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NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[3] -> {Minus, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[4] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[3]}, NeuralNetworks`Private`ScalarSymbol[5] -> {Times, -0.1, NeuralNetworks`Private`ScalarSymbol[4]}, NeuralNetworks`Private`ScalarSymbol[6] -> {Plus, NeuralNetworks`Private`ScalarSymbol[2], NeuralNetworks`Private`ScalarSymbol[5]}]]], "$Dimensions" -> {1024, 19, 19}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{1024, 19, 19}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{1024, 19, 19}, NeuralNetworks`RealT]]], "out1" -> Association[ "Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{1818, 1024, 1, 1}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Nullable[ NeuralNetworks`TensorT[{1818}, NeuralNetworks`RealT]]], "Parameters" -> Association["OutputChannels" -> 1818, "KernelSize" -> {1, 1}, "Stride" -> {1, 1}, "PaddingSize" -> {{0, 0}, {0, 0}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 1024, "$InputSize" -> {19, 19}, "$OutputSize" -> {19, 19}, "$WeightsInputChannels" -> 1024], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{1024, 19, 19}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{1818, 19, 19}, NeuralNetworks`RealT]]], "conv_block_1_1_conv" -> Association[ "Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{256, 512, 1, 1}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Private`DummyArray[{256}]], "Parameters" -> Association["OutputChannels" -> 256, "KernelSize" -> {1, 1}, "Stride" -> {1, 1}, "PaddingSize" -> {{0, 0}, {0, 0}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 512, "$InputSize" -> {19, 19}, "$OutputSize" -> {19, 19}, 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"Elementwise", "Arrays" -> Association[], "Parameters" -> Association["Function" -> NeuralNetworks`ValidatedParameter[ NeuralNetworks`Private`ScalarFunctionObject[{ NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[6], Association[ NeuralNetworks`Private`ScalarSymbol[2] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[3] -> {Minus, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[4] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[3]}, NeuralNetworks`Private`ScalarSymbol[5] -> {Times, -0.1, NeuralNetworks`Private`ScalarSymbol[4]}, NeuralNetworks`Private`ScalarSymbol[6] -> {Plus, NeuralNetworks`Private`ScalarSymbol[2], NeuralNetworks`Private`ScalarSymbol[5]}]]], "$Dimensions" -> {256, 19, 19}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 19, 19}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 19, 19}, NeuralNetworks`RealT]]], "deconv1" -> Association[ "Type" -> "Deconvolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{256, 256, 2, 2}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Nullable[ NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT]]], "Parameters" -> Association["OutputChannels" -> 256, "KernelSize" -> {2, 2}, "Stride" -> {2, 2}, "PaddingSize" -> {{0, 0}, {0, 0}}, "Dimensionality" -> 2, "Interleaving" -> False, "ChannelGroups" -> 1, "$Dilation" -> {1, 1}, "$InputChannels" -> 256, "$InputSize" -> {19, 19}, "$OutputSize" -> {38, 38}, "$WeightsOutputChannels" -> 256], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 19, 19}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "concat1" -> Association[ "Type" -> "Catenate", "Arrays" -> Association[], "Parameters" -> Association["Level" -> 1], "Inputs" -> Association["1" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT], "2" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{768, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2" -> Association[ "Type" -> "Chain", "Nodes" -> Association["conv_block_2_1_conv" -> Association["Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{256, 768, 1, 1}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Private`DummyArray[{256}]], "Parameters" -> Association["OutputChannels" -> 256, "KernelSize" -> {1, 1}, "Stride" -> {1, 1}, "PaddingSize" -> {{0, 0}, {0, 0}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 768, "$InputSize" -> {38, 38}, "$OutputSize" -> {38, 38}, "$WeightsInputChannels" -> 768], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{768, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_1_bn" -> Association["Type" -> "BatchNormalization", "Arrays" -> Association["Scaling" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "MovingMean" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "MovingVariance" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT]], "Parameters" -> Association["Momentum" -> 0.9, "Epsilon" -> 0.00001, "Interleaving" -> False, "$Channels" -> 