mirror of
https://github.com/hpcaitech/ColossalAI.git
synced 2025-09-13 21:22:49 +00:00
[shardformer] update transformers (#5583)
* flash_attention forward upgrade * llama_model_forward * remove useless comment * update the requirements.txt * add the transformers version requirements * remove the LATEST VERSION try * [shardformer] update bloom model (#5518) * update bloom model * remove the version restriction * [shardformer] update_falcon (#5520) * [shardformer] update mistral model (#5511) * [shardformer] update gpt2 (#5502) * [shardformer] update gptj model (#5503) * [shardformer] update opt (#5522) * [shardformer] update t5 model (#5524) * [shardformer] update whisper model (#5529) * [shardformer] update vit model (#5530) * update vit model * remove the output_hidden_states * [shardformer] fix llama modeling * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [zero] support multiple (partial) backward passes (#5596) * [zero] support multiple (partial) backward passes * [misc] update requirements * [zero] support multiple (partial) backward passes (#5596) * [zero] support multiple (partial) backward passes * [misc] update requirements * fix conflicts * [doc] fix ColossalMoE readme (#5599) * fix readme * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * merge with main * merge with main * llama_model_forward * remove useless comment * remove the LATEST VERSION try * [shardformer] update bloom model (#5518) * update bloom model * remove the version restriction * [shardformer] update mistral model (#5511) * [shardformer] update opt (#5522) * [shardformer] update whisper model (#5529) * [shardformer] fix llama modeling * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [hotfix] Fix examples no pad token & auto parallel codegen bug; (#5606) * fix no pad token bug * fixed some auto parallel codegen bug, but might not run on torch 2.1 --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [shardformer] fix pipeline grad ckpt (#5620) * [shardformer] fix pipeline grad ckpt * [shardformer] fix whisper (#5628) * [test] fix llama model test * fix the opt upgrade (#5634) * [shardformer] fix attn replacement (#5636) * [shardformer] update flashattention replacement (#5637) * update transformers update transformers fix fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [test] fix llama test (#5638) * [gemini] fix buffer cast (#5639) * Fix shardformer upgrade (#5640) * fix llama model * fix the mistral * fix the shardformer model * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [shardformer]support pipeline parallelism for mistral. (#5642) * [shardformer] fix attn replacement (#5636) * [shardformer] update flashattention replacement (#5637) * update transformers update transformers fix fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Feature] Support LLaMA-3 CPT and ST (#5619) * support LLaMA-3 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Run pre-commit --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [exampe] update llama example (#5626) * [plugin] support dp inside for hybriad parallel * [example] update llama benchmark * [example] update llama benchmark * [example] update llama readme * [example] update llama readme * [example] llama3 (#5631) * release llama3 * [release] llama3 * [release] llama3 * [release] llama3 * [release] llama3 * [test] fix llama test (#5638) * [gemini] fix buffer cast (#5639) * support pp for mistral * fix * fix fix fix * fix --------- Co-authored-by: Hongxin Liu <lhx0217@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Tong Li <tong.li352711588@gmail.com> Co-authored-by: binmakeswell <binmakeswell@gmail.com> --------- Co-authored-by: Hongxin Liu <lhx0217@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Camille Zhong <44392324+Camille7777@users.noreply.github.com> Co-authored-by: Edenzzzz <wenxuan.tan@wisc.edu> Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: flybird11111 <1829166702@qq.com> Co-authored-by: Tong Li <tong.li352711588@gmail.com> Co-authored-by: binmakeswell <binmakeswell@gmail.com>
This commit is contained in:
Wang Binluo
GitHub
@@ -148,11 +148,9 @@ class GPTJPipelineForwards:
|
||||
head_mask = self.get_head_mask(head_mask, self.config.n_layer)
|
||||
|
||||
# position id to be assigned not just for the first stage for attn input
|
||||
if position_ids is not None:
|
||||
position_ids = position_ids.view(-1, seq_length)
|
||||
else:
|
||||
if position_ids is None:
|
||||
position_ids = torch.arange(0, seq_length, dtype=torch.long, device=device)
|
||||
position_ids = position_ids.unsqueeze(0).view(-1, input_shape[-1])
|
||||
position_ids = position_ids.unsqueeze(0)
|
||||
if stage_manager.is_first_stage():
|
||||
if inputs_embeds is None:
|
||||
inputs_embeds = self.wte(input_ids)
|
||||
@@ -201,21 +199,15 @@ class GPTJPipelineForwards:
|
||||
all_hidden_states = all_hidden_states + (hidden_states,)
|
||||
|
||||
if self.gradient_checkpointing and self.training:
|
||||
|
||||
def create_custom_forward(module):
|
||||
def custom_forward(*inputs):
|
||||
# None for past_key_value
|
||||
return module(*inputs, use_cache, output_attentions)
|
||||
|
||||
return custom_forward
|
||||
|
||||
outputs = torch.utils.checkpoint.checkpoint(
|
||||
create_custom_forward(block),
|
||||
outputs = self._gradient_checkpointing_func(
|
||||
block.__call__,
|
||||
hidden_states,
|
||||
None,
|
||||
attention_mask,
|
||||
position_ids,
|
||||
head_mask[i],
|
||||
use_cache,
|
||||
output_attentions,
|
||||
)
|
||||
else:
|
||||
outputs = block(
|
||||
@@ -627,7 +619,9 @@ def get_gptj_flash_attention_forward():
|
||||
value = torch.cat((past_value, value), dim=-2)
|
||||
|
||||
if use_cache is True:
|
||||
present = (key, value)
|
||||
# Note that this cast is quite ugly, but is not implemented before ROPE as the original codebase keeps the key in float32 all along the computation.
|
||||
# Reference: https://github.com/kingoflolz/mesh-transformer-jax/blob/f8315e3003033b23f21d78361b288953064e0e76/mesh_transformer/layers.py#L128
|
||||
present = (key.to(hidden_states.dtype), value)
|
||||
else:
|
||||
present = None
|
||||
|
||||
|
||||
Reference in New Issue
Block a user