operator name
stringclasses
180 values
used in model
stringclasses
155 values
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stringlengths
19
5.24k
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 24, 56, 56], f16), T([128, 24, 56, 56], f16), T([24, 24, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/regnety_002
((T([128, 24, 56, 56], f16), T([128, 24, 56, 56], f16), T([24, 24, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/regnety_002
((T([128, 24, 56, 56], f16), T([128, 32, 112, 112], f16), T([24, 32, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetv3_b
((T([128, 24, 56, 56], f16), T([128, 48, 56, 56], f16), T([24, 48, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 24, 56, 56], f16), T([128, 48, 56, 56], f16), T([24, 48, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mnasnet_100
((T([128, 24, 56, 56], f16), T([128, 48, 56, 56], f16), T([24, 48, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 24, 56, 56], f16), T([128, 48, 56, 56], f16), T([24, 48, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetv3_b
((T([128, 24, 56, 56], f16), T([128, 64, 56, 56], f16), T([24, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 24, 56, 56], f16), T([128, 64, 56, 56], f16), T([24, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 24, 56, 56], f16), T([128, 72, 56, 56], f16), T([24, 72, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mnasnet_100
((T([128, 24, 56, 56], f16), T([128, 72, 56, 56], f16), T([24, 72, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 24, 56, 56], f16), T([128, 72, 56, 56], f16), T([24, 72, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 24, 56, 56], f16), T([128, 72, 56, 56], f16), T([24, 72, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 24, 56, 56], f16), T([128, 96, 56, 56], f16), T([24, 96, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv2_100
((T([128, 24, 56, 56], f16), T([128, 96, 56, 56], f16), T([24, 96, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 24, 56, 56], f16), T([128, 96, 56, 56], f16), T([24, 96, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/coat_lite_mini
((T([128, 24, 56, 56], f16, stride=(200704, 1, 3584, 64)), T([128, 24, 56, 56], f16, stride=(602304, 1, 10752, 192)), T([24, 1, 5, 5], f16), [24], [1, 1], [2, 2], [1, 1], False, [0, 0], 24, [True, True, True]), {})
aten.convolution_backward.default
TIMM/coat_lite_mini
((T([128, 24, 56, 56], f16, stride=(200704, 1, 3584, 64)), T([128, 24, 56, 56], f16, stride=(602304, 1, 10752, 192)), T([24, 1, 7, 7], f16), [24], [1, 1], [3, 3], [1, 1], False, [0, 0], 24, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 240, 1, 1], f16), T([128, 10, 1, 1], f16), T([240, 10, 1, 1], f16), [240], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 240, 1, 1], f16), T([128, 10, 1, 1], f16), T([240, 10, 1, 1], f16), [240], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 240, 1, 1], f16), T([128, 64, 1, 1], f16), T([240, 64, 1, 1], f16), [240], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 240, 1, 1], f16), T([128, 960, 1, 1], f16), T([240, 960, 1, 1], f16), [240], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 240, 1, 1], f16), T([128, 960, 1, 1], f16), T([240, 960, 1, 1], f16), [240], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 240, 12, 12], f16), T([128, 240, 24, 24], f16), T([240, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 240, 14, 14], f16), T([128, 240, 14, 14], f16), T([240, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 240, 14, 14], f16), T([128, 240, 14, 14], f16), T([240, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 240, 14, 14], f16), T([128, 240, 28, 28], f16), T([240, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 240, 14, 14], f16), T([128, 240, 28, 28], f16), T([240, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 240, 14, 14], f16), T([128, 240, 28, 28], f16), T([240, 1, 5, 5], f16), [0], [2, 2], [2, 2], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mnasnet_100
((T([128, 240, 14, 14], f16), T([128, 240, 28, 28], f16), T([240, 1, 5, 5], f16), [0], [2, 2], [2, 2], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 240, 14, 14], f16), T([128, 240, 28, 28], f16), T([240, 1, 5, 5], f16), [0], [2, 2], [2, 2], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 240, 14, 14], f16), T([128, 240, 29, 29], f16), T([240, 1, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 240, 14, 14], f16), T([128, 80, 14, 14], f16), T([240, 80, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 240, 14, 14], f16), T([128, 80, 14, 14], f16), T([240, 80, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 240, 24, 24], f16), T([128, 240, 24, 24], f16), T([240, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 240, 24, 24], f16), T([128, 40, 24, 24], f16), T([240, 40, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 240, 28, 28], f16), T([128, 240, 28, 28], f16), T([240, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 240, 28, 28], f16), T([128, 240, 28, 28], f16), T([240, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 240, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 240, 28, 28], f16), T([128, 40, 28, 28], f16), T([240, 40, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mnasnet_100
((T([128, 240, 28, 28], f16), T([128, 40, 28, 28], f16), T([240, 40, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 240, 28, 28], f16), T([128, 40, 28, 28], f16), T([240, 40, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 240, 28, 28], f16), T([128, 40, 28, 28], f16), T([240, 40, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 240, 28, 28], f16), T([128, 40, 28, 28], f16), T([240, 40, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 25, 1, 1], f16), T([128, 300, 1, 1], f16), T([25, 300, 1, 1], f16), [25], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 256, 1, 1], f16), T([128, 128, 1, 1], f16), T([256, 128, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 256, 1, 1], f16), T([128, 128, 1, 1], f16), T([256, 128, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/ese_vovnet19b_dw
((T([128, 256, 1, 1], f16), T([128, 256, 1, 1], f16), T([256, 256, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 256, 1, 1], f16), T([128, 512, 1, 1], f16), T([256, 512, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 256, 1, 1], f16), T([128, 512, 1, 1], f16), T([256, 512, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 256, 1, 1], f16), T([128, 64, 1, 1], f16), T([256, 64, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/nfnet_l0
((T([128, 256, 1, 1], f16), T([128, 64, 1, 1], f16), T([256, 64, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/alexnet
((T([128, 256, 13, 13], f16), T([128, 256, 13, 13], f16), T([256, 256, 3, 3], f16), [256], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/alexnet
((T([128, 256, 13, 13], f16), T([128, 384, 13, 13], f16), T([256, 384, 3, 3], f16), [256], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/resnet18
((T([128, 256, 14, 14], f16), T([128, 128, 28, 28], f16), T([256, 128, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/resnet18
((T([128, 256, 14, 14], f16), T([128, 128, 28, 28], f16), T([256, 128, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/resnet18
((T([128, 256, 14, 14], f16), T([128, 256, 14, 14], f16), T([256, 256, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/botnet26t_256
((T([128, 256, 16, 16], f16), T([128, 1024, 16, 16], f16), T([256, 1024, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 256, 16, 16], f16), T([128, 1024, 16, 16], f16), T([256, 1024, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 256, 16, 16], f16), T([128, 1024, 16, 16], f16), T([256, 1024, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 256, 16, 16], f16), T([128, 256, 32, 32], f16), T([256, 16, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 16, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 256, 16, 16], f16), T([128, 256, 32, 32], f16), T([256, 16, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 16, [True, True, False]), {})
aten.convolution_backward.default
TIMM/botnet26t_256
((T([128, 256, 16, 16], f16), T([128, 256, 32, 32], f16), T([256, 256, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 256, 24, 24], f16), T([128, 256, 24, 24], f16), T([256, 128, 3, 3], f16), [256], [1, 1], [1, 1], [1, 1], False, [0, 0], 2, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 256, 24, 24], f16), T([128, 256, 24, 24], f16), T([256, 128, 3, 3], f16), [256], [1, 1], [1, 1], [1, 1], False, [0, 0], 2, [True, True, True]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 256, 24, 24], f16), T([128, 256, 49, 49], f16), T([256, 128, 3, 3], f16), [256], [2, 2], [0, 0], [1, 1], False, [0, 0], 2, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 256, 24, 24], f16), T([128, 256, 49, 49], f16), T([256, 128, 3, 3], f16), [256], [2, 2], [0, 0], [1, 1], False, [0, 0], 2, [True, True, True]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 256, 24, 24], f16), T([128, 512, 24, 24], f16), T([256, 512, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 256, 24, 24], f16), T([128, 512, 24, 24], f16), T([256, 512, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/hrnet_w18
