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5.24k
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 168, 42, 42], f16), T([16, 1008, 42, 42], f16), T([168, 1008, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 168, 42, 42], f16), T([16, 168, 42, 42], f16), T([168, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 168, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 168, 42, 42], f16), T([16, 168, 42, 42], f16), T([168, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 168, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 168, 42, 42], f16), T([16, 168, 42, 42], f16), T([168, 168, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 168, 42, 42], f16), T([16, 336, 42, 42], f16), T([168, 336, 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, 216, 21, 21], f16, stride=(190512, 441, 21, 1)), T([16, 1080, 21, 21], f16), T([216, 1080, 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, 216, 42, 42], f16), T([16, 1080, 42, 42], f16), T([216, 1080, 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, 216, 42, 42], f16), T([16, 216, 42, 42], f16), T([216, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 216, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 216, 42, 42], f16), T([16, 216, 42, 42], f16), T([216, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 216, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 216, 42, 42], f16), T([16, 216, 42, 42], f16), T([216, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 216, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 216, 42, 42], f16), T([16, 216, 42, 42], f16), T([216, 216, 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, 216, 42, 42], f16), T([16, 540, 42, 42], f16), T([216, 540, 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, 256, 14, 14], f16), T([16, 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
TorchBench/resnet18
((T([16, 256, 14, 14], f16), T([16, 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
TorchBench/resnet18
((T([16, 256, 14, 14], f16), T([16, 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
TorchBench/pytorch_stargan
((T([16, 256, 32, 32], f16), T([16, 128, 64, 64], f16), T([256, 128, 4, 4], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/pytorch_stargan
((T([16, 256, 32, 32], f16), T([16, 256, 32, 32], 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
TorchBench/pytorch_stargan
((T([16, 3, 128, 128], f16), T([16, 64, 128, 128], f16), T([3, 64, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 11, 11], f16, stride=(81312, 121, 11, 1)), T([16, 2016, 11, 11], f16), T([336, 2016, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 1344, 21, 21], f16), T([336, 1344, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 2016, 21, 21], f16), T([336, 2016, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 336, 21, 21], 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/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 336, 21, 21], 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/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 336, 21, 21], f16), T([336, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 336, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 336, 21, 21], f16), T([336, 336, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 336, 45, 45], f16), T([336, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 336, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 21, 21], f16), T([16, 336, 47, 47], f16), T([336, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 336, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 336, 42, 42], f16), T([16, 1008, 42, 42], f16), T([336, 1008, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 165, 165], f16), T([16, 96, 165, 165], f16), T([42, 96, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 83, 83], f16), T([16, 42, 169, 169], f16), T([42, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 42, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 83, 83], f16), T([16, 42, 83, 83], f16), T([42, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 42, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 83, 83], f16), T([16, 42, 83, 83], f16), T([42, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 42, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 83, 83], f16), T([16, 42, 83, 83], f16), T([42, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 42, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 83, 83], f16), T([16, 42, 83, 83], f16), T([42, 42, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 83, 83], f16), T([16, 96, 83, 83], f16), T([42, 96, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 42, 83, 83], f16, stride=(578676, 6889, 83, 1)), T([16, 96, 83, 83], f16), T([42, 96, 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, 432, 11, 11], f16, stride=(104544, 121, 11, 1)), T([16, 2160, 11, 11], f16), T([432, 2160, 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, 432, 21, 21], f16), T([16, 2160, 21, 21], f16), T([432, 2160, 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, 432, 21, 21], f16), T([16, 432, 21, 21], f16), T([432, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 432, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 432, 21, 21], f16), T([16, 432, 21, 21], f16), T([432, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 432, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 432, 21, 21], f16), T([16, 432, 21, 21], f16), T([432, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 432, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 432, 21, 21], f16), T([16, 432, 21, 21], f16), T([432, 432, 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, 432, 21, 21], f16), T([16, 432, 42, 42], f16), T([432, 432, 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, 432, 21, 21], f16), T([16, 432, 43, 43], f16), T([432, 1, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 432, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 432, 21, 21], f16), T([16, 432, 45, 45], f16), T([432, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 432, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 432, 21, 21], f16), T([16, 432, 47, 47], f16), T([432, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 432, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 432, 42, 42], f16), T([16, 1080, 42, 42], f16), T([432, 1080, 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, 512, 7, 7], f16), T([16, 256, 14, 14], f16), T([512, 256, 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, 512, 7, 7], f16), T([16, 256, 14, 14], f16), T([512, 256, 3, 3], f16), [0], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/resnet18
