operator name
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180 values
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aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 8, 112, 112], f16), T([128, 3, 224, 224], f16), T([8, 3, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 8, 112, 112], f16), T([128, 8, 112, 112], f16), T([8, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 8, [True, True, False]), {})
aten.convolution_backward.default
TIMM/lcnet_050
((T([128, 8, 112, 112], f16), T([128, 8, 112, 112], f16), T([8, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 8, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 80, 12, 12], f16), T([128, 240, 12, 12], f16), T([80, 240, 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, 80, 12, 12], f16), T([128, 480, 12, 12], f16), T([80, 480, 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, 80, 14, 14], f16), T([128, 184, 14, 14], f16), T([80, 184, 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, 80, 14, 14], f16), T([128, 200, 14, 14], f16), T([80, 200, 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, 80, 14, 14], f16), T([128, 240, 14, 14], f16), T([80, 240, 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, 80, 14, 14], f16), T([128, 240, 14, 14], f16), T([80, 240, 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, 80, 14, 14], f16), T([128, 240, 14, 14], f16), T([80, 240, 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, 80, 14, 14], f16), T([128, 240, 14, 14], f16), T([80, 240, 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, 80, 14, 14], f16), T([128, 240, 14, 14], f16), T([80, 240, 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, 80, 14, 14], f16), T([128, 40, 14, 14], f16), T([80, 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, 80, 14, 14], f16), T([128, 480, 14, 14], f16), T([80, 480, 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, 80, 14, 14], f16), T([128, 480, 14, 14], f16), T([80, 480, 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, 80, 14, 14], f16), T([128, 480, 14, 14], f16), T([80, 480, 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, 80, 14, 14], f16), T([128, 80, 14, 14], f16), T([80, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 80, [True, True, False]), {})
aten.convolution_backward.default
TIMM/coat_lite_mini
((T([128, 80, 14, 14], f16, stride=(62720, 1, 4480, 320)), T([128, 80, 14, 14], f16, stride=(189120, 1, 13440, 960)), T([80, 1, 3, 3], f16), [80], [1, 1], [1, 1], [1, 1], False, [0, 0], 80, [True, True, True]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 80, 7, 7], f16), T([128, 672, 7, 7], f16), T([80, 672, 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, 80, 7, 7], f16), T([128, 80, 7, 7], f16), T([80, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 80, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 80, 7, 7], f16), T([128, 960, 7, 7], f16), T([80, 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, 80, 73, 73], f16), T([128, 64, 73, 73], f16), T([80, 64, 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, 80, 73, 73], f16), T([128, 64, 73, 73], f16), T([80, 64, 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, 80, 73, 73], f16), T([128, 64, 73, 73], f16), T([80, 64, 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, 81, 1, 1], f16), T([128, 972, 1, 1], f16), T([81, 972, 1, 1], f16), [81], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 84, 14, 14], f16), T([128, 432, 14, 14], f16), T([84, 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, 840, 1, 1], f16), T([128, 70, 1, 1], f16), T([840, 70, 1, 1], f16), [840], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 840, 7, 7], f16), T([128, 140, 7, 7], f16), T([840, 140, 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, 840, 7, 7], f16), T([128, 840, 7, 7], f16), T([840, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 840, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 87, 1, 1], f16), T([128, 1044, 1, 1], f16), T([87, 1044, 1, 1], f16), [87], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/res2net50_14w_8s
((T([128, 896, 14, 14], f16), T([128, 1024, 14, 14], f16), T([896, 1024, 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, 896, 7, 7], f16), T([128, 2048, 7, 7], f16), T([896, 2048, 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, 906, 1, 1], f16), T([128, 75, 1, 1], f16), T([906, 75, 1, 1], f16), [906], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 906, 7, 7], f16), T([128, 151, 7, 7], f16), T([906, 151, 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, 906, 7, 7], f16), T([128, 906, 7, 7], f16), T([906, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 906, [True, True, False]), {})
aten.convolution_backward.default
TIMM/regnety_002
((T([128, 92, 1, 1], f16), T([128, 368, 1, 1], f16), T([92, 368, 1, 1], f16), [92], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 92, 14, 14], f16), T([128, 80, 14, 14], f16), T([92, 80, 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, 92, 14, 14], f16), T([128, 92, 14, 14], f16), T([92, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 92, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 95, 14, 14], f16), T([128, 504, 14, 14], f16), T([95, 504, 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, 96, 1, 1], f16), T([128, 4, 1, 1], f16), T([96, 4, 1, 1], f16), [96], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 96, 1, 1], f16), T([128, 4, 1, 1], f16), T([96, 4, 1, 1], f16), [96], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 96, 112, 112], f16), T([128, 16, 112, 112], f16), T([96, 16, 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, 96, 112, 112], f16), T([128, 16, 112, 112], f16), T([96, 16, 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, 96, 112, 112], f16), T([128, 16, 112, 112], f16), T([96, 16, 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, 96, 112, 112], f16), T([128, 16, 112, 112], f16), T([96, 16, 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, 96, 14, 14], f16), T([128, 288, 14, 14], f16), T([96, 288, 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, 96, 14, 14], f16), T([128, 384, 14, 14], f16), T([96, 384, 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, 96, 14, 14], f16), T([128, 480, 14, 14], f16), T([96, 480, 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, 96, 14, 14], f16), T([128, 480, 14, 14], f16), T([96, 480, 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, 