256, "$SpatialDimensions" -> {38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_1_lReLu" -> Association["Type" -> "Elementwise", "Arrays" -> Association[], "Parameters" -> Association["Function" -> NeuralNetworks`ValidatedParameter[ NeuralNetworks`Private`ScalarFunctionObject[{ NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[6], Association[ NeuralNetworks`Private`ScalarSymbol[2] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[3] -> {Minus, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[4] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[3]}, NeuralNetworks`Private`ScalarSymbol[5] -> {Times, -0.1, NeuralNetworks`Private`ScalarSymbol[4]}, NeuralNetworks`Private`ScalarSymbol[6] -> {Plus, NeuralNetworks`Private`ScalarSymbol[2], NeuralNetworks`Private`ScalarSymbol[5]}]]], "$Dimensions" -> {256, 38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_2_conv" -> Association["Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{512, 256, 3, 3}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Private`DummyArray[{512}]], "Parameters" -> Association["OutputChannels" -> 512, "KernelSize" -> {3, 3}, "Stride" -> {1, 1}, "PaddingSize" -> {{1, 1}, {1, 1}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 256, "$InputSize" -> {38, 38}, "$OutputSize" -> {38, 38}, "$WeightsInputChannels" -> 256], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_2_bn" -> Association["Type" -> "BatchNormalization", "Arrays" -> Association["Scaling" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT], "MovingMean" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT], "MovingVariance" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT]], "Parameters" -> Association["Momentum" -> 0.9, "Epsilon" -> 0.00001, "Interleaving" -> False, "$Channels" -> 512, "$SpatialDimensions" -> {38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_2_lReLu" -> Association["Type" -> "Elementwise", "Arrays" -> Association[], "Parameters" -> Association["Function" -> NeuralNetworks`ValidatedParameter[ NeuralNetworks`Private`ScalarFunctionObject[{ NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[6], Association[ NeuralNetworks`Private`ScalarSymbol[2] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[3] -> {Minus, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[4] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[3]}, NeuralNetworks`Private`ScalarSymbol[5] -> {Times, -0.1, NeuralNetworks`Private`ScalarSymbol[4]}, NeuralNetworks`Private`ScalarSymbol[6] -> {Plus, NeuralNetworks`Private`ScalarSymbol[2], NeuralNetworks`Private`ScalarSymbol[5]}]]], "$Dimensions" -> {512, 38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_3_conv" -> Association["Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{256, 512, 1, 1}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Private`DummyArray[{256}]], "Parameters" -> Association["OutputChannels" -> 256, "KernelSize" -> {1, 1}, "Stride" -> {1, 1}, "PaddingSize" -> {{0, 0}, {0, 0}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 512, "$InputSize" -> {38, 38}, "$OutputSize" -> {38, 38}, "$WeightsInputChannels" -> 512], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_3_bn" -> Association["Type" -> "BatchNormalization", "Arrays" -> Association["Scaling" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "MovingMean" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "MovingVariance" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT]], "Parameters" -> Association["Momentum" -> 0.9, "Epsilon" -> 0.00001, "Interleaving" -> False, "$Channels" -> 256, "$SpatialDimensions" -> {38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_3_lReLu" -> Association["Type" -> "Elementwise", "Arrays" -> Association[], "Parameters" -> Association["Function" -> NeuralNetworks`ValidatedParameter[ NeuralNetworks`Private`ScalarFunctionObject[{ NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[6], Association[ NeuralNetworks`Private`ScalarSymbol[2] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[3] -> {Minus, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[4] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[3]}, NeuralNetworks`Private`ScalarSymbol[5] -> {Times, -0.1, NeuralNetworks`Private`ScalarSymbol[4]}, NeuralNetworks`Private`ScalarSymbol[6] -> {Plus, NeuralNetworks`Private`ScalarSymbol[2], NeuralNetworks`Private`ScalarSymbol[5]}]]], "$Dimensions" -> {256, 38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_4_conv" -> Association["Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{512, 256, 3, 3}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Private`DummyArray[{512}]], "Parameters" -> Association["OutputChannels" -> 