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aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 36, 10, 10], f16, stride=(3600, 1, 360, 36)), T([1, 88, 10, 10], f16), T([36, 88, 1, 1], f16), [36], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 36, 20, 20], f16, stride=(14400, 1, 720, 36)), T([1, 88, 20, 20], f16), T([36, 88, 1, 1], f16), [36], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 36, 40, 40], f16, stride=(57600, 1, 1440, 36)), T([1, 88, 40, 40], f16), T([36, 88, 1, 1], f16), [36], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 36, 5, 5], f16, stride=(900, 1, 180, 36)), T([1, 88, 5, 5], f16), T([36, 88, 1, 1], f16), [36], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 36, 80, 80], f16, stride=(230400, 1, 2880, 36)), T([1, 88, 80, 80], f16), T([36, 88, 1, 1], f16), [36], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
HuggingFace/YituTechConvBert
((T([1, 384, 512], f16, stride=(196608, 1, 384)), T([1, 768, 512], f16), T([384, 768, 1], f16), [0], [1], [0], [1], False, [0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 4, 1, 1], f16), T([1, 16, 1, 1], f16), T([4, 16, 1, 1], f16), [4], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 4, 1, 1], f16), T([1, 96, 1, 1], f16), T([4, 96, 1, 1], f16), [4], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 40, 80, 80], f16), T([1, 144, 80, 80], f16), T([40, 144, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 40, 80, 80], f16), T([1, 240, 80, 80], f16), T([40, 240, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 48, 1, 1], f16), T([1, 1152, 1, 1], f16), T([48, 1152, 1, 1], f16), [48], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 480, 1, 1], f16), T([1, 20, 1, 1], f16), T([480, 20, 1, 1], f16), [480], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 480, 40, 40], f16), T([1, 480, 40, 40], f16), T([480, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 480, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 480, 40, 40], f16), T([1, 480, 40, 40], f16), T([480, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 480, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 480, 40, 40], f16), T([1, 80, 40, 40], f16), T([480, 80, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 512, 40, 59], f16), T([1, 512, 40, 59], f16), T([512, 512, 3, 3], f16), [512], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 512, 80, 119], f16), T([1, 1024, 80, 119], f16), T([512, 1024, 3, 3], f16), [512], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 512, 80, 119], f16), T([1, 256, 80, 119], f16), T([512, 256, 3, 3], f16), [512], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 512, 80, 119], f16), T([1, 512, 80, 119], f16), T([512, 512, 3, 3], f16), [512], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 6, 1, 1], f16), T([1, 144, 1, 1], f16), T([6, 144, 1, 1], f16), [6], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_CycleGAN_and_pix2pix
((T([1, 64, 256, 256], f16), T([1, 128, 128, 128], f16), T([128, 64, 3, 3], f16), [64], [2, 2], [1, 1], [1, 1], True, [1, 1], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_CycleGAN_and_pix2pix
((T([1, 64, 256, 256], f16), T([1, 3, 262, 262], f16), T([64, 3, 7, 7], f16), [64], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [False, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 64, 320, 479], f16), T([1, 128, 320, 479], f16), T([64, 128, 3, 3], f16), [64], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 64, 640, 959], f16), T([1, 128, 640, 959], f16), T([64, 128, 3, 3], f16), [64], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 64, 640, 959], f16), T([1, 3, 640, 959], f16), T([64, 3, 3, 3], f16), [64], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [False, True, True]), {})
aten.convolution_backward.default
TorchBench/pytorch_unet
((T([1, 64, 640, 959], f16), T([1, 64, 640, 959], f16), T([64, 64, 3, 3], f16), [64], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 672, 1, 1], f16), T([1, 28, 1, 1], f16), T([672, 28, 1, 1], f16), [672], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 672, 20, 20], f16), T([1, 672, 43, 43], 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
TorchBench/timm_efficientdet
((T([1, 672, 40, 40], f16), T([1, 112, 40, 40], f16), T([672, 112, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 672, 40, 40], f16), T([1, 672, 40, 40], 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
HuggingFace/YituTechConvBert