96, 14, 14], f16), T([128, 576, 14, 14], f16), T([96, 576, 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, 96, 14, 14], f16), T([128, 576, 14, 14], f16), T([96, 576, 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, 96, 17, 17], f16), T([128, 96, 35, 35], f16), T([96, 96, 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, 96, 17, 17], f16), T([128, 96, 35, 35], f16), T([96, 96, 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, 96, 17, 17], f16), T([128, 96, 35, 35], f16), T([96, 96, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 96, 28, 28], f16), T([128, 32, 28, 28], f16), T([96, 32, 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, 96, 28, 28], f16), T([128, 96, 28, 28], f16), T([96, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 96, 35, 35], f16), T([128, 64, 35, 35], f16), T([96, 64, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 96, 35, 35], f16), T([128, 64, 35, 35], f16), T([96, 64, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 96, 35, 35], f16), T([128, 64, 35, 35], f16), T([96, 64, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/adv_inception_v3
((T([128, 96, 35, 35], f16), T([128, 96, 35, 35], f16), T([96, 96, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/gluon_inception_v3
((T([128, 96, 35, 35], f16), T([128, 96, 35, 35], f16), T([96, 96, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/inception_v3
((T([128, 96, 35, 35], f16), T([128, 96, 35, 35], f16), T([96, 96, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 96, 48, 48], f16), T([128, 96, 96, 96], f16), T([96, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/repvgg_a2
((T([128, 96, 56, 56], f16), T([128, 64, 112, 112], f16), T([96, 64, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/repvgg_a2
((T([128, 96, 56, 56], f16), T([128, 64, 112, 112], f16), T([96, 64, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 96, 56, 56], f16), T([128, 96, 112, 112], f16), T([96, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv2_100
((T([128, 96, 56, 56], f16), T([128, 96, 112, 112], f16), T([96, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 96, 56, 56], f16), T([128, 96, 112, 112], f16), T([96, 1, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 96, 56, 56], f16), T([128, 96, 113, 113], f16), T([96, 1, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/repvgg_a2
((T([128, 96, 56, 56], f16), T([128, 96, 56, 56], f16), T([96, 96, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/repvgg_a2
((T([128, 96, 56, 56], f16), T([128, 96, 56, 56], f16), T([96, 96, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 96, 96, 96], f16), T([128, 16, 96, 96], f16), T([96, 16, 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, 960, 1, 1], f16), T([128, 240, 1, 1], f16), T([960, 240, 1, 1], f16), [960], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 960, 1, 1], f16), T([128, 240, 1, 1], f16), T([960, 240, 1, 1], f16), [960], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 960, 7, 7], f16), T([128, 160, 7, 7], f16), T([960, 160, 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, 960, 7, 7], f16), T([128, 160, 7, 7], f16), T([960, 160, 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, 960, 7, 7], f16), T([128, 160, 7, 7], f16), T([960, 160, 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, 960, 7, 7], f16), T([128, 192, 7, 7], f16), T([960, 192, 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, 960, 7, 7], f16), T([128, 480, 14, 14], f16), T([960, 480, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv2_100
((T([128, 960, 7, 7], f16), T([128, 960, 7, 7], f16), T([960, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 960, [True, True, False]), {})
aten.convolution_backward.default
TIMM/mobilenetv3_large_100
((T([128, 960, 7, 7], f16), T([128, 960, 7, 7], f16), T([960, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 960, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 972, 1, 1], f16), T([128, 81, 1, 1], f16), T([972, 81, 1, 1], f16), [972], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 972, 7, 7], f16), T([128, 162, 7, 7], f16), T([972, 162, 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, 972, 7, 7], f16), T([128, 972, 7, 7], f16), T([972, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 972, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 42, 42], f16), T([108, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 108, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 42, 42], f16), T([108, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 108, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 42, 42], f16), T([108, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 108, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 42, 42], f16), T([108, 108, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 83, 83], f16), T([108, 108, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 85, 85], f16), T([108, 1, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 108, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 87, 87], f16), T([108, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 108, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16), T([16, 108, 89, 89], f16), T([108, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 108, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 42, 42], f16, stride=(381024, 1764, 42, 1)), T([16, 270, 42, 42], f16), T([108, 270, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 108, 83, 83], f16), T([16, 270, 83, 83], f16), T([108, 270, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/resnet18
((T([16, 128, 28, 28], f16), T([16, 128, 28, 28], f16), T([128, 128, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/resnet18
((T([16, 128, 28, 28], f16), T([16, 64, 56, 56], f16), T([128, 64, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/resnet18
((T([16, 128, 28, 28], f16), T([16, 64, 56, 56], f16), T([128, 64, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/pytorch_stargan
((T([16, 128, 64, 64], f16), T([16, 256, 32, 32], f16), T([256, 128, 4, 4], f16), [0], [2, 2], [1, 1], [1, 1], True, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/pytorch_stargan
((T([16, 128, 64, 64], f16), T([16, 64, 128, 128], f16), T([128, 64, 4, 4], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 168, 21, 21], f16, stride=(148176, 441, 21, 1)), T([16, 1008, 21, 21], f16), T([168, 1008, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})