for reference
The following are constants used when utilizing [`Accelerator.save_state`]
`utils.MODEL_NAME`: `"pytorch_model"`
`utils.OPTIMIZER_NAME`: `"optimizer"`
`utils.RNG_STATE_NAME`: `"random_states"`
`utils.SCALER_NAME`: `"scaler.pt`
`utils.SCHEDULER_NAME`: `"scheduler`
The following are constants used when utilizing [`Accelerator.save_model`]
`utils.WEIGHTS_NAME`: `"pytorch_model.bin"`
`utils.SAFE_WEIGHTS_NAME`: `"model.safetensors"`
`utils.WEIGHTS_INDEX_NAME`: `"pytorch_model.bin.index.json"`
`utils.SAFE_WEIGHTS_INDEX_NAME`: `"model.safetensors.index.json"`
## Data Classes
These are basic dataclasses used throughout 🤗 Accelerate and they can be passed in as parameters.
[[autodoc]] utils.DistributedType
[[autodoc]] utils.DynamoBackend
[[autodoc]] utils.LoggerType
[[autodoc]] utils.PrecisionType
[[autodoc]] utils.FP8RecipeKwargs
[[autodoc]] utils.ProjectConfiguration
## Environmental Variables
These are environmental variables that can be enabled for different use cases
* `ACCELERATE_DEBUG_MODE` (`str`): Whether to run accelerate in debug mode. More info available [here](../usage_guides/debug.md).
## Plugins
These are plugins that can be passed to the [`Accelerator`] object. While they are defined elsewhere in the documentation,
for convience all of them are available to see here:
[[autodoc]] utils.DeepSpeedPlugin
[[autodoc]] utils.FullyShardedDataParallelPlugin
[[autodoc]] utils.GradientAccumulationPlugin
[[autodoc]] utils.MegatronLMPlugin
[[autodoc]] utils.TorchDynamoPlugin
## Data Manipulation and Operations
These include data operations that mimic the same `torch` ops but can be used on distributed processes.
[[autodoc]] utils.broadcast
[[autodoc]] utils.concatenate
[[autodoc]] utils.gather
[[autodoc]] utils.pad_across_processes
[[autodoc]] utils.reduce
[[autodoc]] utils.send_to_device
## Environment Checks
These functionalities check the state of the current working environment including information about the operating system itself, what it can support, and if particular dependencies are installed.
[[autodoc]] utils.is_bf16_available
[[autodoc]] utils.is_ipex_available
[[autodoc]] utils.is_mps_available
[[autodoc]] utils.is_npu_available
[[autodoc]] utils.is_torch_version
[[autodoc]] utils.is_tpu_available
[[autodoc]] utils.is_xpu_available
## Environment Manipulation
[[autodoc]] utils.patch_environment
[[autodoc]] utils.clear_environment
[[autodoc]] utils.write_basic_config
When setting up 🤗 Accelerate for the first time, rather than running `accelerate config` [~utils.write_basic_config] can be used as an alternative for quick configuration.
## Memory
[[autodoc]] utils.get_max_memory
[[autodoc]] utils.find_executable_batch_size
## Modeling
These utilities relate to interacting with PyTorch models
[[autodoc]] utils.extract_model_from_parallel
[[autodoc]] utils.get_max_layer_size
[[autodoc]] utils.offload_state_dict
## Parallel
These include general utilities that should be used when working in parallel.
[[autodoc]] utils.extract_model_from_parallel
[[autodoc]] utils.save
[[autodoc]] utils.wait_for_everyone
## Random
These utilities relate to setting and synchronizing of all the random states.
[[autodoc]] utils.set_seed
[[autodoc]] utils.synchronize_rng_state
[[autodoc]] utils.synchronize_rng_states
## PyTorch XLA
These include utilities that are useful while using PyTorch with XLA.
[[autodoc]] utils.install_xla
## Loading model weights
These include utilities that are useful to load checkpoints.
[[autodoc]] utils.load_checkpoint_in_model
## Quantization
These include utilities that are useful to quantize model.
[[autodoc]] utils.load_and_quantize_model
[[autodoc]] utils.BnbQuantizationConfig |