[Sharderformer] Support zbv in Sharderformer Policy (#6150)

* [feat] Sharderformer support zbv

* [feat] support chatglm2, command, deepseek for zbv

* [feat] support zbv in shardformer policy:
falcon,gptj,mistral,opt,qwen2,t5, vit, whisper

* [feat] support GPT2FusedLinearConv1D

* [feat] support GPT2FusedLinear (without tp)

* [fix] debug FusedConvLinear

* [shardfromer] support gpt2 policy for zbv, support GPT2FusedLinearConv
Col and Row.

* [Shardformer] support FusedLinear1D base for zbv

* [shardformer] support zbv in FusedLinear1D base, Col, Row

* [shardformer] support zbv in blip2 and sam policy

* [shardformer] fix bug incorrect number of gradients; add fusedLinear
base testcase;

* [fix] fix incorrect number of gradients ;

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* [Shardformer] add en doc for zbv;

* [fix] fix typo in Model compatibility table

* [fix] fix API Reference typo

* [Shardformer] add zh-Han doc for zbv

* [fix] fix Linear name; update en & zh doc

* [fix] fix shardformer doc import err

* [fix] fix shardconfig import in doc

* [fix] fix shardformer doc

* [fix] fix shardconfig doc

* [fix] fix config

* [fix] remove shardconfig

* [fix] fix doc

* [feat] add zbv doc string

* [fix] rm doc

* [fix] fix doc

* [fix] empty zbv doc

* [fix] ifx torch version

* [fix] fix torch version

* [fix] fix torch versions

* [fix] fix torch versions

* [fix] fix pyramid versions

* [fix] fix pyramid, zope version

* [fix] try fix workflow

* [fix] try import ShardConfig in yml

* [fix] fix workflow

* [fix] fix workflow

* [fix] fix workflow

* [fix] fix workflow

* [fix] fix ci

* [fix] fix zbv doc

* [fix] fix param for qkv linear, gpt2fused linear; fix requirments;

* [fix] fix policy use fused_linear

* [fix] fix weight grad none, err caused by  weight ptr change

* [fix] fix comm in WeightGradStore

* [fix] fix WeightGradStore pop param

* [fix] remove useless param in doc; fix gpt2 qkv test;

* [shardformer] simplify execute_w_pass_grad_accum;

* [fix] rm useless comments

* [shardformer] simplify execute_w_pass_grad_accum & execute_w_pass

* [shardformer] Run meaningful doc test

* [shadformer] fix doc test cmd;

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
duanjunwen
2025-01-02 10:22:26 +08:00
committed by GitHub
parent af06d162cf
commit a9bedc7a43
27 changed files with 3511 additions and 316 deletions

View File

@@ -10,6 +10,7 @@ from colossalai.shardformer.layer import (
LayerNorm,
Linear1D_Col,
Linear1D_Row,
LinearWithGradAccum,
PaddingEmbedding,
PaddingLMHead,
VocabParallelEmbedding1D,
@@ -107,6 +108,8 @@ class CommandPolicy(Policy):
target_key=CohereModel,
)
use_zbv = self.pipeline_stage_manager is not None and self.pipeline_stage_manager.use_zbv
if self.shard_config.enable_tensor_parallelism:
assert (
num_q_heads % tp_size == 0
@@ -128,41 +131,137 @@ class CommandPolicy(Policy):
SubModuleReplacementDescription(
suffix="self_attn.q_proj",
target_module=Linear1D_Col,
kwargs=dict(seq_parallel_mode=sp_mode, fp8_communication=self.shard_config.fp8_communication),
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="self_attn.k_proj",
target_module=Linear1D_Col,
kwargs=dict(seq_parallel_mode=sp_mode, fp8_communication=self.shard_config.fp8_communication),
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="self_attn.v_proj",
target_module=Linear1D_Col,
kwargs=dict(seq_parallel_mode=sp_mode, fp8_communication=self.shard_config.fp8_communication),
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="self_attn.o_proj",
target_module=Linear1D_Row,
kwargs=dict(seq_parallel_mode=sp_mode, fp8_communication=self.shard_config.fp8_communication),
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="mlp.gate_proj",
target_module=Linear1D_Col,
kwargs=dict(seq_parallel_mode=sp_mode, fp8_communication=self.shard_config.fp8_communication),
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="mlp.up_proj",
target_module=Linear1D_Col,
kwargs=dict(seq_parallel_mode=sp_mode, fp8_communication=self.shard_config.fp8_communication),
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="mlp.down_proj",
target_module=Linear1D_Row,
kwargs=dict(seq_parallel_mode=sp_mode, fp8_communication=self.shard_config.fp8_communication),
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
],
)
elif use_zbv:
policy[CohereDecoderLayer] = ModulePolicyDescription(
attribute_replacement=decoder_attribute_replacement,
sub_module_replacement=[
SubModuleReplacementDescription(
suffix="self_attn.q_proj",
target_module=LinearWithGradAccum,
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="self_attn.k_proj",
target_module=LinearWithGradAccum,
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="self_attn.v_proj",
target_module=LinearWithGradAccum,
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="self_attn.o_proj",
target_module=LinearWithGradAccum,
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="mlp.gate_proj",
target_module=LinearWithGradAccum,
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="mlp.up_proj",
target_module=LinearWithGradAccum,
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
SubModuleReplacementDescription(
suffix="mlp.down_proj",
target_module=LinearWithGradAccum,
kwargs=dict(
seq_parallel_mode=sp_mode,
fp8_communication=self.shard_config.fp8_communication,
use_zbv=use_zbv,
),
),
],
)
if embedding_cls is not None:
self.append_or_create_submodule_replacement(
description=SubModuleReplacementDescription(
@@ -258,7 +357,9 @@ class CommandPolicy(Policy):
held_layers.append(module.embed_tokens)
for start_idx, end_idx in stage_indices:
held_layers.extend(module.layers[start_idx:end_idx])
if stage_manager.is_last_stage(ignore_chunk=True):
if (stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True)) or (
not stage_manager.use_zbv and stage_manager.is_last_stage(ignore_chunk=True)
):
held_layers.append(module.norm)
else:
@@ -351,8 +452,14 @@ class CommandForCausalLMPolicy(CommandPolicy):
"""Get pipeline layers for current stage."""
stage_manager = self.pipeline_stage_manager
held_layers = super().get_held_layers()
if stage_manager.is_last_stage(ignore_chunk=True):
held_layers.append(self.model.lm_head)
if stage_manager.is_interleave:
if (stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True)) or (
not stage_manager.use_zbv and stage_manager.is_last_stage(ignore_chunk=True)
):
held_layers.append(self.model.lm_head)
else:
if stage_manager.is_last_stage(ignore_chunk=True):
held_layers.append(self.model.lm_head)
return held_layers
def get_shared_params(self) -> List[Dict[int, Tensor]]: