operator name
stringclasses
180 values
used in model
stringclasses
155 values
args
stringlengths
19
5.24k
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 27, 56, 56], f16), T([128, 96, 56, 56], f16), T([27, 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, 28, 1, 1], f16), T([128, 672, 1, 1], f16), T([28, 672, 1, 1], f16), [28], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 28, 1, 1], f16), T([128, 672, 1, 1], f16), T([28, 672, 1, 1], f16), [28], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/res2net50_14w_8s
((T([128, 28, 28, 28], f16), T([128, 28, 28, 28], f16), T([28, 28, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2net50_14w_8s
((T([128, 28, 28, 28], f16), T([128, 28, 28, 28], f16, stride=(175616, 784, 28, 1)), T([28, 28, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2net50_14w_8s
((T([128, 28, 28, 28], f16), T([128, 28, 56, 56], f16, stride=(702464, 3136, 56, 1)), T([28, 28, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 288, 1, 1], f16), T([128, 1152, 1, 1], f16), T([288, 1152, 1, 1], f16), [288], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 288, 14, 14], f16), T([128, 288, 14, 14], f16), T([288, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 288, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 288, 14, 14], f16), T([128, 96, 14, 14], f16), T([288, 96, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 288, 28, 28], f16), T([128, 432, 28, 28], f16), T([288, 432, 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, 30, 1, 1], f16), T([128, 366, 1, 1], f16), T([30, 366, 1, 1], f16), [30], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 300, 1, 1], f16), T([128, 25, 1, 1], f16), T([300, 25, 1, 1], f16), [300], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 300, 28, 28], f16), T([128, 300, 28, 28], f16), T([300, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 300, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 300, 28, 28], f16), T([128, 50, 28, 28], f16), T([300, 50, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 304, 14, 14], f16), T([128, 152, 14, 14], f16), T([304, 152, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 304, 14, 14], f16), T([128, 288, 28, 28], f16), T([304, 288, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 304, 14, 14], f16), T([128, 304, 14, 14], f16), T([304, 304, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 304, 14, 14], f16), T([128, 304, 14, 14], f16), T([304, 304, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 304, 14, 14], f16), T([128, 608, 14, 14], f16), T([304, 608, 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, 3072, 6, 6], f16), T([128, 1536, 6, 6], f16), T([3072, 1536, 1, 1], f16), [3072], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 3072, 6, 6], f16), T([128, 1536, 6, 6], f16), T([3072, 1536, 1, 1], f16), [3072], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/visformer_small
((T([128, 3072, 7, 7], f16), T([128, 768, 7, 7], f16), T([3072, 768, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 32, 1, 1], f16), T([128, 120, 1, 1], f16), T([32, 120, 1, 1], f16), [32], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 32, 1, 1], f16), T([128, 120, 1, 1], f16), T([32, 120, 1, 1], f16), [32], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 32, 1, 1], f16), T([128, 128, 1, 1], f16), T([32, 128, 1, 1], f16), [32], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/fbnetv3_b
((T([128, 32, 1, 1], f16), T([128, 360, 1, 1], f16), T([32, 360, 1, 1], f16), [32], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/fbnetv3_b
((T([128, 32, 1, 1], f16), T([128, 720, 1, 1], f16), T([32, 720, 1, 1], f16), [32], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 32, 1, 1], f16), T([128, 8, 1, 1], f16), T([32, 8, 1, 1], f16), [32], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 32, 1, 1], f16), T([128, 8, 1, 1], f16), T([32, 8, 1, 1], f16), [32], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/nfnet_l0
((T([128, 32, 112, 112], f16), T([128, 16, 112, 112], f16), T([32, 16, 3, 3], f16), [32], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/mnasnet_100
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv2_100
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/regnety_002
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/visformer_small
((T([128, 32, 112, 112], f16), T([128, 3, 224, 224], f16), T([32, 3, 7, 7], f16), [0], [2, 2], [3, 3], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 32, 112, 112], f16), T([128, 3, 225, 225], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/hardcorenas_a
((T([128, 32, 112, 112], f16), T([128, 32, 112, 112], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mnasnet_100
((T([128, 32, 112, 112], f16), T([128, 32, 112, 112], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv2_100
((T([128, 32, 112, 112], f16), T([128, 32, 112, 112], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 32, 112, 112], f16), T([128, 32, 112, 112], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/spnasnet_100
((T([128, 32, 112, 112], f16), T([128, 32, 112, 112], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 32, 112, 112], f16), T([128, 32, 112, 112], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/botnet26t_256
((T([128, 32, 128, 128], f16), T([128, 24, 128, 128], f16), T([32, 24, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 32, 128, 128], f16), T([128, 24, 128, 128], f16), T([32, 24, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 32, 128, 128], f16), T([128, 24, 128, 128], f16), T([32, 24, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gernet_l
