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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
@@ -20,7 +20,7 @@ def data_gen():
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# token_type_ids = tokenized_input['token_type_ids']
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input_ids = torch.tensor([[101, 7592, 1010, 2026, 3899, 2003, 10140, 102]], dtype=torch.int64)
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token_type_ids = torch.tensor([[0, 0, 0, 0, 0, 0, 0, 0]], dtype=torch.int64)
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attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1, 1, 1]], dtype=torch.int64)
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attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1, 1, 0]], dtype=torch.int64)
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return dict(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask)
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@@ -69,19 +69,21 @@ def data_gen_for_mcq():
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# data['labels'] = torch.tensor([0], dtype=torch.int64)
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input_ids = torch.tensor([[[
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101, 1999, 3304, 1010, 10733, 2366, 1999, 5337, 10906, 1010, 2107, 2004, 2012, 1037, 4825, 1010, 2003, 3591,
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4895, 14540, 6610, 2094, 1012, 102, 2009, 2003, 8828, 2007, 1037, 9292, 1998, 1037, 5442, 1012, 102
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4895, 14540, 6610, 2094, 1012, 102, 2009, 2003, 8828, 2007, 1037, 9292, 1998, 1037, 5442, 1012, 102, 102
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],
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[
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101, 1999, 3304, 1010, 10733, 2366, 1999, 5337, 10906, 1010, 2107, 2004, 2012, 1037,
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4825, 1010, 2003, 3591, 4895, 14540, 6610, 2094, 1012, 102, 2009, 2003, 8828, 2096,
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2218, 1999, 1996, 2192, 1012, 102, 0
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2218, 1999, 1996, 2192, 1012, 102, 0, 0
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]]])
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token_type_ids = torch.tensor(
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[[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0]]])
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[[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
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0]]])
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attention_mask = torch.tensor(
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[[[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0]]])
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[[[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
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0]]])
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labels = torch.tensor([0], dtype=torch.int64)
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return dict(input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask, labels=labels)
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@@ -38,6 +38,7 @@ output_transform_fn = lambda x: x
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loss_fn_blip2_model = lambda x: x.loss
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config = transformers.Blip2Config()
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config.vision_config.patch_size = 14
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config.text_config.num_hidden_layers = 1
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config.qformer_config.num_hidden_layers = 1
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config.vision_config.num_hidden_layers = 1
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@@ -16,8 +16,8 @@ def data_gen():
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# tokenized_input = tokenizer(input, return_tensors='pt')
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# input_ids = tokenized_input['input_ids']
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# attention_mask = tokenized_input['attention_mask']
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input_ids = torch.tensor([[59414, 15, 2670, 35433, 632, 207595]], dtype=torch.int64)
