operator name
stringclasses
180 values
used in model
stringclasses
155 values
args
stringlengths
19
5.24k
aten.mean.dim
TIMM/tinynet_a
((T([128, 240, 12, 12], f16), [2, 3], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 240, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 240, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 240, 24, 24], f16), [2, 3], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 240, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 240, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/eca_botnext26ts_256
((T([128, 256, 16, 16], f16), [2, 3]), {})
aten.mean.dim
TIMM/eca_halonext26ts
((T([128, 256, 16, 16], f16), [2, 3]), {})
aten.mean.dim
TIMM/dm_nfnet_f0
((T([128, 256, 48, 48], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_nfnet
((T([128, 256, 48, 48], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ese_vovnet19b_dw
((T([128, 256, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/nfnet_l0
((T([128, 256, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/lcnet_050
((T([128, 256, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/lcnet_050
((T([128, 256, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/gernet_l
((T([128, 2560, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 300, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/dm_nfnet_f0
((T([128, 3072, 6, 6], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_nfnet
((T([128, 3072, 6, 6], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 32, 112, 112], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 32, 96, 96], f16), [2, 3], True), {})
aten.mean.dim
TIMM/fbnetv3_b
((T([128, 360, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 366, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/regnety_002
((T([128, 368, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/regnety_002
((T([128, 368, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 432, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 480, 12, 12], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ghostnet_100
((T([128, 480, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 480, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mobilenetv3_large_100
((T([128, 480, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 480, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 504, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/dm_nfnet_f0
((T([128, 512, 24, 24], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_nfnet
((T([128, 512, 24, 24], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ese_vovnet19b_dw
((T([128, 512, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/nfnet_l0
((T([128, 512, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/resnet18
((T([128, 512, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/regnety_002
((T([128, 56, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 570, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 636, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/eca_botnext26ts_256
((T([128, 64, 64, 64], f16), [2, 3]), {})
aten.mean.dim
TIMM/eca_halonext26ts
((T([128, 64, 64, 64], f16), [2, 3]), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 672, 12, 12], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ghostnet_100
((T([128, 672, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 672, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mobilenetv3_large_100
((T([128, 672, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 672, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 672, 6, 6], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ghostnet_100
((T([128, 672, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 672, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mobilenetv3_large_100
((T([128, 672, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 672, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 702, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ghostnet_100
((T([128, 72, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mobilenetv3_large_100
((T([128, 72, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 72, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/fbnetv3_b
((T([128, 720, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/fbnetv3_b
((T([128, 736, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ese_vovnet19b_dw
((T([128, 768, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/visformer_small
((T([128, 768, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 768, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 840, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 906, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 96, 48, 48], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 96, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ghostnet_100
((T([128, 960, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 960, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/mobilenetv3_large_100
((T([128, 960, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/ghostnet_100
((T([128, 960, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mobilenetv3_large_100
((T([128, 960, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 972, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/BERT_pytorch
((T([16, 128, 768], f16), [-1], True), {})
aten.mean.dim
TorchBench/pytorch_stargan
((T([16, 128], f16), [0]), {})
aten.mean.dim
TorchBench/pytorch_stargan
((T([16, 256], f16), [0]), {})
aten.mean.dim
TIMM/nasnetalarge
((T([16, 4032, 11, 11], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/pnasnet5large
((T([16, 4320, 11, 11], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/resnet18
((T([16, 512, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/pytorch_stargan
((T([16, 64], f16), [0]), {})
aten.mean.dim
TIMM/crossvit_9_240
((T([2, 64, 1000], f16), [0]), {})
aten.mean.dim
TorchBench/squeezenet1_1
((T([32, 1000, 13, 13], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/gluon_senet154
((T([32, 1024, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/legacy_senet154
((T([32, 1024, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_vovnet
((T([32, 1024, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/convnext_base
((T([32, 1024, 7, 7], f16, stride=(50176, 1, 7168, 1024)), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 1152, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/mobilenet_v3_large
((T([32, 120, 28, 28], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 128, 32, 32], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_resnest
((T([32, 128, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/convnext_base
((T([32, 128, 56, 56], f16, stride=(401408, 1, 7168, 128)), [1], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 128, 64, 64], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 1280, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/mnasnet1_0
((T([32, 1280, 7, 7], f16), [2, 3]), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 144, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 144, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/gluon_xception65
((T([32, 2048, 10, 10], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/gluon_senet154
((T([32, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/legacy_senet154
((T([32, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/swsl_resnext101_32x16d
((T([32, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/resnet50
((T([32, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_resnest
((T([32, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/gluon_senet154
((T([32, 2048, 7, 7], f16), [2, 3], True), {})