((T([128, 32, 128, 128], f16), T([128, 3, 256, 256], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 32, 147, 147], f16), T([128, 32, 149, 149], f16), T([32, 32, 3, 3], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 32, 147, 147], f16), T([128, 32, 149, 149], f16), T([32, 32, 3, 3], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 32, 147, 147], f16), T([128, 32, 149, 149], f16), T([32, 32, 3, 3], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 32, 149, 149], f16), T([128, 3, 299, 299], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 32, 149, 149], f16), T([128, 3, 299, 299], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 32, 149, 149], f16), T([128, 3, 299, 299], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 32, 28, 28], f16), T([128, 144, 28, 28], f16), T([32, 144, 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, 32, 28, 28], f16), T([128, 144, 28, 28], f16), T([32, 144, 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, 32, 28, 28], f16), T([128, 192, 28, 28], f16), T([32, 192, 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, 32, 28, 28], f16), T([128, 192, 28, 28], f16), T([32, 192, 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, 32, 28, 28], f16), T([128, 32, 56, 56], f16), T([32, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 32, 28, 28], f16), T([128, 96, 28, 28], f16), T([32, 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, 32, 28, 28], f16, stride=(100352, 1, 3584, 128)), T([128, 32, 28, 28], f16, stride=(301440, 1, 10752, 384)), T([32, 1, 3, 3], f16), [32], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, True]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 32, 35, 35], f16), T([128, 192, 35, 35], f16), T([32, 192, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 32, 35, 35], f16), T([128, 192, 35, 35], f16), T([32, 192, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 32, 35, 35], f16), T([128, 192, 35, 35], f16), T([32, 192, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/levit_128
((T([128, 32, 56, 56], f16), T([128, 16, 112, 112], f16), T([32, 16, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 32, 56, 56], f16), T([128, 16, 56, 56], f16), T([32, 16, 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, 32, 56, 56], f16), T([128, 18, 56, 56], f16), T([32, 18, 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, 32, 56, 56], f16), T([128, 32, 56, 56], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 32, 56, 56], f16), T([128, 32, 56, 56], f16), T([32, 32, 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, 32, 56, 56], f16), T([128, 32, 56, 56], f16), T([32, 32, 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, 32, 56, 56], f16), T([128, 32, 56, 56], f16), T([32, 4, 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, 32, 56, 56], f16), T([128, 32, 56, 56], f16, stride=(401408, 3136, 56, 1)), T([32, 4, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 8, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 32, 56, 56], f16), T([128, 64, 56, 56], f16), T([32, 64, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/dm_nfnet_f0
((T([128, 32, 96, 96], f16), T([128, 16, 96, 96], f16), T([32, 16, 3, 3], f16), [32], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_nfnet
((T([128, 32, 96, 96], f16), T([128, 16, 96, 96], f16), T([32, 16, 3, 3], f16), [32], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 32, 96, 96], f16), T([128, 3, 192, 192], f16), T([32, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 32, 96, 96], f16), T([128, 32, 96, 96], f16), T([32, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 32, [True, True, False]), {})
aten.convolution_backward.default
TIMM/coat_lite_mini
((T([128, 320, 14, 14], f16, stride=(62720, 1, 4480, 320)), T([128, 128, 28, 28], f16), T([320, 128, 2, 2], f16), [320], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/coat_lite_mini
((T([128, 320, 14, 14], f16, stride=(63040, 1, 4480, 320)), T([128, 320, 14, 14], f16, stride=(63040, 1, 4480, 320)), T([320, 1, 3, 3], f16), [320], [1, 1], [1, 1], [1, 1], False, [0, 0], 320, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 320, 6, 6], f16), T([128, 1152, 6, 6], f16), T([320, 1152, 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, 320, 7, 7], f16), T([128, 1152, 7, 7], f16), T([320, 1152, 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, 320, 7, 7], f16), T([128, 1152, 7, 7], f16), T([320, 1152, 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, 320, 7, 7], f16), T([128, 1152, 7, 7], f16), T([320, 1152, 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, 320, 7, 7], f16), T([128, 960, 7, 7], f16), T([320, 960, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 320, 8, 8], f16), T([128, 1280, 8, 8], f16), T([320, 1280, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 320, 8, 8], f16), T([128, 1280, 8, 8], f16), T([320, 1280, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 320, 8, 8], f16), T([128, 1280, 8, 8], f16), T([320, 1280, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 320, 8, 8], f16), T([128, 192, 17, 17], f16), T([320, 192, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 320, 8, 8], f16), T([128, 192, 17, 17], f16), T([320, 192, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 320, 8, 8], f16), T([128, 192, 17, 17], f16), T([320, 192, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 320, 8, 8], f16), T([128, 2048, 8, 8], f16), T([320, 2048, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 320, 8, 8], f16), T([128, 2048, 8, 8], f16), T([320, 2048, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 320, 8, 8], f16), T([128, 2048, 8, 8], f16), T([320, 2048, 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, 336, 14, 14], f16), T([128, 112, 14, 14], f16), T([336, 112, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 336, 14, 14], f16), T([128, 112, 14, 14], f16), T([336, 112, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 336, 14, 14], f16), T([128, 336, 14, 14], f16), T([336, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 336, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 336, 14, 14], f16), T([128, 336, 14, 14], f16), T([336, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 336, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 352, 7, 7], f16), T([128, 1104, 7, 7], f16), T([352, 1104, 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, 36, 1, 1], f16), T([128, 432, 1, 1], f16), T([36, 432, 1, 1], f16), [36], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})