((T([128, 256, 28, 28], f16), T([128, 128, 56, 56], f16), T([256, 128, 3, 3], f16), [256], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/hrnet_w18
((T([128, 256, 28, 28], f16), T([128, 36, 28, 28], f16), T([256, 36, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 256, 28, 28], f16), T([128, 512, 28, 28], f16), T([256, 512, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hrnet_w18
((T([128, 256, 28, 28], f16), T([128, 64, 28, 28], f16), T([256, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/botnet26t_256
((T([128, 256, 32, 32], f16), T([128, 512, 32, 32], f16), T([256, 512, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 256, 32, 32], f16), T([128, 512, 32, 32], f16), T([256, 512, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 256, 32, 32], f16), T([128, 512, 32, 32], f16), T([256, 512, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 256, 48, 48], f16), T([128, 128, 48, 48], f16), T([256, 128, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 256, 48, 48], f16), T([128, 128, 48, 48], f16), T([256, 128, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 256, 48, 48], f16), T([128, 256, 48, 48], f16), T([256, 256, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 256, 48, 48], f16), T([128, 256, 48, 48], f16), T([256, 256, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/res2net50_14w_8s
((T([128, 256, 56, 56], f16), T([128, 112, 56, 56], f16), T([256, 112, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 256, 56, 56], f16), T([128, 128, 56, 56], f16), T([256, 128, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nfnet_l0
((T([128, 256, 56, 56], f16), T([128, 128, 56, 56], f16), T([256, 128, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 256, 56, 56], f16), T([128, 256, 56, 56], f16), T([256, 256, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ese_vovnet19b_dw
((T([128, 256, 56, 56], f16), T([128, 448, 56, 56], f16), T([256, 448, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hrnet_w18
((T([128, 256, 56, 56], f16), T([128, 64, 56, 56], f16), T([256, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2net50_14w_8s
((T([128, 256, 56, 56], f16), T([128, 64, 56, 56], f16), T([256, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 256, 56, 56], f16), T([128, 64, 56, 56], f16), T([256, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nfnet_l0
((T([128, 256, 56, 56], f16), T([128, 64, 56, 56], f16), T([256, 64, 1, 1], f16), [256], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/botnet26t_256
((T([128, 256, 64, 64], f16), T([128, 64, 64, 64], f16), T([256, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 256, 64, 64], f16), T([128, 64, 64, 64], f16), T([256, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 256, 64, 64], f16), T([128, 64, 64, 64], f16), T([256, 64, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 256, 7, 7], f16), T([128, 128, 7, 7], f16), T([256, 128, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hrnet_w18
((T([128, 256, 7, 7], f16), T([128, 144, 7, 7], f16), T([256, 144, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 256, 7, 7], f16), T([128, 256, 14, 14], f16, stride=(200704, 196, 14, 1)), T([256, 32, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 8, [True, True, False]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 256, 7, 7], f16), T([128, 256, 7, 7], f16), T([256, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 256, [True, True, False]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 256, 7, 7], f16), T([128, 256, 7, 7], f16), T([256, 256, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hrnet_w18
((T([128, 256, 7, 7], f16), T([128, 256, 7, 7], f16), T([256, 256, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 256, 7, 7], f16), T([128, 256, 7, 7], f16), T([256, 32, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 8, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 256, 7, 7], f16), T([128, 256, 7, 7], f16, stride=(50176, 49, 7, 1)), T([256, 32, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 8, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gernet_l
((T([128, 2560, 8, 8], f16), T([128, 640, 8, 8], f16), T([2560, 640, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})