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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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119
colossalai/shardformer/policies/whisper.py
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@@ -52,6 +52,11 @@ class WhisperPolicy(Policy):
policy = {}
if self.shard_config.enable_fused_normalization:
norm_cls = col_nn.FusedLayerNorm
else:
norm_cls = col_nn.LayerNorm
if self.shard_config.enable_sequence_parallelism:
self.shard_config.enable_sequence_parallelism = False
warnings.warn(
@@ -161,62 +166,61 @@ class WhisperPolicy(Policy):
)
# optimization configuration
if self.shard_config.enable_fused_normalization:
# Handle encoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="self_attn_layer_norm",
target_module=col_nn.FusedLayerNorm,
),
SubModuleReplacementDescription(
suffix="final_layer_norm",
target_module=col_nn.FusedLayerNorm,
),
],
policy=policy,
target_key=WhisperEncoderLayer,
)
# Handle encoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="self_attn_layer_norm",
target_module=norm_cls,
),
SubModuleReplacementDescription(
suffix="final_layer_norm",
target_module=norm_cls,
),
],
policy=policy,
target_key=WhisperEncoderLayer,
)
# Handle decoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="self_attn_layer_norm",
target_module=col_nn.FusedLayerNorm,
),
SubModuleReplacementDescription(
suffix="final_layer_norm",
target_module=col_nn.FusedLayerNorm,
),
],
policy=policy,
target_key=WhisperDecoderLayer,
)
# Handle decoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="self_attn_layer_norm",
target_module=norm_cls,
),
SubModuleReplacementDescription(
suffix="final_layer_norm",
target_module=norm_cls,
),
],
policy=policy,
target_key=WhisperDecoderLayer,
)
# handle encoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="layer_norm",
target_module=col_nn.FusedLayerNorm,
)
],
policy=policy,
target_key=WhisperEncoder,
)
# handle encoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="layer_norm",
target_module=norm_cls,
)
],
policy=policy,
target_key=WhisperEncoder,
)
# handle decoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="layer_norm",
target_module=col_nn.FusedLayerNorm,
)
],
policy=policy,
target_key=WhisperDecoder,
)
# handle decoder layer
self.append_or_create_submodule_replacement(
description=[
SubModuleReplacementDescription(
suffix="layer_norm",
target_module=norm_cls,
)
],
policy=policy,
target_key=WhisperDecoder,
)
# enable flash attention
if self.shard_config.enable_flash_attention:
@@ -416,9 +420,6 @@ class WhisperPolicy(Policy):
# WhisperModel
class WhisperModelPolicy(WhisperPolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
from transformers import WhisperModel
@@ -441,9 +442,6 @@ class WhisperModelPolicy(WhisperPolicy):
# WhisperForConditionalGeneration
class WhisperForConditionalGenerationPolicy(WhisperPolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
from transformers import WhisperForConditionalGeneration
@@ -502,9 +500,6 @@ class WhisperForConditionalGenerationPolicy(WhisperPolicy):
# WhisperForAudioClassification
class WhisperForAudioClassificationPolicy(WhisperPolicy):
def __init__(self) -> None:
super().__init__()
def preprocess(self):
return self.model