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[Shardformer] Merge flash attention branch to pipeline branch (#4362)
* [shardformer] supported flash attention test dependency (#4158) * [shardformer] fix flash attention utils test (#4180) * [shardformer] opt support flash attention (#4163) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] add performance benchmark of shardformer (#4175) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] benchmark fix * [shardformer] benchmark fix * [shardformer] llama support flash attention (#4185) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] llama support flash attention * [shardformer] llama support flash attention * [shardformer] Move the import statement for xformer outside the forward function. * [shardformer] gpt2 support flash attention. (#4191) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] gpt2 support flash attention * [shardformer] gpt2 support flash attention * [shardformer] gpt2 support flash attention * [shardformer] bloom support flash attention (#4188) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] bloom suport flash attention * [shardformer] add assert to sequence length * [shardformer] fix * [shardformer] fix * [shardformer] fix * [shardformer] bert support flash attention. (#4206) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] bert support flash attention * [shardformer] t5 support flash attention. (#4216) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] t5 support flash attention * [shardformer] t5 support flash attention * fix typo * fix typo * fix typo * fix typo * fix typo * fix typo * [shardformer] support 'paddedcausal' type of attention mask in Coloattention. (#4215) * added padded causal attn mask type for ColoAttention * [shardformer]t5 flash attention fix (#4239) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] t5 flash attention fix * [shardformer] update gpt2 to use coloattention. (#4234) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] update gpt2 to use coloattention * [shardformer] update gpt2 to use coloattention * [shardformer] update gpt2 to use coloattention * [shardformer] update gpt2 to use coloattention * [shardformer] update gpt2 * [shardformer] update opt and llama to use coloattention. (#4226) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * update opt to use coloattention * [shardformer]update opt to use coloattention * [shardformer]update opt to use coloattention * [shardformer]update opt to use coloattention * [shardformer]update opt to use coloattention * [shardformer]update opt to use coloattention * [shardformer]update opt to use coloattention * [shardformer]update opt * [shardformer] shardformer support jit fused operator. (#4236) * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] opt support flash attention * [shardformer] move to modeling * [shardformer] move to modeling * [shardformer] bloom support jit fused operator * [shardformer] bloom support jit fused operator * [shardformer] bloom support jit fused operator * [shardformer] t5 support jit fused operator * [shardformer] t5 support jit fused operator * [shardformer] t5 support jit fused operator * [shardformer] add roadmap of flash attention * [shardformer] add roadmap of flash attention * [shardformer] add roadmap of flash attention * [shardformer] add type hint to 'self' param of forward * [shardformer] merge feature/shardformer-models branch to feature/flash-attention-shardformer branch. (#4290) * Feature/vit support (#4182) * [shardformer] added tests * [shardformer] vit test finish and support * fix attention dropout * [shardformer] support SAM (#4231) * 1.support sam 2.add fused qkv for nn.Linear * update utils support set element in list * overtwrite SamVisionAttention foward to use DropoutForParallelInput * remove unused code * [shardformer] support whisper (#4212) * support whisper * fix bug in vocabembedding * support downstream model of whisper * update readme * Feature/chatglm (#4240) * [shardformer] added tests * [shardformer] vit test finish and support * [shardformer] chatglm ready * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] chatglm shard without mlp sharding * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] fix chatglm configuration with pre-commit --------- Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> * [shardformer] whisper support flash attention (#4301) * Feature/vit support (#4182) * [shardformer] added tests * [shardformer] vit test finish and support * fix attention dropout * [shardformer] support SAM (#4231) * 1.support sam 2.add fused qkv for nn.Linear * update utils support set element in list * overtwrite SamVisionAttention foward to use DropoutForParallelInput * remove unused code * [shardformer] support whisper (#4212) * support whisper * fix bug in vocabembedding * support downstream model of whisper * update readme * Feature/chatglm (#4240) * [shardformer] added tests * [shardformer] vit test finish and support * [shardformer] chatglm ready * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] chatglm shard without mlp sharding * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] fix chatglm configuration with pre-commit * [shardformer] whisper support flash attention * [shardformer] whisper support flash attention * [shardformer]whisper support jit operator --------- Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> * [shardformer] sam support flash attention (#4316) * Feature/vit support (#4182) * [shardformer] added tests * [shardformer] vit test finish and support * fix attention dropout * [shardformer] support SAM (#4231) * 1.support sam 2.add fused qkv for nn.Linear * update utils support set element in list * overtwrite SamVisionAttention foward to use DropoutForParallelInput * remove unused code * [shardformer] support whisper (#4212) * support whisper * fix bug in vocabembedding * support downstream model of whisper * update readme * Feature/chatglm (#4240) * [shardformer] added tests * [shardformer] vit test finish and support * [shardformer] chatglm ready * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] chatglm shard without mlp sharding * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] fix chatglm configuration with pre-commit * [shardformer] sam support flash attention --------- Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> * [shardformer] merge blip2/chatglm (#4321) * Feature/vit support (#4182) * [shardformer] added tests * [shardformer] vit test finish and support * fix attention dropout * [shardformer] support SAM (#4231) * 1.support sam 2.add fused qkv for nn.Linear * update utils support set element in list * overtwrite SamVisionAttention foward to use DropoutForParallelInput * remove unused code * [shardformer] support whisper (#4212) * support whisper * fix bug in vocabembedding * support downstream model of whisper * update readme * Feature/chatglm (#4240) * [shardformer] added tests * [shardformer] vit test finish and support * [shardformer] chatglm ready * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] chatglm shard without mlp sharding * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] fix chatglm configuration with pre-commit * [shardformer] added tests * [shardformer] vit test finish and support * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] support ChatGLMForConditionalGeneration & add fusedlayernorm for vit * [shardformer] support Blip2 (#4243) * support base blip2 * add support for downstream blip2 model * update readme * add forward injection * skip not compatible models test * fix test for gemini and low_level_zero_pugin --------- Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> Co-authored-by: klhhhhh <1412841649@qq.com> * [shardformer] blip2 support flash attention and jit operator (#4325) * Feature/vit support (#4182) * [shardformer] added tests * [shardformer] vit test finish and support * fix attention dropout * [shardformer] support SAM (#4231) * 1.support sam 2.add fused qkv for nn.Linear * update utils support set element in list * overtwrite SamVisionAttention foward to use DropoutForParallelInput * remove unused code * [shardformer] support whisper (#4212) * support whisper * fix bug in vocabembedding * support downstream model of whisper * update readme * Feature/chatglm (#4240) * [shardformer] added tests * [shardformer] vit test finish and support * [shardformer] chatglm ready * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] chatglm shard without mlp sharding * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] fix chatglm configuration with pre-commit * [shardformer] added tests * [shardformer] vit test finish and support * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] support ChatGLMForConditionalGeneration & add fusedlayernorm for vit * [shardformer] support Blip2 (#4243) * support base blip2 * add support for downstream blip2 model * update readme * add forward injection * skip not compatible models test * fix test for gemini and low_level_zero_pugin * [shardformer] blip2 support flash attention and jit operator * [shardformer] blip2 support flash attention and jit operator * [shardformer] blip2 support flash attention and jit operator --------- Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> Co-authored-by: klhhhhh <1412841649@qq.com> * [shardformer] chatglm support flash attention and jit operator (#4330) * Feature/vit support (#4182) * [shardformer] added tests * [shardformer] vit test finish and support * fix attention dropout * [shardformer] support SAM (#4231) * 1.support sam 2.add fused qkv for nn.Linear * update utils support set element in list * overtwrite SamVisionAttention foward to use DropoutForParallelInput * remove unused code * [shardformer] support whisper (#4212) * support whisper * fix bug in vocabembedding * support downstream model of whisper * update readme * Feature/chatglm (#4240) * [shardformer] added tests * [shardformer] vit test finish and support * [shardformer] chatglm ready * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] chatglm shard without mlp sharding * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] fix chatglm configuration with pre-commit * [shardformer] added tests * [shardformer] vit test finish and support * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] support ChatGLMForConditionalGeneration & add fusedlayernorm for vit * [shardformer] support Blip2 (#4243) * support base blip2 * add support for downstream blip2 model * update readme * add forward injection * skip not compatible models test * fix test for gemini and low_level_zero_pugin * [shardformer] chatglm support flash attention and jit operator * [shardformer] chatglm support flash attention and jit operator * [shardformer] chatglm support flash attention and jit operator * [shardformer] chatglm support flash attention and jit operator --------- Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> Co-authored-by: klhhhhh <1412841649@qq.com> * [shardformer] vit support flash attention and jit operator (#4334) * Feature/vit support (#4182) * [shardformer] added tests * [shardformer] vit test finish and support * fix attention dropout * [shardformer] support SAM (#4231) * 1.support sam 2.add fused qkv for nn.Linear * update utils support set element in list * overtwrite SamVisionAttention foward to use DropoutForParallelInput * remove unused code * [shardformer] support whisper (#4212) * support whisper * fix bug in vocabembedding * support downstream model of whisper * update readme * Feature/chatglm (#4240) * [shardformer] added tests * [shardformer] vit test finish and support * [shardformer] chatglm ready * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] chatglm shard without mlp sharding * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] fix chatglm configuration with pre-commit * [shardformer] added tests * [shardformer] vit test finish and support * import chatglm * [shardformer] add test kit in model zoo for chatglm * [sharformer] add first version of policy of chatglm * [shardformer] polish chatglm code * [shardformer] polish code * [shardformer] support chatglm without layernorm * [shardformer] delete some file * [shardformer] ChatGLM support layernorm sharding * [shardformer] register without auto policy * [shardformer] pre-commit check files * [shardformer] support ChatGLMForConditionalGeneration & add fusedlayernorm for vit * [shardformer] support Blip2 (#4243) * support base blip2 * add support for downstream blip2 model * update readme * add forward injection * skip not compatible models test * fix test for