operator name
stringclasses
180 values
used in model
stringclasses
155 values
args
stringlengths
19
5.24k
aten.embedding_dense_backward.default
HuggingFace/MegatronBertForCausalLM
((T([2, 128, 1024], f16), T([2, 128], i64), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/XGLMForCausalLM
((T([2, 128, 1024], f16), T([2, 128], i64), 256008, 1, False), {})
aten.embedding_dense_backward.default
HuggingFace/MegatronBertForCausalLM
((T([2, 128, 1024], f16), T([2, 128], i64), 29056, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/AlbertForMaskedLM
((T([2, 512, 128], f16), T([2, 512], i64), 30000, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/AlbertForQuestionAnswering
((T([2, 512, 128], f16), T([2, 512], i64), 30000, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/AlbertForMaskedLM
((T([2, 512, 128], f16), T([2, 512], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/AlbertForQuestionAnswering
((T([2, 512, 128], f16), T([2, 512], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
TorchBench/attention_is_all_you_need_pytorch
((T([256, 31, 512], f16), T([256, 31], i64, stride=(1, 256)), 9521, 1, False), {})
aten.embedding_dense_backward.default
TorchBench/attention_is_all_you_need_pytorch
((T([256, 33, 512], f16), T([256, 33], i64, stride=(1, 256)), 9521, 1, False), {})
aten.embedding_dense_backward.default
HuggingFace/MobileBertForQuestionAnswering
((T([32, 128, 128], f16), T([32, 128], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/MobileBertForQuestionAnswering
((T([32, 128, 512], f16), T([32, 128], i64), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/DistilBertForQuestionAnswering
((T([32, 128, 768], f16), T([32, 128], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/BartForCausalLM
((T([4, 1024, 1024], f16), T([4, 1024], i64), 1026, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/BartForCausalLM
((T([4, 1024, 1024], f16), T([4, 1024], i64), 50265, 1, False), {})
aten.embedding_dense_backward.default
HuggingFace/GPT2ForSequenceClassification
((T([4, 1024, 768], f16), T([4, 1024], i64), 50257, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/PegasusForConditionalGeneration
((T([4, 128, 1024], f16), T([4, 128], i64), 50265, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/OPTForCausalLM
((T([4, 128, 768], f16), T([4, 128], i64), 2050, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/RobertaForCausalLM
((T([4, 128, 768], f16), T([4, 128], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/OPTForCausalLM
((T([4, 128, 768], f16), T([4, 128], i64), 50272, 1, False), {})
aten.embedding_dense_backward.default
HuggingFace/RobertaForCausalLM
((T([4, 128, 768], f16), T([4, 128], i64), 512, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/RobertaForCausalLM
((T([4, 128, 768], f16), T([4, 128], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_Bart
((T([4, 512, 768], f16), T([4, 512], i64), 1026, -1, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_Bert
((T([4, 512, 768], f16), T([4, 512], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_GPT2
((T([4, 512, 768], f16), T([4, 512], i64), 50257, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/DebertaForMaskedLM
((T([4, 512, 768], f16), T([4, 512], i64), 50265, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/DebertaForQuestionAnswering
((T([4, 512, 768], f16), T([4, 512], i64), 50265, 0, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_Bart
((T([4, 512, 768], f16), T([4, 512], i64), 50265, 1, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_Bert
((T([4, 512, 768], f16), T([4, 512], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/XLNetLMHeadModel
