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""" Example python script to generate a YAML config file which can be used to run a training with nanotron. Refer to "examples" section in the `/README.md` for more information. |
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Usage: |
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``` |
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python config_tiny_mistral.py |
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``` |
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""" |
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import os |
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from dataclasses import dataclass |
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from typing import Optional |
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from nanotron.config import ( |
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CheckpointsArgs, |
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Config, |
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DataArgs, |
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GeneralArgs, |
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LoggingArgs, |
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LRSchedulerArgs, |
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ModelArgs, |
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OptimizerArgs, |
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ParallelismArgs, |
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PretrainDatasetsArgs, |
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RandomInit, |
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TokenizerArgs, |
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TokensArgs, |
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) |
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from nanotron.logging import human_format |
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from config_mistral import MistralConfig, get_num_params |
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MODEL_CONFIG = MistralConfig( |
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attn_pdrop=0.0, |
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bos_token_id=1, |
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eos_token_id=2, |
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hidden_act="silu", |
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hidden_size=4096, |
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initializer_range=0.02, |
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intermediate_size=14336, |
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max_position_embeddings=32768, |
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num_attention_heads=32, |
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num_hidden_layers=32, |
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num_key_value_heads=8, |
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pretraining_tp=1, |
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rms_norm_eps=1e-05, |
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rope_theta=10000.0, |
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sliding_window_size=4096, |
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tie_word_embeddings=False, |
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use_cache=True, |
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vocab_size=32000, |
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) |
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num_params = human_format(get_num_params(MODEL_CONFIG)).replace(".", "p") |
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print(f"Model has {num_params} parameters") |
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PARALLELISM = ParallelismArgs( |
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dp=2, |
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pp=2, |
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tp=2, |
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pp_engine="1f1b", |
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tp_mode="REDUCE_SCATTER", |
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tp_linear_async_communication=True, |
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recompute_granularity="selective", |
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) |
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CONFIG = Config( |
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general=GeneralArgs(project="mistralai", run="Mistral-7B-v0.1", seed=42, step=0), |
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checkpoints=None, |
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parallelism=PARALLELISM, |
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model=ModelArgs(init_method=RandomInit(std=0.025), model_config=MODEL_CONFIG), |
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tokenizer=TokenizerArgs("mistralai/Mistral-7B-v0.1"), |
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optimizer=None, |
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logging=None, |
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tokens=None, |
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data=None, |
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profiler=None, |
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lighteval=None, |
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) |
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if __name__ == "__main__": |
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file_path = os.path.abspath(__file__) |
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file_path = file_path.replace(".py", ".yaml") |
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config.save_as_yaml(file_path) |
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