Below is a list of all the available commands 🤗 Accelerate with their parameters
Command:
accelerate config or accelerate-config
Launches a series of prompts to create and save a default_config.yml configuration file for your training system. Should
always be ran first on your machine.
Usage:
accelerate config [arguments]
Optional Arguments:
--config_file CONFIG_FILE (str) — The path to use to store the config file. Will default to a file named default_config.yaml in the cache location, which is the content
of the environment HF_HOME suffixed with ‘accelerate’, or if you don’t have such an environment variable, your cache directory
(~/.cache or the content of XDG_CACHE_HOME) suffixed with huggingface.-h, --help (bool) — Show a help message and exitCommand:
accelerate env or accelerate-env
Lists the contents of the passed 🤗 Accelerate configuration file. Should always be used when opening an issue on the GitHub repository.
Usage:
accelerate env [arguments]Optional Arguments:
--config_file CONFIG_FILE (str) — The path to use to store the config file. Will default to a file named default_config.yaml in the cache location, which is the content
of the environment HF_HOME suffixed with ‘accelerate’, or if you don’t have such an environment variable, your cache directory
(~/.cache or the content of XDG_CACHE_HOME) suffixed with huggingface.-h, --help (bool) — Show a help message and exitCommand:
accelerate launch or accelerate-launch
Launches a specified script on a distributed system with the right parameters.
Usage:
accelerate launch [arguments] {training_script} --{training_script-argument-1} --{training_script-argument-2} ...Positional Arguments:
{training_script} — The full path to the script to be launched in parallel--{training_script-argument-1} — Arguments of the training scriptOptional Arguments:
-h, --help (bool) — Show a help message and exit--config_file CONFIG_FILE (str)— The config file to use for the default values in the launching script.--cpu (bool) — Whether or not to force the training on the CPU.--mixed_precision {no,fp16,bf16} (str) — Whether or not to use mixed precision training. Choose between FP16 and BF16 (bfloat16) training. BF16 training is only supported on
Nvidia Ampere GPUs and PyTorch 1.10 or later.--multi_gpu (bool, defaults to False) — Whether or not this should launch a distributed GPU training.-m, --module (bool) — Change each process to interpret the launch script as a Python module, executing with the same behavior as ‘python -m’.--no_python (bool) — Skip prepending the training script with ‘python’ - just execute it directly. Useful when the script is not a Python script.The rest of these arguments are configured through accelerate config and are read in from the specified --config_file (or default configuration) for their
values. They can also be passed in manually.
Machine Configuration Arguments:
The following arguments are useful for customization of worker machines
--machine_rank MACHINE_RANK (int) — The rank of the machine on which this script is launched.--num_machines NUM_MACHINES (int) — The total number of machines used in this training.--num_processes NUM_PROCESSES (int) — The total number of processes to be launched in parallel.--main_process_ip MAIN_PROCESS_IP (str) — The IP address of the machine of rank 0.--main_process_port MAIN_PROCESS_PORT (int) — The port to use to communicate with the machine of rank 0.--num_cpu_threads_per_process NUM_CPU_THREADS_PER_PROCESS (int) — The number of CPU threads per process. Can be tuned for optimal performance.DeepSpeed Arguments:
The following arguments are only useful when use_deepspeed is passed:
--use_deepspeed (bool) — Whether to use deepspeed.--deepspeed_config_file DEEPSPEED_CONFIG_FILE (str) — DeepSpeed config file.--zero_stage ZERO_STAGE (str) — DeepSpeed’s ZeRO optimization stage--offload_optimizer_device OFFLOAD_OPTIMIZER_DEVICE (str) — Decides where (none|cpu|nvme) to offload optimizer states--offload_param_device OFFLOAD_PARAM_DEVICE (str) — Decides where (none|cpu|nvme) to offload parameters--gradient_accumulation_steps GRADIENT_ACCUMULATION_STEPS (int) — Number of gradient_accumulation_steps used in your training script--gradient_clipping GRADIENT_CLIPPING (float) — gradient clipping value used in your training script
The following arguments are related to using ZeRO Stage-3--zero3_init_flag ZERO3_INIT_FLAG (bool) — Decides Whether (true|false) to enable deepspeed.zero.Init for constructing massive models--zero3_save_16bit_model ZERO3_SAVE_16BIT_MODEL (bool) — Decides Whether (true|false) to save 16-bit model weights when using ZeRO Stage-3Fully Sharded Data Parallelism Arguments:
The following arguments are only useful when use_fdsp is passed:
--use_fsdp (bool) — Whether to use fsdp.--offload_params OFFLOAD_PARAMS (bool) — Decides Whether (true|false) to offload parameters and gradients to CPU.--min_num_params MIN_NUM_PARAMS (int) — FSDP’s minimum number of parameters for Default Auto Wrapping.--sharding_strategy SHARDING_STRATEGY (str) — FSDP’s Sharding Strategy.TPU Arguments:
The following arguments are only useful when tpu is passed:
--tpu (bool) - Whether or not this should launch a TPU training.--main_training_function MAIN_TRAINING_FUNCTION (str) — The name of the main function to be executed in your script.AWS SageMaker Arguments:
The following arguments are only useful when training in SageMaker
--aws_access_key_id AWS_ACCESS_KEY_ID (str) — The AWS_ACCESS_KEY_ID used to launch the Amazon SageMaker training job--aws_secret_access_key AWS_SECRET_ACCESS_KEY (str) — The AWS_SECRET_ACCESS_KEY used to launch the Amazon SageMaker training jobaccelerate test or accelerate-test
Runs accelerate/test_utils/test_script.py to verify that 🤗 Accelerate has been properly configured on your system and runs.
Usage:
accelerate test [arguments]Optional Arguments:
--config_file CONFIG_FILE (str) — The path to use to store the config file. Will default to a file named default_config.yaml in the cache location, which is the content
of the environment HF_HOME suffixed with ‘accelerate’, or if you don’t have such an environment variable, your cache directory
(~/.cache or the content of XDG_CACHE_HOME) suffixed with huggingface.-h, --help (bool) — Show a help message and exit