((T([16, 512, 7, 7], f16), T([16, 512, 7, 7], f16), T([512, 512, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 54, 165, 165], f16), T([16, 96, 165, 165], f16), T([54, 96, 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, 54, 83, 83], f16), T([16, 54, 165, 165], f16), T([54, 54, 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, 54, 83, 83], f16), T([16, 54, 167, 167], f16), T([54, 1, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 54, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 54, 83, 83], f16), T([16, 54, 169, 169], f16), T([54, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 54, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 54, 83, 83], f16), T([16, 54, 171, 171], f16), T([54, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 54, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 54, 83, 83], f16), T([16, 54, 83, 83], f16), T([54, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 54, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 54, 83, 83], f16), T([16, 54, 83, 83], f16), T([54, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 54, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 54, 83, 83], f16), T([16, 54, 83, 83], f16), T([54, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 54, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 54, 83, 83], f16), T([16, 54, 83, 83], f16), T([54, 54, 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, 54, 83, 83], f16), T([16, 96, 83, 83], f16), T([54, 96, 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, 54, 83, 83], f16, stride=(744012, 6889, 83, 1)), T([16, 96, 83, 83], f16), T([54, 96, 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, 64, 112, 112], f16), T([16, 3, 224, 224], f16), T([64, 3, 7, 7], f16), [0], [2, 2], [3, 3], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TorchBench/pytorch_stargan
((T([16, 64, 128, 128], f16), T([16, 128, 64, 64], f16), T([128, 64, 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, 64, 128, 128], f16), T([16, 8, 128, 128], f16), T([64, 8, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TorchBench/resnet18
((T([16, 64, 56, 56], f16), T([16, 64, 56, 56], f16), T([64, 64, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 2688, 11, 11], f16), T([672, 2688, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 4032, 11, 11], f16), T([672, 4032, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 672, 11, 11], f16), T([672, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 672, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 672, 11, 11], f16), T([672, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 672, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 672, 11, 11], f16), T([672, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 672, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 672, 11, 11], f16), T([672, 672, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 672, 25, 25], f16), T([672, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 672, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 11, 11], f16), T([16, 672, 27, 27], f16), T([672, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 672, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 672, 21, 21], f16), T([16, 2016, 21, 21], f16), T([672, 2016, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16), T([16, 84, 42, 42], f16), T([84, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 84, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16), T([16, 84, 42, 42], f16), T([84, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 84, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16), T([16, 84, 42, 42], f16), T([84, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 84, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16), T([16, 84, 42, 42], f16), T([84, 84, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16), T([16, 84, 87, 87], f16), T([84, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 84, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16), T([16, 84, 89, 89], f16), T([84, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 84, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 42, 42], f16, stride=(296352, 1764, 42, 1)), T([16, 168, 42, 42], f16), T([84, 168, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 84, 83, 83], f16), T([16, 168, 83, 83], f16), T([84, 168, 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, 864, 11, 11], f16), T([16, 4320, 11, 11], f16), T([864, 4320, 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, 864, 11, 11], f16), T([16, 864, 11, 11], f16), T([864, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 864, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 864, 11, 11], f16), T([16, 864, 11, 11], f16), T([864, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 864, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 864, 11, 11], f16), T([16, 864, 11, 11], f16), T([864, 1, 7, 7], f16), [0], [1, 1], [3, 3], [1, 1], False, [0, 0], 864, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 864, 11, 11], f16), T([16, 864, 11, 11], f16), T([864, 864, 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, 864, 11, 11], f16), T([16, 864, 21, 21], f16), T([864, 864, 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, 864, 11, 11], f16), T([16, 864, 23, 23], f16), T([864, 1, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 864, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 864, 11, 11], f16), T([16, 864, 25, 25], f16), T([864, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 864, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 864, 11, 11], f16), T([16, 864, 27, 27], f16), T([864, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 864, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 864, 21, 21], f16), T([16, 2160, 21, 21], f16), T([864, 2160, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 96, 165, 165], f16), T([16, 3, 331, 331], f16), T([96, 3, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 96, 165, 165], f16), T([16, 3, 331, 331], f16), T([96, 3, 3, 3], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [False, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 96, 83, 83], f16), T([16, 96, 167, 167], 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/nasnetalarge
((T([16, 96, 83, 83], f16), T([16, 96, 169, 169], f16), T([96, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/pnasnet5large
((T([16, 96, 83, 83], f16), T([16, 96, 169, 169], f16), T([96, 1, 5, 5], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/nasnetalarge
((T([16, 96, 83, 83], f16), T([16, 96, 171, 171], f16), T([96, 1, 7, 7], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 96, [True, True, False]), {})
aten.convolution_backward.default
TIMM/cait_m36_384
((T([2, 768, 24, 24], f16, stride=(442368, 1, 18432, 768)), T([2, 3, 384, 384], f16), T([768, 3, 16, 16], f16), [768], [16, 16], [0, 0], [1, 1], False, [0, 0], 1, [False, True, True]), {})
aten.convolution_backward.default
TorchBench/Background_Matting
((T([3, 1, 512, 512], f16), T([3, 64, 518, 518], f16), T([1, 64, 7, 7], f16), [1], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})