((T([1, 768, 512], f16), T([1, 768, 512], f16, stride=(393216, 1, 768)), T([768, 1, 9], f16), [0], [1], [4], [1], False, [0], 768, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 8, 1, 1], f16), T([1, 32, 1, 1], f16), T([8, 32, 1, 1], f16), [8], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 80, 1, 1], f16), T([1, 1920, 1, 1], f16), T([80, 1920, 1, 1], f16), [80], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 80, 40, 40], f16), T([1, 240, 40, 40], 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
TorchBench/timm_efficientdet
((T([1, 80, 40, 40], f16), T([1, 480, 40, 40], 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
TorchBench/timm_efficientdet
((T([1, 810, 10, 10], f16, stride=(81000, 1, 8100, 810)), T([1, 88, 10, 10], f16), T([810, 88, 1, 1], f16), [810], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 810, 20, 20], f16, stride=(324000, 1, 16200, 810)), T([1, 88, 20, 20], f16), T([810, 88, 1, 1], f16), [810], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 810, 40, 40], f16, stride=(1296000, 1, 32400, 810)), T([1, 88, 40, 40], f16), T([810, 88, 1, 1], f16), [810], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 810, 5, 5], f16, stride=(20250, 1, 4050, 810)), T([1, 88, 5, 5], f16), T([810, 88, 1, 1], f16), [810], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 810, 80, 80], f16, stride=(5184000, 1, 64800, 810)), T([1, 88, 80, 80], f16), T([810, 88, 1, 1], f16), [810], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 10, 10], f16), T([1, 88, 10, 10], f16), T([88, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 88, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 10, 10], f16), T([1, 88, 10, 10], f16), T([88, 88, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 20, 20], f16), T([1, 320, 20, 20], f16), T([88, 320, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 20, 20], f16), T([1, 88, 20, 20], f16), T([88, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 88, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 20, 20], f16), T([1, 88, 20, 20], f16), T([88, 88, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 40, 40], f16), T([1, 112, 40, 40], f16), T([88, 112, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 40, 40], f16), T([1, 88, 40, 40], f16), T([88, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 88, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 40, 40], f16), T([1, 88, 40, 40], f16), T([88, 88, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 5, 5], f16), T([1, 88, 5, 5], f16), T([88, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 88, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 5, 5], f16), T([1, 88, 5, 5], f16), T([88, 88, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 80, 80], f16), T([1, 40, 80, 80], f16), T([88, 40, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 80, 80], f16), T([1, 88, 80, 80], f16), T([88, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 88, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 88, 80, 80], f16), T([1, 88, 80, 80], f16), T([88, 88, 1, 1], f16), [88], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TorchBench/timm_efficientdet
((T([1, 96, 1, 1], f16), T([1, 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
TorchBench/timm_efficientdet
((T([1, 96, 160, 160], f16), T([1, 96, 321, 321], 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
TorchBench/timm_efficientdet
((T([1, 96, 320, 320], f16), T([1, 16, 320, 320], 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/eca_botnext26ts_256
((T([128, 1, 128], f16), T([128, 1, 128], f16), T([1, 1, 5], f16), [0], [1], [2], [1], False, [0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 1, 128], f16), T([128, 1, 128], f16), T([1, 1, 5], f16), [0], [1], [2], [1], False, [0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 1, 256], f16), T([128, 1, 256], f16), T([1, 1, 5], f16), [0], [1], [2], [1], False, [0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 1, 256], f16), T([128, 1, 256], f16), T([1, 1, 5], f16), [0], [1], [2], [1], False, [0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 1, 64], f16), T([128, 1, 64], f16), T([1, 1, 3], f16), [0], [1], [1], [1], False, [0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 1, 64], f16), T([128, 1, 64], f16), T([1, 1, 3], f16), [0], [1], [1], [1], False, [0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/tf_efficientnet_b0
((T([128, 10, 1, 1], f16), T([128, 240, 1, 1], f16), T([10, 240, 1, 1], f16), [10], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/tinynet_a
((T([128, 10, 1, 1], f16), T([128, 240, 1, 1], f16), T([10, 240, 1, 1], f16), [10], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 100, 14, 14], f16), T([128, 100, 14, 14], f16), T([100, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 100, [True, True, False]), {})
aten.convolution_backward.default
TIMM/ghostnet_100
