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[shardformer] fix pipeline forward error if custom layer distribution is used (#5189)

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* Use self.[distribute_layers|get_stage_index] to exploit custom layer distribution

* Change static methods for t5 layer distribution to member functions

* Change static methods for whisper layer distribution to member functions

* Replace whisper policy usage with self one

* Fix test case to use non-static layer distribution methods

* fix: fix typo

---------

Co-authored-by: Wenhao Chen <cwher@outlook.com>
This commit is contained in:
Insu Jang
2024-03-27 01:57:00 -04:00
committed by GitHub
parent e6707a6e8d
commit 00525f7772
18 changed files with 136 additions and 106 deletions
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67
colossalai/shardformer/policies/bert.py
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@@ -84,17 +84,26 @@ class BertPolicy(Policy):
SubModuleReplacementDescription(
suffix="attention.self.query",
target_module=col_nn.Linear1D_Col,
kwargs={"seq_parallel": use_sequence_parallel, "overlap": overlap},
kwargs={
"seq_parallel": use_sequence_parallel,
"overlap": overlap,
},
),
SubModuleReplacementDescription(
suffix="attention.self.key",
target_module=col_nn.Linear1D_Col,
kwargs={"seq_parallel": use_sequence_parallel, "overlap": overlap},
kwargs={
"seq_parallel": use_sequence_parallel,
"overlap": overlap,
},
),
SubModuleReplacementDescription(
suffix="attention.self.value",
target_module=col_nn.Linear1D_Col,
kwargs={"seq_parallel": use_sequence_parallel, "overlap": overlap},
kwargs={
"seq_parallel": use_sequence_parallel,
"overlap": overlap,
},
),
SubModuleReplacementDescription(
suffix="attention.self.dropout",
@@ -112,7 +121,10 @@ class BertPolicy(Policy):
SubModuleReplacementDescription(
suffix="intermediate.dense",
target_module=col_nn.Linear1D_Col,
kwargs={"seq_parallel": use_sequence_parallel, "overlap": overlap},
kwargs={
"seq_parallel": use_sequence_parallel,
"overlap": overlap,
},
),
SubModuleReplacementDescription(
suffix="output.dense",
@@ -214,7 +226,9 @@ class BertPolicy(Policy):
if self.shard_config.enable_tensor_parallelism:
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(
suffix="decoder", target_module=col_nn.Linear1D_Col, kwargs={"gather_output": True}
suffix="decoder",
target_module=col_nn.Linear1D_Col,
kwargs={"gather_output": True},
),
policy=base_policy,
target_key=BertLMPredictionHead,
@@ -241,7 +255,9 @@ class BertPolicy(Policy):
"_load_from_state_dict": col_nn.ParallelModule._load_from_state_dict,
}
self.append_or_create_method_replacement(
description=method_replacement, policy=base_policy, target_key=BertLMPredictionHead
description=method_replacement,
policy=base_policy,
target_key=BertLMPredictionHead,
)
return base_policy
@@ -264,24 +280,32 @@ class BertPolicy(Policy):
if stage_manager.is_interleave:
layers_per_stage = self.distribute_layers(
len(module.encoder.layer), stage_manager.num_stages * stage_manager.num_model_chunks
len(module.encoder.layer),
stage_manager.num_stages * stage_manager.num_model_chunks,
)
stage_manager.stage_indices = Policy.get_stage_index(
stage_manager.stage_indices = self.get_stage_index(
layers_per_stage,
stage_manager.stage,
num_model_chunks=stage_manager.num_model_chunks,
num_stages=stage_manager.num_stages,
)
method_replacement = {
"forward": partial(new_forward, stage_manager=stage_manager, shard_config=self.shard_config)
"forward": partial(
new_forward,
stage_manager=stage_manager,
shard_config=self.shard_config,
)
}
else:
layers_per_stage = Policy.distribute_layers(len(module.encoder.layer), stage_manager.num_stages)
stage_index = Policy.get_stage_index(layers_per_stage, stage_manager.stage)
layers_per_stage = self.distribute_layers(len(module.encoder.layer), stage_manager.num_stages)
stage_index = self.get_stage_index(layers_per_stage, stage_manager.stage)
method_replacement = {
"forward": partial(
new_forward, stage_manager=stage_manager, stage_index=stage_index, shard_config=self.shard_config
new_forward,
stage_manager=stage_manager,
stage_index=stage_index,
shard_config=self.shard_config,
)
}
@@ -301,9 +325,10 @@ class BertPolicy(Policy):
if stage_manager.is_interleave:
assert stage_manager.num_model_chunks is not None
layers_per_stage = self.distribute_layers(
len(module.encoder.layer), stage_manager.num_stages * stage_manager.num_model_chunks
len(module.encoder.layer),
stage_manager.num_stages * stage_manager.num_model_chunks,
)
stage_indices = Policy.get_stage_index(
stage_indices = self.get_stage_index(
layers_per_stage,
stage_manager.stage,
num_model_chunks=stage_manager.num_model_chunks,
@@ -320,7 +345,7 @@ class BertPolicy(Policy):
layers_per_stage = self.distribute_layers(len(module.encoder.layer), stage_manager.num_stages)
if stage_manager.is_first_stage():
held_layers.append(module.embeddings)
start_idx, end_idx = Policy.get_stage_index(layers_per_stage, stage_manager.stage)
start_idx, end_idx = self.get_stage_index(layers_per_stage, stage_manager.stage)
held_layers.extend(module.encoder.layer[start_idx:end_idx])
if stage_manager.is_last_stage():
held_layers.append(module.pooler)
@@ -336,7 +361,9 @@ class BertModelPolicy(BertPolicy):
if self.pipeline_stage_manager:
self.set_pipeline_forward(
model_cls=BertModel, new_forward=BertPipelineForwards.bert_model_forward, policy=policy
model_cls=BertModel,
new_forward=BertPipelineForwards.bert_model_forward,
policy=policy,
)
return policy
@@ -399,7 +426,9 @@ class BertLMHeadModelPolicy(BertPolicy):
if self.pipeline_stage_manager:
self.set_pipeline_forward(
model_cls=BertLMHeadModel, new_forward=BertPipelineForwards.bert_lm_head_model_forward, policy=policy
model_cls=BertLMHeadModel,
new_forward=BertPipelineForwards.bert_lm_head_model_forward,
policy=policy,
)
return policy
@@ -437,7 +466,9 @@ class BertForMaskedLMPolicy(BertPolicy):
if self.pipeline_stage_manager:
self.set_pipeline_forward(
model_cls=BertForMaskedLM, new_forward=BertPipelineForwards.bert_for_masked_lm_forward, policy=policy
model_cls=BertForMaskedLM,
new_forward=BertPipelineForwards.bert_for_masked_lm_forward,
policy=policy,
)
return policy