mirror of https://github.com/hpcaitech/ColossalAI
97 lines
4.7 KiB
Python
97 lines
4.7 KiB
Python
from transformers.models.gpt2.modeling_gpt2 import GPT2Block, GPT2Model
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import colossalai.shardformer.layer as col_nn
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from .basepolicy import ModulePolicyDescription, Policy, SubModuleReplacementDescription
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class GPT2Policy(Policy):
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def preprocess(self):
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# reshape the embedding layer
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r"""
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Reshape the Embedding layer to make the embedding dimension divisible by world_size
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"""
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vocab_size = self.model.config.vocab_size
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world_size = self.shard_config.tensor_parallel_size
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if vocab_size % world_size != 0:
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new_vocab_size = vocab_size + world_size - vocab_size % world_size
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self.model.resize_token_embeddings(new_vocab_size)
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return self.model
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def module_policy(self):
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return {
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GPT2Model:
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ModulePolicyDescription(attribute_replacement={},
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param_replacement=[],
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sub_module_replacement=[
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SubModuleReplacementDescription(
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suffix="wte",
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target_module=col_nn.VocabParallelEmbedding1D,
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),
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]),
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GPT2Block:
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ModulePolicyDescription(attribute_replacement={
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"attn.embed_dim": self.model.config.hidden_size // self.shard_config.tensor_parallel_size,
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"attn.split_size": self.model.config.hidden_size // self.shard_config.tensor_parallel_size,
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"attn.num_heads": self.model.config.num_attention_heads // self.shard_config.tensor_parallel_size,
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},
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param_replacement=[],
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sub_module_replacement=[
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SubModuleReplacementDescription(
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suffix="attn.c_attn",
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target_module=col_nn.LinearConv1D_Col,
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kwargs={
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"n_cast": 3,
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},
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),
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SubModuleReplacementDescription(
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suffix="attn.c_proj",
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target_module=col_nn.LinearConv1D_Row,
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kwargs={
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"n_cast": 1,
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},
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),
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SubModuleReplacementDescription(
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suffix="mlp.c_fc",
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target_module=col_nn.LinearConv1D_Col,
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kwargs={
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"n_cast": 1,
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},
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),
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SubModuleReplacementDescription(
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suffix="mlp.c_proj",
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target_module=col_nn.LinearConv1D_Row,
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kwargs={
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"n_cast": 1,
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},
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),
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SubModuleReplacementDescription(
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suffix="attn.attn_dropout",
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target_module=col_nn.Dropout1D,
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),
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SubModuleReplacementDescription(
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suffix="attn.resid_dropout",
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target_module=col_nn.Dropout1D,
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),
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SubModuleReplacementDescription(
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suffix="mlp.dropout",
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target_module=col_nn.Dropout1D,
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),
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])
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}
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def new_model_class(self):
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return self.model
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def postprocess(self):
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return self.model
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# GPT2Model
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class GPT2ModelPolicy(GPT2Policy):
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def __init__(self) -> None:
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super().__init__()
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