((T([128, 100, 14, 14], f16), T([128, 80, 14, 14], f16), T([100, 80, 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, 1024, 1, 1], f16), T([128, 1024, 1, 1], f16), T([1024, 1024, 1, 1], f16), [1024], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 1024, 14, 14], f16), T([128, 1024, 14, 14], f16), T([1024, 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, 1024, 14, 14], f16), T([128, 448, 14, 14], f16), T([1024, 448, 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, 1024, 14, 14], f16), T([128, 512, 14, 14], f16), T([1024, 512, 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, 1024, 14, 14], f16), T([128, 512, 28, 28], f16), T([1024, 512, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/res2next50
((T([128, 1024, 14, 14], f16), T([128, 512, 28, 28], f16), T([1024, 512, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/botnet26t_256
((T([128, 1024, 16, 16], f16), T([128, 256, 16, 16], f16), T([1024, 256, 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, 1024, 16, 16], f16), T([128, 256, 16, 16], f16), T([1024, 256, 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, 1024, 16, 16], f16), T([128, 256, 16, 16], f16), T([1024, 256, 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, 1024, 16, 16], f16), T([128, 512, 32, 32], f16), T([1024, 512, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_botnext26ts_256
((T([128, 1024, 16, 16], f16), T([128, 512, 32, 32], f16), T([1024, 512, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/eca_halonext26ts
((T([128, 1024, 16, 16], f16), T([128, 512, 32, 32], f16), T([1024, 512, 1, 1], f16), [0], [2, 2], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 1024, 4, 4], f16), T([128, 1280, 4, 4], f16), T([1024, 1280, 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, 1024, 7, 7], f16), T([128, 144, 7, 7], f16), T([1024, 144, 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, 1024, 7, 7], f16), T([128, 1440, 7, 7], f16), T([1024, 1440, 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, 1024, 7, 7], f16), T([128, 2048, 7, 7], f16), T([1024, 2048, 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, 1024, 7, 7], f16), T([128, 256, 7, 7], f16), T([1024, 256, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TorchBench/shufflenet_v2_x1_0
((T([128, 1024, 7, 7], f16), T([128, 464, 7, 7], f16), T([1024, 464, 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, 1024, 7, 7], f16), T([128, 512, 14, 14], f16), T([1024, 512, 3, 3], f16), [1024], [2, 2], [1, 1], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/selecsls42b
((T([128, 1024, 7, 7], f16), T([128, 960, 7, 7], f16), T([1024, 960, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 1044, 1, 1], f16), T([128, 87, 1, 1], f16), T([1044, 87, 1, 1], f16), [1044], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 1044, 7, 7], f16), T([128, 1044, 7, 7], f16), T([1044, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1044, [True, True, False]), {})
aten.convolution_backward.default
TIMM/rexnet_100
((T([128, 1044, 7, 7], f16), T([128, 174, 7, 7], f16), T([1044, 174, 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, 106, 14, 14], f16), T([128, 570, 14, 14], f16), T([106, 570, 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, 1104, 1, 1], f16), T([128, 48, 1, 1], f16), T([1104, 48, 1, 1], f16), [1104], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, True]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 1104, 7, 7], f16), T([128, 1104, 7, 7], f16), T([1104, 1, 3, 3], f16), [0], [1, 1], [1, 1], [1, 1], False, [0, 0], 1104, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 1104, 7, 7], f16), T([128, 1104, 7, 7], f16), T([1104, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 1104, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetv3_b
((T([128, 1104, 7, 7], f16), T([128, 1104, 7, 7], f16), T([1104, 1, 5, 5], f16), [0], [1, 1], [2, 2], [1, 1], False, [0, 0], 1104, [True, True, False]), {})
aten.convolution_backward.default
TIMM/fbnetc_100
((T([128, 1104, 7, 7], f16), T([128, 184, 7, 7], f16), T([1104, 184, 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, 1104, 7, 7], f16), T([128, 184, 7, 7], f16), T([1104, 184, 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, 112, 12, 12], f16), T([128, 480, 12, 12], f16), T([112, 480, 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, 112, 12, 12], f16), T([128, 672, 12, 12], f16), T([112, 672, 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, 112, 14, 14], f16), T([128, 336, 14, 14], f16), T([112, 336, 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, 112, 14, 14], f16), T([128, 384, 14, 14], f16), T([112, 384, 1, 1], f16), [0], [1, 1], [0, 0], [1, 1], False, [0, 0], 1, [True, True, False]), {})