autotune?
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6ed6ab8c03
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@ -313,6 +313,9 @@ class Hyperparameters:
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scheduler: str = ""
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scheduler_type: str = "" # deprecated
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scheduler_params: dict = field(default_factory=lambda: {}) # to pass through deepspeed config
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autotune: bool = False
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autotune_params: dict = field(default_factory=lambda: {}) # to pass through deepspeed config
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torch_optimizer: bool = False
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torch_scheduler: bool = False
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@ -354,6 +357,17 @@ class DeepSpeed:
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if cfg.trainer.weight_dtype.lower() == "float16":
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cfg.trainer.amp = False
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autotune_params = cfg.hyperparameters.autotune_params
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if "enabled" not in autotune_params:
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autotune_params['enabled'] = True
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if "results_dir" not in autotune_params:
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autotune_params['results_dir'] = str( cfg.relpath / "autotune" / "results" )
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if "exps_dir" not in autotune_params:
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autotune_params['exps_dir'] = str( cfg.relpath / "autotune" / "exps_" )
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ds_cfg = {
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"train_micro_batch_size_per_gpu": cfg.hyperparameters.batch_size,
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"gradient_accumulation_steps": cfg.hyperparameters.gradient_accumulation_steps,
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@ -374,8 +388,9 @@ class DeepSpeed:
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"enabled": cfg.trainer.weight_dtype.lower() == "bfloat16",
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},
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"amp": {
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"enabled": cfg.trainer.amp,
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},
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"enabled": cfg.trainer.amp,
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},
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"autotuning": autotune_params if cfg.hyperparameters.autotune else None,
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"compression_training": {
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"weight_quantization": {
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"shared_parameters":{
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