operator name
stringclasses
180 values
used in model
stringclasses
155 values
args
stringlengths
19
5.24k
aten.avg_pool2d_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16, stride=(325248, 121, 11, 1)), T([16, 672, 11, 11], f16), [3, 3], [1, 1], [1, 1], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16, stride=(325248, 121, 11, 1)), T([16, 672, 23, 23], f16), [3, 3], [2, 2], [0, 0], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16, stride=(487872, 121, 11, 1)), T([16, 672, 11, 11], f16), [3, 3], [1, 1], [1, 1], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16, stride=(592704, 1764, 42, 1)), T([16, 84, 42, 42], f16), [3, 3], [1, 1], [1, 1], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16, stride=(592704, 1764, 42, 1)), T([16, 84, 85, 85], f16), [3, 3], [2, 2], [0, 0], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/nasnetalarge
((T([16, 96, 83, 83], f16), T([16, 96, 165, 165], f16), [1, 1], [2, 2], [0, 0], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/pnasnet5large
((T([16, 96, 83, 83], f16), T([16, 96, 165, 165], f16), [1, 1], [2, 2], [0, 0], False, False, None), {})
aten.avg_pool2d_backward.default
TorchBench/timm_resnest
((T([32, 1024, 7, 7], f16), T([32, 1024, 14, 14], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TIMM/resnest101e
((T([32, 1024, 8, 8], f16), T([32, 1024, 16, 16], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TorchBench/timm_resnest
((T([32, 128, 28, 28], f16), T([32, 128, 56, 56], f16), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/resnest101e
((T([32, 128, 32, 32], f16), T([32, 128, 64, 64], f16), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/timm_resnest
((T([32, 256, 14, 14], f16), T([32, 256, 28, 28], f16), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/resnest101e
((T([32, 256, 16, 16], f16), T([32, 256, 32, 32], f16), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/timm_resnest
((T([32, 256, 28, 28], f16), T([32, 256, 56, 56], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TIMM/resnest101e
((T([32, 256, 32, 32], f16), T([32, 256, 64, 64], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TorchBench/timm_resnest
((T([32, 512, 14, 14], f16), T([32, 512, 28, 28], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TIMM/resnest101e
((T([32, 512, 16, 16], f16), T([32, 512, 32, 32], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TorchBench/timm_resnest
((T([32, 512, 7, 7], f16), T([32, 512, 14, 14], f16), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/resnest101e
((T([32, 512, 8, 8], f16), T([32, 512, 16, 16], f16), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/densenet121
((T([4, 128, 28, 28], f16), T([4, 128, 56, 56], f16), [2, 2], [2, 2], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/densenet121
((T([4, 256, 14, 14], f16), T([4, 256, 28, 28], f16), [2, 2], [2, 2], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/densenet121
((T([4, 512, 7, 7], f16), T([4, 512, 14, 14], f16), [2, 2], [2, 2], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/Super_SloMo
((T([6, 128, 44, 44], f16), T([6, 128, 88, 88], f16), [2, 2], [], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/Super_SloMo
((T([6, 256, 22, 22], f16), T([6, 256, 44, 44], f16), [2, 2], [], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/Super_SloMo
((T([6, 32, 176, 176], f16), T([6, 32, 352, 352], f16), [2, 2], [], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/Super_SloMo
((T([6, 512, 11, 11], f16), T([6, 512, 22, 22], f16), [2, 2], [], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TorchBench/Super_SloMo
((T([6, 64, 88, 88], f16), T([6, 64, 176, 176], f16), [2, 2], [], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/ecaresnet101d
((T([64, 1024, 7, 7], f16), T([64, 1024, 14, 14], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TIMM/res2net101_26w_4s
((T([64, 104, 14, 14], f16, stride=(81536, 196, 14, 1)), T([64, 104, 28, 28], f16, stride=(326144, 784, 28, 1)), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/densenet121
((T([64, 128, 28, 28], f16), T([64, 128, 56, 56], f16), [2, 2], [2, 2], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/volo_d1_224
((T([64, 192, 14, 14], f16, stride=(37632, 1, 2688, 192)), T([64, 192, 28, 28], f16, stride=(150528, 1, 5376, 192)), [2, 2], [2, 2], [0, 0], True, True, None), {})
aten.avg_pool2d_backward.default
TIMM/poolformer_m36
((T([64, 192, 28, 28], f16), T([64, 192, 28, 28], f16), [3, 3], [1, 1], [1, 1], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/res2net101_26w_4s
((T([64, 208, 7, 7], f16, stride=(40768, 49, 7, 1)), T([64, 208, 14, 14], f16, stride=(163072, 196, 14, 1)), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/densenet121
((T([64, 256, 14, 14], f16), T([64, 256, 28, 28], f16), [2, 2], [2, 2], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/ecaresnet101d
((T([64, 256, 28, 28], f16), T([64, 256, 56, 56], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TIMM/res2net101_26w_4s
((T([64, 26, 56, 56], f16, stride=(326144, 3136, 56, 1)), T([64, 26, 56, 56], f16, stride=(326144, 3136, 56, 1)), [3, 3], [1, 1], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/poolformer_m36
((T([64, 384, 14, 14], f16), T([64, 384, 14, 14], f16), [3, 3], [1, 1], [1, 1], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/ecaresnet101d