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attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1]], dtype=torch.int64)
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input_ids = torch.tensor([[59414, 15, 2670, 35433, 632, 207595, 632, 207595]], dtype=torch.int64)
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attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1, 1, 1]], dtype=torch.int64)
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return dict(input_ids=input_ids, attention_mask=attention_mask)
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@@ -33,7 +33,7 @@ def data_gen_for_token_classification():
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# token classification data gen
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# `labels` is the type not the token id for token classification, 0 or 1
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data = data_gen()
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data['labels'] = torch.tensor([[0, 0, 0, 0, 0, 0]], dtype=torch.int64)
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data['labels'] = torch.tensor([[0, 0, 0, 0, 0, 0, 0, 0]], dtype=torch.int64)
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return data
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@@ -53,8 +53,8 @@ def data_gen_for_question_answering():
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# inputs = tokenizer(question, text, return_tensors="pt")
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input_ids = torch.tensor(
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[[57647, 1620, 23967, 620, 107373, 34, 91514, 620, 107373, 1620, 267, 35378, 48946, 18161]], dtype=torch.int64)
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attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], dtype=torch.int64)
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[[57647, 1620, 23967, 620, 107373, 34, 91514, 620, 107373, 1620, 267, 35378, 48946, 18161, 48946, 18161]], dtype=torch.int64)
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attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], dtype=torch.int64)
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start_positions = torch.tensor([1], dtype=torch.int64)
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end_positions = torch.tensor([10], dtype=torch.int64)
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return dict(input_ids=input_ids,
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@@ -6,7 +6,6 @@ from colossalai.shardformer.modeling.chatglm2_6b.modeling_chatglm import ChatGLM
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from ..registry import ModelAttribute, model_zoo
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# ================================
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# Register single-sentence ChatGLM
|
||||
# ================================
|
||||
|
||||
@@ -1,58 +0,0 @@
|
||||
from transformers import PretrainedConfig
|
||||
|
||||
|
||||
class ChatGLMConfig(PretrainedConfig):
|
||||
model_type = "chatglm"
|
||||
|
||||
def __init__(self,
|
||||
num_layers=28,
|
||||
padded_vocab_size=65024,
|
||||
hidden_size=4096,
|
||||
ffn_hidden_size=13696,
|
||||
kv_channels=128,
|
||||
num_attention_heads=32,
|
||||
seq_length=2048,
|
||||
hidden_dropout=0.0,
|
||||
attention_dropout=0.0,
|
||||
layernorm_epsilon=1e-5,
|
||||
rmsnorm=True,
|
||||
apply_residual_connection_post_layernorm=False,
|
||||
post_layer_norm=True,
|
||||
add_bias_linear=False,
|
||||
add_qkv_bias=False,
|
||||
bias_dropout_fusion=True,
|
||||
multi_query_attention=False,
|
||||
multi_query_group_num=1,
|
||||
apply_query_key_layer_scaling=True,
|
||||
attention_softmax_in_fp32=True,
|
||||
fp32_residual_connection=False,
|
||||
quantization_bit=0,
|
||||
pre_seq_len=None,
|
||||
prefix_projection=False,
|
||||
**kwargs):
|
||||
self.num_layers = num_layers
|
||||
self.vocab_size = padded_vocab_size
|
||||
self.padded_vocab_size = padded_vocab_size
|
||||
self.hidden_size = hidden_size
|
||||
self.ffn_hidden_size = ffn_hidden_size
|
||||
self.kv_channels = kv_channels
|
||||
self.num_attention_heads = num_attention_heads
|
||||
self.seq_length = seq_length
|
||||
self.hidden_dropout = hidden_dropout
|
||||
self.attention_dropout = attention_dropout
|
||||
self.layernorm_epsilon = layernorm_epsilon
|
||||
self.rmsnorm = rmsnorm
|
||||
self.apply_residual_connection_post_layernorm = apply_residual_connection_post_layernorm
|
||||