gemini and low_level_zero_pugin * [shardformer] vit support flash attention and jit operator * [shardformer] vit support flash attention and jit operator --------- Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> Co-authored-by: klhhhhh <1412841649@qq.com> * [pipeline] merge flash attention branch * [pipeline] merge flash attention branch * [pipeline] merge flash attention branch * [pipeline] fix conflict * [pipeline] fix conflict * Merge branch 'feature/pipeline' into feature/pipeline * Merge branch 'feature/pipeline' into feature/pipeline * Merge branch 'feature/pipeline' into feature/pipeline * activate checks * activate checks * activate checks * activate checks * activate checks * activate checks * activate checks * activate checks * fix flash attention tests * gemini ignore whisper * fix vit * fix xformers import handle --------- Co-authored-by: Frank Lee <somerlee.9@gmail.com> Co-authored-by: Kun Lin <81014421+klhhhhh@users.noreply.github.com> Co-authored-by: FoolPlayer <45593998+FoolPlayer@users.noreply.github.com> Co-authored-by: klhhhhh <1412841649@qq.com>
This commit is contained in:
flybird1111
Hongxin Liu
@@ -1,5 +1,6 @@
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import math
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import warnings
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from typing import Any, Dict, List, Optional, Tuple
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from typing import Dict, List, Optional, Tuple
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import torch
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from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
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@@ -962,3 +963,138 @@ class BertPipelineForwards:
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else:
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hidden_states = outputs.get('hidden_states')
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return {'hidden_states': hidden_states}
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def get_bert_flash_attention_forward():
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try:
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from xformers.ops import memory_efficient_attention as me_attention
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except:
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raise ImportError("Error: xformers module is not installed. Please install it to use flash attention.")
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from transformers.models.bert.modeling_bert import BertAttention
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def forward(
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self: BertAttention,
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hidden_states: torch.Tensor,
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attention_mask: Optional[torch.FloatTensor] = None,
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head_mask: Optional[torch.FloatTensor] = None,
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encoder_hidden_states: Optional[torch.FloatTensor] = None,
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encoder_attention_mask: Optional[torch.FloatTensor] = None,
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past_key_value: Optional[Tuple[Tuple[torch.FloatTensor]]] = None,
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output_attentions: Optional[bool] = False,
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) -> Tuple[torch.Tensor]:
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mixed_query_layer = self.query(hidden_states)
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# If this is instantiated as a cross-attention module, the keys
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# and values come from an encoder; the attention mask needs to be
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# such that the encoder's padding tokens are not attended to.
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is_cross_attention = encoder_hidden_states is not None
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if is_cross_attention and past_key_value is not None:
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# reuse k,v, cross_attentions
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key_layer = past_key_value[0]
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value_layer = past_key_value[1]
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attention_mask = encoder_attention_mask
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elif is_cross_attention:
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key_layer = self.transpose_for_scores(self.key(encoder_hidden_states))
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value_layer = self.transpose_for_scores(self.value(encoder_hidden_states))
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attention_mask = encoder_attention_mask
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elif past_key_value is not None:
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key_layer = self.transpose_for_scores(self.key(hidden_states))
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value_layer = self.transpose_for_scores(self.value(hidden_states))
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key_layer = torch.cat([past_key_value[0], key_layer], dim=2)
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value_layer = torch.cat([past_key_value[1], value_layer], dim=2)
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else:
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key_layer = self.transpose_for_scores(self.key(hidden_states))
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value_layer = self.transpose_for_scores(self.value(hidden_states))
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query_layer = self.transpose_for_scores(mixed_query_layer)
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use_cache = past_key_value is not None
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if self.is_decoder:
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# if cross_attention save Tuple(torch.Tensor, torch.Tensor) of all cross attention key/value_states.