((T([64, 512, 14, 14], f16), T([64, 512, 28, 28], f16), [2, 2], [2, 2], [0, 0], True, False, None), {})
aten.avg_pool2d_backward.default
TIMM/densenet121
((T([64, 512, 7, 7], f16), T([64, 512, 14, 14], f16), [2, 2], [2, 2], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/sebotnet33ts_256
((T([64, 512, 8, 8], f16), T([64, 512, 16, 16], f16), [2, 2], [2, 2], [0, 0], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/res2net101_26w_4s
((T([64, 52, 28, 28], f16, stride=(163072, 784, 28, 1)), T([64, 52, 56, 56], f16, stride=(652288, 3136, 56, 1)), [3, 3], [2, 2], [1, 1], False, True, None), {})
aten.avg_pool2d_backward.default
TIMM/poolformer_m36
((T([64, 768, 7, 7], f16), T([64, 768, 7, 7], f16), [3, 3], [1, 1], [1, 1], False, False, None), {})
aten.avg_pool2d_backward.default
TIMM/poolformer_m36
((T([64, 96, 56, 56], f16), T([64, 96, 56, 56], f16), [3, 3], [1, 1], [1, 1], False, False, None), {})
aten.avg_pool2d_backward.default
TorchBench/LearningToPaint
((T([96, 512, 1, 1], f16), T([96, 512, 4, 4], f16), [4, 4], [], [0, 0], False, True, None), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.52173912525177), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.54347825050354), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.5652174055576324), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.5869565308094025), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.6086956560611725), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.6304347813129425), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.6521739065647125), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.6739130318164825), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.695652186870575), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.717391312122345), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.739130437374115), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.760869562625885), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.782608687877655), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.8043478280305862), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.8260869532823563), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.8478260785341263), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.8695652186870575), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.8913043439388275), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.9130434766411781), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.9347826093435287), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.9565217383205891), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16), 0.9782608691602945), {})
aten.bernoulli_.float
TIMM/jx_nest_base
((T([64, 1, 1, 1], f16),), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.8999999985098839), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9043478220701218), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9086956530809402), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9130434766411781), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.917391300201416), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9217391312122345), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9260869547724724), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9304347857832909), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9347826093435287), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9391304329037666), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9434782564640045), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9478260837495327), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9521739110350609), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9565217345952988), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.960869561880827), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9652173891663551), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9695652164518833), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9739130418747663), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9782608672976494), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9826086945831776), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9869565209373832), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9913043472915888), {})
aten.bernoulli_.float
TIMM/swin_base_patch4_window7_224
((T([64, 1, 1], f16), 0.9956521736457944), {})
aten.bitwise_and.Tensor
TorchBench/vision_maskrcnn
((T([0], b8), T([0], b8)), {})
aten.bitwise_and.Tensor
TorchBench/attention_is_all_you_need_pytorch
((T([256, 1, 31], b8, stride=(1, 7936, 256)), T([1, 31, 31], b8)), {})
aten.bitwise_and.Tensor
TorchBench/vision_maskrcnn
((T([5000], b8), T([5000], b8)), {})
aten.bitwise_not.default
HuggingFace/DebertaV2ForMaskedLM
((T([1, 1, 512, 512], b8),), {})
aten.bitwise_not.default
HuggingFace/DebertaV2ForQuestionAnswering
((T([1, 1, 512, 512], b8),), {})
aten.bitwise_not.default
HuggingFace/DebertaForMaskedLM
((T([4, 1, 512, 512], b8),), {})
aten.bitwise_not.default
HuggingFace/DebertaForQuestionAnswering
((T([4, 1, 512, 512], b8),), {})
aten.bitwise_xor.Tensor
TorchBench/fastNLP_Bert
((T([6, 1], i64, stride=(476, 1)), T([6, 476], i64)), {})
aten.bmm.default
TorchBench/pytorch_struct
((T([1, 1, 256], f16), T([1, 256, 30], f16, stride=(256, 1, 256))), {})
aten.bmm.default
TorchBench/pytorch_struct
((T([1, 1, 30], f16), T([1, 30, 256], f16)), {})