operator name
stringclasses
180 values
used in model
stringclasses
155 values
args
stringlengths
19
5.24k
aten.clone.default
HuggingFace/DebertaV2ForQuestionAnswering
((T([1], i64),), {})
aten.clone.default
HuggingFace/GPTNeoForSequenceClassification
((T([1], i64),), {})
aten.clone.default
HuggingFace/BartForConditionalGeneration
((T([2, 1023], i64, stride=(1024, 1)),), {})
aten.clone.default
HuggingFace/BartForConditionalGeneration
((T([2, 1024], i64),), {})
aten.clone.default
TorchBench/hf_BigBird
((T([2, 1024], i64),), {})
aten.clone.default
TorchBench/hf_Longformer
((T([2, 1024], i64),), {})
aten.clone.default
HuggingFace/XGLMForCausalLM
((T([2, 127], i64, stride=(128, 1)),), {})
aten.clone.default
HuggingFace/M2M100ForConditionalGeneration
((T([2, 128], i64),), {})
aten.clone.default
HuggingFace/MegatronBertForCausalLM
((T([2, 128], i64),), {})
aten.clone.default
HuggingFace/XGLMForCausalLM
((T([2, 128], i64),), {})
aten.clone.default
TIMM/cait_m36_384
((T([2, 3, 384, 384], f16),), {})
aten.clone.default
HuggingFace/AlbertForMaskedLM
((T([2, 512], i64),), {})
aten.clone.default
HuggingFace/AlbertForQuestionAnswering
((T([2, 512], i64),), {})
aten.clone.default
TorchBench/fambench_dlrm
((T([248, 1024], i64),), {})
aten.clone.default
TorchBench/nvidia_deeprecommender
((T([256, 197951], f16),), {})
aten.clone.default
TorchBench/attention_is_all_you_need_pytorch
((T([256, 31], i64, stride=(1, 256)),), {})
aten.clone.default
TorchBench/attention_is_all_you_need_pytorch
((T([256, 33], i64, stride=(1, 256)),), {})
aten.clone.default
HuggingFace/AlbertForQuestionAnswering
((T([2], i64),), {})
aten.clone.default
TorchBench/Background_Matting
((T([3, 1, 512, 512], f16),), {})
aten.clone.default
TorchBench/Background_Matting
((T([3, 3, 512, 512], f16),), {})
aten.clone.default
TorchBench/Background_Matting
((T([3, 4, 512, 512], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 10, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 1152, 7, 7], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 1280, 7, 7], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 1280], f16),), {})
aten.clone.default
HuggingFace/DistilBertForQuestionAnswering
((T([32, 128], i64),), {})
aten.clone.default
HuggingFace/MobileBertForQuestionAnswering
((T([32, 128], i64),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 144, 28, 28], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 144, 56, 56], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 16, 112, 112], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 184, 14, 14], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 20, 1, 1], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 200, 14, 14], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 240, 14, 14], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 240, 14, 14], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 240, 28, 28], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 240, 28, 28], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 28, 1, 1], f16),), {})
aten.clone.default
TIMM/convmixer_768_32
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TIMM/convnext_base
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TIMM/dpn107
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TIMM/gluon_senet154
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TIMM/legacy_senet154
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TIMM/swsl_resnext101_32x16d
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TIMM/twins_pcpvt_base
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/mnasnet1_0
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/resnet50
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/squeezenet1_1
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/timm_regnet
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/timm_resnest
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TorchBench/timm_vovnet
((T([32, 3, 224, 224], f16),), {})
aten.clone.default
TIMM/resnest101e
((T([32, 3, 256, 256], f16),), {})
aten.clone.default
TIMM/gluon_xception65
((T([32, 3, 299, 299], f16),), {})
aten.clone.default
TorchBench/dcgan
((T([32, 3, 64, 64], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 32, 112, 112], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 4, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 48, 1, 1], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 480, 14, 14], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 480, 14, 14], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 6, 1, 1], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 672, 14, 14], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 672, 14, 14], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 672, 7, 7], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 672, 7, 7], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 8, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 96, 112, 112], f16),), {})
aten.clone.default
TorchBench/timm_efficientnet
((T([32, 96, 56, 56], f16),), {})
aten.clone.default
TorchBench/mobilenet_v3_large
((T([32, 960, 7, 7], f16),), {})
aten.clone.default
HuggingFace/DistilBertForQuestionAnswering
((T([32], i64),), {})
aten.clone.default
HuggingFace/MobileBertForQuestionAnswering
((T([32], i64),), {})
aten.clone.default
HuggingFace/BartForCausalLM
((T([4, 1024], i64),), {})
aten.clone.default
HuggingFace/GPT2ForSequenceClassification
((T([4, 1024], i64),), {})
aten.clone.default
HuggingFace/OPTForCausalLM
((T([4, 128], i64),), {})
aten.clone.default
HuggingFace/PegasusForConditionalGeneration
((T([4, 128], i64),), {})
aten.clone.default
HuggingFace/RobertaForCausalLM
((T([4, 128], i64),), {})
aten.clone.default
TorchBench/densenet121
((T([4, 3, 224, 224], f16),), {})
aten.clone.default
HuggingFace/DebertaForMaskedLM
((T([4, 512], i64),), {})
aten.clone.default
HuggingFace/DebertaForQuestionAnswering
((T([4, 512], i64),), {})
aten.clone.default
HuggingFace/XLNetLMHeadModel
((T([4, 512], i64),), {})
aten.clone.default
TorchBench/hf_Bart
((T([4, 512], i64),), {})
aten.clone.default
TorchBench/hf_Bert
((T([4, 512], i64),), {})
aten.clone.default
TorchBench/hf_GPT2
((T([4, 512], i64),), {})
aten.clone.default
TorchBench/pytorch_struct
((T([40, 29], i64, stride=(1, 40)),), {})
aten.clone.default
HuggingFace/DebertaForQuestionAnswering
((T([4], i64),), {})
aten.clone.default
HuggingFace/GPT2ForSequenceClassification
((T([4], i64),), {})
aten.clone.default
TorchBench/maml_omniglot
((T([5, 1, 28, 28], f16),), {})
aten.clone.default
TorchBench/Super_SloMo
((T([6, 3, 352, 352], f16),), {})
aten.clone.default
TorchBench/fastNLP_Bert
((T([6, 474], i64),), {})
aten.clone.default
TIMM/sebotnet33ts_256
((T([64, 1024, 16, 16], f16),), {})
aten.clone.default
TIMM/mobilevit_s
((T([64, 128, 128, 128], f16),), {})
aten.clone.default
TIMM/mobilevit_s
((T([64, 128, 16, 16], f16),), {})
aten.clone.default
TIMM/sebotnet33ts_256
((T([64, 128, 32, 32], f16),), {})
aten.clone.default
TIMM/mobilevit_s
((T([64, 128, 64, 64], f16),), {})
aten.clone.default
TIMM/sebotnet33ts_256
((T([64, 128, 64, 64], f16),), {})
aten.clone.default
TIMM/sebotnet33ts_256
((T([64, 1280, 8, 8], f16),), {})
aten.clone.default
HuggingFace/BertForMaskedLM
((T([64, 128], i64),), {})
aten.clone.default
HuggingFace/BertForQuestionAnswering
((T([64, 128], i64),), {})
aten.clone.default
HuggingFace/BlenderbotSmallForCausalLM
((T([64, 128], i64),), {})