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# Further calls to cross_attention layer can then reuse all cross-attention
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# key/value_states (first "if" case)
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# if uni-directional self-attention (decoder) save Tuple(torch.Tensor, torch.Tensor) of
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# all previous decoder key/value_states. Further calls to uni-directional self-attention
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# can concat previous decoder key/value_states to current projected key/value_states (third "elif" case)
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# if encoder bi-directional self-attention `past_key_value` is always `None`
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past_key_value = (key_layer, value_layer)
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final_attention_mask = None
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if self.position_embedding_type == "relative_key" or self.position_embedding_type == "relative_key_query":
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query_length, key_length = query_layer.shape[2], key_layer.shape[2]
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if use_cache:
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position_ids_l = torch.tensor(key_length - 1, dtype=torch.long, device=hidden_states.device).view(-1, 1)
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else:
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position_ids_l = torch.arange(query_length, dtype=torch.long, device=hidden_states.device).view(-1, 1)
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position_ids_r = torch.arange(key_length, dtype=torch.long, device=hidden_states.device).view(1, -1)
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distance = position_ids_l - position_ids_r
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positional_embedding = self.distance_embedding(distance + self.max_position_embeddings - 1)
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positional_embedding = positional_embedding.to(dtype=query_layer.dtype) # fp16 compatibility
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if self.position_embedding_type == "relative_key":
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relative_position_scores = torch.einsum("bhld,lrd->bhlr", query_layer, positional_embedding)
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final_attention_mask = relative_position_scores
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elif self.position_embedding_type == "relative_key_query":
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relative_position_scores_query = torch.einsum("bhld,lrd->bhlr", query_layer, positional_embedding)
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relative_position_scores_key = torch.einsum("bhrd,lrd->bhlr", key_layer, positional_embedding)
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final_attention_mask = relative_position_scores_query + relative_position_scores_key
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scale = 1 / math.sqrt(self.attention_head_size)
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if attention_mask is not None:
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if final_attention_mask != None:
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final_attention_mask = final_attention_mask * scale + attention_mask
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else:
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final_attention_mask = attention_mask
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batch_size, src_len = query_layer.size()[0], query_layer.size()[2]
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tgt_len = key_layer.size()[2]
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final_attention_mask = final_attention_mask.expand(batch_size, self.num_attention_heads, src_len, tgt_len)
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query_layer = query_layer.permute(0, 2, 1, 3).contiguous()
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key_layer = key_layer.permute(0, 2, 1, 3).contiguous()
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value_layer = value_layer.permute(0, 2, 1, 3).contiguous()
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context_layer = me_attention(query_layer,
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key_layer,
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value_layer,
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attn_bias=final_attention_mask,
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p=self.dropout.p,
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scale=scale)
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new_context_layer_shape = context_layer.size()[:-2] + (self.all_head_size,)
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context_layer = context_layer.view(new_context_layer_shape)
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outputs = (context_layer, None)
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if self.is_decoder:
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outputs = outputs + (past_key_value,)
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return outputs
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return forward
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def get_jit_fused_bert_self_output_forward():
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from transformers.models.bert.modeling_bert import BertSelfOutput
|
||||
|
||||
def forward(self: BertSelfOutput, hidden_states: torch.Tensor, input_tensor: torch.Tensor) -> torch.Tensor:
|
||||
hidden_states = self.dense(hidden_states)
|
||||
hidden_states = self.dropout_add(hidden_states, input_tensor, self.dropout.p, self.dropout.training)
|
||||
hidden_states = self.LayerNorm(hidden_states)
|
||||
return hidden_states
|
||||
|
||||
return forward
|
||||
|
||||
|
||||
def get_jit_fused_bert_output_forward():
|
||||
|
||||
from transformers.models.bert.modeling_bert import BertOutput
|
||||
|
||||
def forward(self: BertOutput, hidden_states: torch.Tensor, input_tensor: torch.Tensor) -> torch.Tensor:
|
||||
hidden_states = self.dense(hidden_states)
|
||||
hidden_states = self.dropout_add(hidden_states, input_tensor, self.dropout.p, self.dropout.training)
|
||||
hidden_states = self.LayerNorm(hidden_states)
|
||||
return hidden_states
|
||||
|
||||
return forward
|
||||
|
||||
Reference in New Issue
Block a user