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[hotfix] Add layer norm gradients all-reduce for sequence parallel (#4926)

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* [hotfix] Add layer norm gradients all-reduce for sequence parallel. (#4915)

* Add layer norm gradients all-reduce for sequence parallel.

* skip pipeline inference test

* [hotfix] fixing polices of sequence parallel (#4922)

* Add layer norm gradients all-reduce for sequence parallel.

* fix parameter passing when calling get_autopolicy

---------

Co-authored-by: littsk <1214689160@qq.com>

* Hotfix/add grad all reduce for sequence parallel (#4927)

* Add layer norm gradients all-reduce for sequence parallel.


* fix parameter passing when calling get_autopolicy

* fix bug using wrong variables

---------

Co-authored-by: littsk <1214689160@qq.com>

* fix policy initialization

* fix bloom and chatglm policices

* polish code of handling layernorm

* fix moe module

* polish code of class initializing

---------

Co-authored-by: Zhongkai Zhao <kanezz620@gmail.com>
This commit is contained in:
littsk
2023-11-03 13:32:43 +08:00
committed by GitHub
parent d99b2c961a
commit 1a3315e336
30 changed files with 1120 additions and 552 deletions
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78
colossalai/shardformer/policies/t5.py
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@@ -11,6 +11,7 @@ from colossalai.shardformer.layer import (
FusedRMSNorm,
Linear1D_Col,
Linear1D_Row,
RMSNorm,
VocabParallelEmbedding1D,
)
from colossalai.shardformer.policies.base_policy import ModulePolicyDescription
@@ -58,6 +59,11 @@ class T5BasePolicy(Policy):
policy = {}
if self.shard_config.enable_fused_normalization:
norm_cls = FusedRMSNorm
else:
norm_cls = RMSNorm
if self.shard_config.enable_sequence_parallelism:
self.shard_config.enable_sequence_parallelism = False
warnings.warn("T5 dosen't support sequence parallelism now, will ignore the sequence parallelism flag.")
@@ -169,38 +175,37 @@ class T5BasePolicy(Policy):
)
# optimization configuration
if self.shard_config.enable_fused_normalization:
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(
suffix="layer_norm",
target_module=FusedRMSNorm,
),
policy=policy,
target_key=T5LayerFF,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(
suffix="layer_norm",
target_module=FusedRMSNorm,
),
policy=policy,
target_key=T5LayerFF,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(suffix="layer_norm", target_module=FusedRMSNorm),
policy=policy,
target_key=T5LayerSelfAttention,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(suffix="layer_norm", target_module=FusedRMSNorm),
policy=policy,
target_key=T5LayerCrossAttention,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(suffix="final_layer_norm", target_module=FusedRMSNorm),
policy=policy,
target_key=T5Stack,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(
suffix="layer_norm",
target_module=norm_cls,
),
policy=policy,
target_key=T5LayerFF,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(
suffix="layer_norm",
target_module=norm_cls,
),
policy=policy,
target_key=T5LayerFF,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(suffix="layer_norm", target_module=norm_cls),
policy=policy,
target_key=T5LayerSelfAttention,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(suffix="layer_norm", target_module=norm_cls),
policy=policy,
target_key=T5LayerCrossAttention,
)
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(suffix="final_layer_norm", target_module=norm_cls),
policy=policy,
target_key=T5Stack,
)
# use flash attention
if self.shard_config.enable_flash_attention:
@@ -363,9 +368,6 @@ class T5BasePolicy(Policy):
class T5ModelPolicy(T5BasePolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
from transformers import T5Model
@@ -402,9 +404,6 @@ class T5ModelPolicy(T5BasePolicy):
class T5ForConditionalGenerationPolicy(T5BasePolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
from transformers import T5ForConditionalGeneration
@@ -466,9 +465,6 @@ class T5ForConditionalGenerationPolicy(T5BasePolicy):
class T5EncoderPolicy(T5BasePolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
from transformers import T5EncoderModel