((T([512, 4, 1024], f16), T([512, 4], i64), 32000, -1, False), {})
aten.embedding_dense_backward.default
TorchBench/fastNLP_Bert
((T([6, 476, 768], f16), T([6, 476], i64), 2, -1, False), {})
aten.embedding_dense_backward.default
TorchBench/fastNLP_Bert
((T([6, 476, 768], f16), T([6, 476], i64), 21128, 0, False), {})
aten.embedding_dense_backward.default
TorchBench/fastNLP_Bert
((T([6, 476, 768], f16), T([6, 476], i64, stride=(0, 1)), 512, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/Speech2Text2ForCausalLM
((T([64, 128, 256], f16), T([64, 128], i64), 10000, 1, False), {})
aten.embedding_dense_backward.default
HuggingFace/BlenderbotSmallForCausalLM
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aten.embedding_dense_backward.default
HuggingFace/BlenderbotSmallForConditionalGeneration
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aten.embedding_dense_backward.default
HuggingFace/BertForMaskedLM
((T([64, 128, 768], f16), T([64, 128], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/BertForQuestionAnswering
((T([64, 128, 768], f16), T([64, 128], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/RobertaForQuestionAnswering
((T([64, 128, 768], f16), T([64, 128], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/RobertaForQuestionAnswering
((T([64, 128, 768], f16), T([64, 128], i64), 512, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/BertForMaskedLM
((T([64, 128, 768], f16), T([64, 128], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/BertForQuestionAnswering
((T([64, 128, 768], f16), T([64, 128], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/RobertaForQuestionAnswering
((T([64, 128, 768], f16), T([64, 128], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/ElectraForQuestionAnswering
((T([64, 512, 128], f16), T([64, 512], i64), 30522, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/ElectraForQuestionAnswering
((T([64, 512, 128], f16), T([64, 512], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/MBartForConditionalGeneration
((T([8, 128, 1024], f16), T([8, 128], i64), 1026, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/MegatronBertForQuestionAnswering
((T([8, 128, 1024], f16), T([8, 128], i64), 2, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/MegatronBertForQuestionAnswering
((T([8, 128, 1024], f16), T([8, 128], i64), 29056, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/PegasusForCausalLM
((T([8, 128, 1024], f16), T([8, 128], i64), 50265, 0, False), {})
aten.embedding_dense_backward.default
HuggingFace/MBartForConditionalGeneration
((T([8, 128, 1024], f16), T([8, 128], i64), 50265, 1, False), {})
aten.embedding_dense_backward.default
HuggingFace/TrOCRForCausalLM
((T([8, 128, 1024], f16), T([8, 128], i64), 50265, 1, False), {})
aten.embedding_dense_backward.default
HuggingFace/TrOCRForCausalLM
((T([8, 128, 1024], f16), T([8, 128], i64), 514, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/PLBartForConditionalGeneration
((T([8, 128, 768], f16), T([8, 128], i64), 1026, -1, False), {})
aten.embedding_dense_backward.default
HuggingFace/PLBartForConditionalGeneration
((T([8, 128, 768], f16), T([8, 128], i64), 50005, 1, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_Albert
((T([8, 512, 128], f16), T([8, 512], i64), 30000, 0, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_Albert
((T([8, 512, 128], f16), T([8, 512], i64, stride=(0, 1)), 2, -1, False), {})
aten.embedding_dense_backward.default
TorchBench/hf_DistilBert
((T([8, 512, 768], f16), T([8, 512], i64), 30522, 0, False), {})
aten.eq.Scalar
TorchBench/vision_maskrcnn
((T([0], i64), 0), {})
aten.eq.Scalar
TorchBench/vision_maskrcnn
((T([0], i64), 1), {})
