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(backbone): GenEfficientNet(
(conv_stem): Conv2dSame(3, 48, kernel_size=(3, 3), stride=(2, 2), bias=False)
(bn1): InPlaceABN(48, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act1): Identity()
(blocks): Sequential(
(0): Sequential(
(0): DepthwiseSeparableConv(
(conv_dw): Conv2d(48, 48, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=48, bias=False)
(bn1): InPlaceABN(48, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act1): Identity()
(se): Identity()
(conv_pw): Conv2d(48, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn2): InPlaceABN(24, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
)
(1): DepthwiseSeparableConv(
(conv_dw): Conv2d(24, 24, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=24, bias=False)
(bn1): InPlaceABN(24, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act1): Identity()
(se): Identity()
(conv_pw): Conv2d(24, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn2): InPlaceABN(24, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
)
(2): DepthwiseSeparableConv(
(conv_dw): Conv2d(24, 24, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=24, bias=False)
(bn1): InPlaceABN(24, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act1): Identity()
(se): Identity()
(conv_pw): Conv2d(24, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn2): InPlaceABN(24, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
)
)
(1): Sequential(
(0): InvertedResidual(
(conv_pw): Conv2d(24, 144, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(144, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2dSame(144, 144, kernel_size=(3, 3), stride=(2, 2), groups=144, bias=False)
(bn2): InPlaceABN(144, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(144, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(40, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(1): InvertedResidual(
(conv_pw): Conv2d(40, 240, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(240, 240, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=240, bias=False)
(bn2): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(240, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(40, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(2): InvertedResidual(
(conv_pw): Conv2d(40, 240, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(240, 240, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=240, bias=False)
(bn2): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(240, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(40, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(3): InvertedResidual(
(conv_pw): Conv2d(40, 240, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(240, 240, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=240, bias=False)
(bn2): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(240, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(40, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(4): InvertedResidual(
(conv_pw): Conv2d(40, 240, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(240, 240, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=240, bias=False)
(bn2): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(240, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(40, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
)
(2): Sequential(
(0): InvertedResidual(
(conv_pw): Conv2d(40, 240, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2dSame(240, 240, kernel_size=(5, 5), stride=(2, 2), groups=240, bias=False)
(bn2): InPlaceABN(240, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(240, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(64, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(1): InvertedResidual(
(conv_pw): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(384, 384, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=384, bias=False)
(bn2): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(64, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(2): InvertedResidual(
(conv_pw): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(384, 384, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=384, bias=False)
(bn2): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(64, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(3): InvertedResidual(
(conv_pw): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(384, 384, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=384, bias=False)
(bn2): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(64, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(4): InvertedResidual(
(conv_pw): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(384, 384, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=384, bias=False)
(bn2): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(64, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
)
(3): Sequential(
(0): InvertedResidual(
(conv_pw): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2dSame(384, 384, kernel_size=(3, 3), stride=(2, 2), groups=384, bias=False)
(bn2): InPlaceABN(384, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(128, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(1): InvertedResidual(
(conv_pw): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(768, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=768, bias=False)
(bn2): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(128, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(2): InvertedResidual(
(conv_pw): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(768, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=768, bias=False)
(bn2): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(128, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(3): InvertedResidual(
(conv_pw): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(768, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=768, bias=False)
(bn2): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(128, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(4): InvertedResidual(
(conv_pw): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(768, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=768, bias=False)
(bn2): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(128, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(5): InvertedResidual(
(conv_pw): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(768, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=768, bias=False)
(bn2): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(128, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(6): InvertedResidual(
(conv_pw): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(768, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=768, bias=False)
(bn2): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(128, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
)
(4): Sequential(
(0): InvertedResidual(
(conv_pw): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(768, 768, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=768, bias=False)
(bn2): InPlaceABN(768, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(768, 176, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(176, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(1): InvertedResidual(
(conv_pw): Conv2d(176, 1056, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1056, 1056, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1056, bias=False)
(bn2): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1056, 176, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(176, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(2): InvertedResidual(
(conv_pw): Conv2d(176, 1056, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1056, 1056, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1056, bias=False)
(bn2): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1056, 176, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(176, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(3): InvertedResidual(
(conv_pw): Conv2d(176, 1056, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1056, 1056, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1056, bias=False)
(bn2): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1056, 176, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(176, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(4): InvertedResidual(
(conv_pw): Conv2d(176, 1056, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1056, 1056, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1056, bias=False)
(bn2): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1056, 176, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(176, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(5): InvertedResidual(
