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# Copyright (c) Meta Platforms, Inc. and affiliates. | |
# This software may be used and distributed according to the terms of the Llama 2 Community License Agreement. | |
def fsdp_auto_wrap_policy(model, transformer_layer_name): | |
import functools | |
import os | |
from accelerate import FullyShardedDataParallelPlugin | |
from transformers.models.t5.modeling_t5 import T5Block | |
from torch.distributed.fsdp.wrap import _or_policy, lambda_auto_wrap_policy, transformer_auto_wrap_policy | |
from peft.tuners import PrefixEncoder, PromptEmbedding, PromptEncoder | |
def lambda_policy_fn(module): | |
if ( | |
len(list(module.named_children())) == 0 | |
and getattr(module, "weight", None) is not None | |
and module.weight.requires_grad | |
): | |
return True | |
return False | |
lambda_policy = functools.partial(lambda_auto_wrap_policy, lambda_fn=lambda_policy_fn) | |
transformer_wrap_policy = functools.partial( | |
transformer_auto_wrap_policy, | |
transformer_layer_cls=( | |
PrefixEncoder, | |
PromptEncoder, | |
PromptEmbedding, | |
transformer_layer_name, | |
# FullyShardedDataParallelPlugin.get_module_class_from_name( | |
# model, transformer_layer_name | |
# ), | |
), | |
) | |
auto_wrap_policy = functools.partial(_or_policy, policies=[lambda_policy, transformer_wrap_policy]) | |
return auto_wrap_policy |