self.post_layer_norm = post_layer_norm
|
||||
self.add_bias_linear = add_bias_linear
|
||||
self.add_qkv_bias = add_qkv_bias
|
||||
self.bias_dropout_fusion = bias_dropout_fusion
|
||||
self.multi_query_attention = multi_query_attention
|
||||
self.multi_query_group_num = multi_query_group_num
|
||||
self.apply_query_key_layer_scaling = apply_query_key_layer_scaling
|
||||
self.attention_softmax_in_fp32 = attention_softmax_in_fp32
|
||||
self.fp32_residual_connection = fp32_residual_connection
|
||||
self.quantization_bit = quantization_bit
|
||||
self.pre_seq_len = pre_seq_len
|
||||
self.prefix_projection = prefix_projection
|
||||
super().__init__(**kwargs)
|
||||
File diff suppressed because it is too large
Load Diff
@@ -18,8 +18,8 @@ def data_gen():
|
||||
# tokenized_input = tokenizer(input, return_tensors='pt')
|
||||
# input_ids = tokenized_input['input_ids']
|
||||
# attention_mask = tokenized_input['attention_mask']
|
||||
input_ids = torch.tensor([[15496, 11, 616, 3290, 318, 13779]], dtype=torch.int64)
|
||||
attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1]], dtype=torch.int64)
|
||||
input_ids = torch.tensor([[15496, 11, 616, 3290, 318, 13779, 318, 13779]], dtype=torch.int64)
|
||||
attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1, 1, 1]], dtype=torch.int64)
|
||||
return dict(input_ids=input_ids, attention_mask=attention_mask)
|
||||
|
||||
|
||||
@@ -46,7 +46,7 @@ def data_gen_for_token_classification():
|
||||
# token classification data gen
|
||||
# `labels` is the type not the token id for token classification, 0 or 1
|
||||
data = data_gen()
|
||||
data['labels'] = torch.tensor([[0, 0, 0, 0, 0, 1]], dtype=torch.int64)
|
||||
data['labels'] = torch.tensor([[0, 0, 0, 0, 0, 0, 0, 1]], dtype=torch.int64)
|
||||
return data
|
||||
|
||||
|
||||
|
||||
@@ -16,8 +16,9 @@ def data_gen_for_encoder_only():
|
||||
# config = T5Config(decoder_start_token_id=0)
|
||||
# tokenizer = T5Tokenizer.from_pretrained("t5-small")
|
||||
# input_ids = tokenizer("translate English to German: The house is wonderful.", return_tensors="pt").input_ids
|
||||
input_ids = torch.Tensor([[13959, 1566, 12, 2968, 10, 37, 629, 19, 1627, 5, 1]]).long()
|
||||
return dict(input_ids=input_ids)
|
||||
input_ids = torch.Tensor([[13959, 1566, 12, 2968, 10, 37, 629, 19, 1627, 5, 1, 12]]).long()
|
||||
attention_mask = torch.Tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0]]).long()
|
||||
return dict(input_ids=input_ids, attention_mask=attention_mask)
|
||||
|
||||
|
||||
def data_gen_for_conditional_generation():
|
||||
@@ -25,17 +26,16 @@ def data_gen_for_conditional_generation():
|
||||
#
|
||||
# labels = tokenizer("Das Haus ist wunderbar.", return_tensors="pt").input_ids
|
||||
data = data_gen_for_encoder_only()
|
||||
labels = torch.Tensor([[644, 4598, 229, 19250, 5, 1]]).long()
|
||||
labels = torch.Tensor([[644, 4598, 229, 19250, 5, 1, 644, 4598, 229, 19250, 5, 1]]).long()
|
||||
data['labels'] = labels
|
||||
return data
|
||||
|
||||
|
||||
def data_gen_for_t5_model():
|
||||
# decoder_inputs_ids is obtained with the following code
|
||||
#
|
||||
# decoder_input_ids = model._shift_right(input_ids)
|
||||
data = data_gen_for_encoder_only()
|
||||
decoder_input_ids = torch.Tensor([[0, 13959, 1566, 12, 2968, 10, 37, 629, 19, 1627, 5]]).long()
|
||||
decoder_input_ids = torch.Tensor([[0, 13959, 1566, 12, 2968, 10, 37, 629, 19, 1627, 5, 5]]).long()
|
||||
data['decoder_input_ids'] = decoder_input_ids
|
||||
return data
|
||||
|
||||
|
||||
@@ -76,14 +76,14 @@ model_zoo.register(name='transformers_whisper',
|
||||
loss_fn=loss_fn,
|
||||
model_attribute=ModelAttribute(has_control_flow=True))
|
||||
|
||||
model_zoo.register(name='transformers_whisperForConditionalGeneration',
|
||||
model_zoo.register(name='transformers_whisper_for_conditional_generation',
|
||||
model_fn=lambda: transformers.WhisperForConditionalGeneration(config),
|
||||
data_gen_fn=data_gen_for_conditional_generation,
|
||||
output_transform_fn=output_transform_fn,
|
||||
loss_fn=loss_fn_attr,
|
||||
model_attribute=ModelAttribute(has_control_flow=True))
|
||||
|
||||
model_zoo.register(name='transformers_whisperWhisperForAudioClassification',
|
||||
model_zoo.register(name='transformers_whisper_for_audio_classification',
|
||||
model_fn=lambda: transformers.WhisperForAudioClassification(config),
|
||||
data_gen_fn=data_gen_for_audio_classification,
|
||||
output_transform_fn=output_transform_fn,
|
||||
|
||||
Reference in New Issue
Block a user