aten.eq.Scalar
TorchBench/vision_maskrcnn
((T([0], i64), 2), {})
aten.eq.Scalar
TorchBench/vision_maskrcnn
((T([0], i64), 3), {})
aten.eq.Scalar
HuggingFace/AllenaiLongformerBase
((T([1, 256, 1, 257], f16), 1), {})
aten.eq.Scalar
HuggingFace/AllenaiLongformerBase
((T([1, 256, 12, 257], f16, stride=(65792, 257, 0, 1)), 1), {})
aten.eq.Scalar
TorchBench/speech_transformer
((T([10, 22], i64), 2), {})
aten.eq.Scalar
TorchBench/BERT_pytorch
((T([16, 1, 128, 128], b8), 0), {})
aten.eq.Scalar
TorchBench/BERT_pytorch
((T([16, 128, 1], f16), 0), {})
aten.eq.Scalar
HuggingFace/DistilBertForMaskedLM
((T([16, 128], f32), 0), {})
aten.eq.Scalar
HuggingFace/BartForConditionalGeneration
((T([2, 1024], i64), -100), {})
aten.eq.Scalar
TorchBench/hf_Longformer
((T([2, 256, 1, 257], f16, stride=(0, 257, 257, 1)), 1), {})
aten.eq.Scalar
TorchBench/hf_Longformer
((T([2, 256, 12, 257], f16, stride=(0, 257, 0, 1)), 1), {})
aten.eq.Scalar
TorchBench/attention_is_all_you_need_pytorch
((T([256, 1, 1, 33], b8, stride=(1, 8448, 8448, 256)), 0), {})
aten.eq.Scalar
TorchBench/attention_is_all_you_need_pytorch
((T([256, 1, 31, 31], b8, stride=(1, 7936, 256, 7936)), 0), {})
aten.eq.Scalar
HuggingFace/DistilBertForQuestionAnswering
((T([32, 128], f32), 0), {})
aten.eq.Scalar
TorchBench/fastNLP_Bert
((T([6, 474, 1], b8), False), {})
aten.eq.Scalar
TorchBench/fastNLP_Bert
((T([6, 474], b8), False), {})
aten.eq.Scalar
TorchBench/fastNLP_Bert
((T([6, 476], i64), 511), {})
aten.eq.Scalar
TorchBench/tts_angular
((T([64, 1], f16), 0), {})
aten.eq.Scalar
HuggingFace/MBartForConditionalGeneration
((T([8, 128], i64), -100), {})
aten.eq.Scalar
HuggingFace/PLBartForConditionalGeneration
((T([8, 128], i64), -100), {})
aten.eq.Scalar
TorchBench/hf_DistilBert
((T([8, 512], f32), 0), {})
aten.eq.Tensor
HuggingFace/OPTForCausalLM
((T([4, 12, 128, 128], f16), T([], f32)), {})
aten.eq.Tensor
TorchBench/timm_efficientdet
((T([5000, 4], f32), T([4], f16)), {})
aten.erf.default
TorchBench/fastNLP_Bert
((T([6, 476, 3072], f16),), {})
aten.exp.default
TorchBench/vision_maskrcnn
((T([0, 91], f16),), {})
aten.exp.default
TorchBench/vision_maskrcnn
((T([1438452, 1], f16),), {})
aten.exp.default
TorchBench/timm_efficientdet
((T([5000], f32, stride=(4,)),), {})
aten.exp.default
TorchBench/fastNLP_Bert
((T([6, 476, 3072], f16),), {})
aten.exp.default
TorchBench/yolov3
((T([8, 3, 12, 16, 2], f16, stride=(48960, 16320, 1360, 85, 1)),), {})
aten.exp.default
TorchBench/yolov3
((T([8, 3, 24, 32, 2], f16, stride=(195840, 65280, 2720, 85, 1)),), {})
aten.exp.default
TorchBench/yolov3
((T([8, 3, 48, 64, 2], f16, stride=(783360, 261120, 5440, 85, 1)),), {})
aten.fill_.Scalar
TorchBench/speech_transformer
((T([10, 22], i64), -1), {})
aten.fill_.Scalar
TorchBench/speech_transformer
((T([10, 22], i64), 2), {})
aten.fill_.Scalar
TorchBench/fastNLP_Bert
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aten.fill_.Scalar
TorchBench/fastNLP_Bert
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aten.fill_.Scalar
TorchBench/vision_maskrcnn
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aten.fill_.Scalar
TorchBench/vision_maskrcnn
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aten.fill_.Scalar
TorchBench/vision_maskrcnn
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aten.fill_.Scalar
TorchBench/vision_maskrcnn
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aten.fill_.Scalar
TorchBench/vision_maskrcnn
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aten.fill_.Scalar
TorchBench/vision_maskrcnn
((T([], i64), 8), {})
aten.fill_.Tensor
TorchBench/speech_transformer
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