(conv_pw): Conv2d(176, 1056, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1056, 1056, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1056, bias=False)
(bn2): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1056, 176, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(176, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(6): InvertedResidual(
(conv_pw): Conv2d(176, 1056, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1056, 1056, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1056, bias=False)
(bn2): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1056, 176, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(176, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
)
(5): Sequential(
(0): InvertedResidual(
(conv_pw): Conv2d(176, 1056, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2dSame(1056, 1056, kernel_size=(5, 5), stride=(2, 2), groups=1056, bias=False)
(bn2): InPlaceABN(1056, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1056, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(1): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(2): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(3): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(4): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(5): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(6): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(7): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(8): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 304, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(304, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
)
(6): Sequential(
(0): InvertedResidual(
(conv_pw): Conv2d(304, 1824, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(1824, 1824, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1824, bias=False)
(bn2): InPlaceABN(1824, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(1824, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(512, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(1): InvertedResidual(
(conv_pw): Conv2d(512, 3072, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(3072, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(3072, 3072, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=3072, bias=False)
(bn2): InPlaceABN(3072, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(3072, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(512, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
(2): InvertedResidual(
(conv_pw): Conv2d(512, 3072, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): InPlaceABN(3072, eps=0.001, momentum=0.1, affine=True, activation=identity)
(act1): LeakyReLU(negative_slope=0.01)
(conv_dw): Conv2d(3072, 3072, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=3072, bias=False)
(bn2): InPlaceABN(3072, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
(se): Identity()
(conv_pwl): Conv2d(3072, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): InPlaceABN(512, eps=0.001, momentum=0.1, affine=True, activation=identity)
)
)
)
(conv_head): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn2): InPlaceABN(2048, eps=0.001, momentum=0.1, affine=True, activation=leaky_relu[0.01])
(act2): Identity()
)
(neck): TWOWAYFPN(
(lateral_convs_top): ModuleList(
(0): ConvModule(
(conv): Conv2d(40, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(1): ConvModule(
(conv): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(2): ConvModule(
(conv): Conv2d(176, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(3): ConvModule(
(conv): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(lateral_convs_bottom): ModuleList(
(0): ConvModule(
(conv): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(1): ConvModule(
(conv): Conv2d(176, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(2): ConvModule(
(conv): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(3): ConvModule(
(conv): Conv2d(40, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(fpn_convs): ModuleList(
(0): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(1): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(2): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(3): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
(rpn_head): RPNHead(
(loss_cls): CrossEntropyLoss()
(loss_bbox): SmoothL1Loss()
(rpn_conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(rpn_cls): Conv2d(256, 3, kernel_size=(1, 1), stride=(1, 1))
(rpn_reg): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1))
)
(bbox_roi_extractor): SingleRoIExtractor(
(roi_layers): ModuleList(
(0): RoIAlign(out_size=(7, 7), spatial_scale=0.25, sample_num=2, use_torchvision=False, aligned=False)
(1): RoIAlign(out_size=(7, 7), spatial_scale=0.125, sample_num=2, use_torchvision=False, aligned=False)
(2): RoIAlign(out_size=(7, 7), spatial_scale=0.0625, sample_num=2, use_torchvision=False, aligned=False)
(3): RoIAlign(out_size=(7, 7), spatial_scale=0.03125, sample_num=2, use_torchvision=False, aligned=False)
)
)
(bbox_head): SharedFCBBoxHead(
(loss_cls): CrossEntropyLoss()
(loss_bbox): SmoothL1Loss()
(fc_cls): Linear(in_features=1024, out_features=9, bias=True)
(fc_reg): Linear(in_features=1024, out_features=36, bias=True)
(shared_convs): ModuleList()
(shared_fcs): ModuleList(
(0): Linear(in_features=12544, out_features=1024, bias=True)
(1): Linear(in_features=1024, out_features=1024, bias=True)
)
(cls_convs): ModuleList()
(cls_fcs): ModuleList()
(reg_convs): ModuleList()
(reg_fcs): ModuleList()
(relu): ReLU(inplace=True)
)
(mask_roi_extractor): SingleRoIExtractor(
(roi_layers): ModuleList(
(0): RoIAlign(out_size=(14, 14), spatial_scale=0.25, sample_num=2, use_torchvision=False, aligned=False)
(1): RoIAlign(out_size=(14, 14), spatial_scale=0.125, sample_num=2, use_torchvision=False, aligned=False)
(2): RoIAlign(out_size=(14, 14), spatial_scale=0.0625, sample_num=2, use_torchvision=False, aligned=False)
(3): RoIAlign(out_size=(14, 14), spatial_scale=0.03125, sample_num=2, use_torchvision=False, aligned=False)
)
)
(mask_head): FCNSepMaskHead(
(loss_mask): CrossEntropyLoss()
(convs): ModuleList(
(0): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(2): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(3): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
(upsample): ConvTranspose2d(256, 256, kernel_size=(2, 2), stride=(2, 2))
(conv_logits): Conv2d(256, 9, kernel_size=(1, 1), stride=(1, 1))
(relu): ReLU(inplace=True)
)
(semantic_head): EfficientPSSemanticHead(
(lateral_convs_ss): ModuleList(
(0): DPC(
(convs): ModuleList(
(0): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 6), dilation=(1, 6), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(2): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(6, 21), dilation=(6, 21), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(3): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(18, 15), dilation=(18, 15), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(4): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(6, 3), dilation=(6, 3), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
(conv): ConvModule(
(conv): Conv2d(1280, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DPC(
(convs): ModuleList(
(0): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 6), dilation=(1, 6), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(2): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(6, 21), dilation=(6, 21), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(3): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(18, 15), dilation=(18, 15), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(4): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(6, 3), dilation=(6, 3), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
(conv): ConvModule(
(conv): Conv2d(1280, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
(lateral_convs_ls): ModuleList(
(0): LSFE(
(convs): Sequential(
(0): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
)
(1): LSFE(
(convs): Sequential(
(0): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256, bias=False)
(bn): InPlaceABN(256, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
)
)
(aligning_convs): ModuleList(
(0): MC(
(convs): Sequential(
(0): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
)
(1): MC(
(convs): Sequential(
(0): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
(1): DepthwiseSeparableConvModule(
(depthwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
(pointwise_conv): ConvModule(
(conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn): InPlaceABN(128, eps=1e-05, momentum=0.1, affine=True, activation=leaky_relu[0.01])
)
)
)
)
)
(conv_logits): Conv2d(512, 19, kernel_size=(1, 1), stride=(1, 1))
(criterion): CrossEntropyLoss()
)
) |