512, "KernelSize" -> {3, 3}, "Stride" -> {1, 1}, "PaddingSize" -> {{1, 1}, {1, 1}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 256, "$InputSize" -> {38, 38}, "$OutputSize" -> {38, 38}, "$WeightsInputChannels" -> 256], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_4_bn" -> Association["Type" -> "BatchNormalization", "Arrays" -> Association["Scaling" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT], "MovingMean" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT], "MovingVariance" -> NeuralNetworks`TensorT[{512}, NeuralNetworks`RealT]], "Parameters" -> Association["Momentum" -> 0.9, "Epsilon" -> 0.00001, "Interleaving" -> False, "$Channels" -> 512, "$SpatialDimensions" -> {38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_4_lReLu" -> Association["Type" -> "Elementwise", "Arrays" -> Association[], "Parameters" -> Association["Function" -> NeuralNetworks`ValidatedParameter[ NeuralNetworks`Private`ScalarFunctionObject[{ NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[6], Association[ NeuralNetworks`Private`ScalarSymbol[2] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[3] -> {Minus, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[4] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[3]}, NeuralNetworks`Private`ScalarSymbol[5] -> {Times, -0.1, NeuralNetworks`Private`ScalarSymbol[4]}, NeuralNetworks`Private`ScalarSymbol[6] -> {Plus, NeuralNetworks`Private`ScalarSymbol[2], NeuralNetworks`Private`ScalarSymbol[5]}]]], "$Dimensions" -> {512, 38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_5_conv" -> Association["Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{256, 512, 1, 1}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Private`DummyArray[{256}]], "Parameters" -> Association["OutputChannels" -> 256, "KernelSize" -> {1, 1}, "Stride" -> {1, 1}, "PaddingSize" -> {{0, 0}, {0, 0}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 512, "$InputSize" -> {38, 38}, "$OutputSize" -> {38, 38}, "$WeightsInputChannels" -> 512], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{512, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_5_bn" -> Association["Type" -> "BatchNormalization", "Arrays" -> Association["Scaling" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "MovingMean" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT], "MovingVariance" -> NeuralNetworks`TensorT[{256}, NeuralNetworks`RealT]], "Parameters" -> Association["Momentum" -> 0.9, "Epsilon" -> 0.00001, "Interleaving" -> False, "$Channels" -> 256, "$SpatialDimensions" -> {38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_5_lReLu" -> Association["Type" -> "Elementwise", "Arrays" -> Association[], "Parameters" -> Association["Function" -> NeuralNetworks`ValidatedParameter[ NeuralNetworks`Private`ScalarFunctionObject[{ NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[6], Association[ NeuralNetworks`Private`ScalarSymbol[2] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[3] -> {Minus, NeuralNetworks`Private`ScalarSymbol[1]}, NeuralNetworks`Private`ScalarSymbol[4] -> {Ramp, NeuralNetworks`Private`ScalarSymbol[3]}, NeuralNetworks`Private`ScalarSymbol[5] -> {Times, -0.1, NeuralNetworks`Private`ScalarSymbol[4]}, NeuralNetworks`Private`ScalarSymbol[6] -> {Plus, NeuralNetworks`Private`ScalarSymbol[2], NeuralNetworks`Private`ScalarSymbol[5]}]]], "$Dimensions" -> {256, 38, 38}], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]]], "Edges" -> {NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath["Inputs", "Input"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_3_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_3_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_3_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_3_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_3_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_4_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_3_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_4_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_4_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_4_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_4_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_5_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_4_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_5_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_5_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_5_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_5_bn", "Outputs", "Output"], NeuralNetworks`NetPath["Outputs", "Output"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_5_lReLu", "Outputs", "Output"]}, "Inputs" -> Association[ "Input" -> NeuralNetworks`TensorT[{768, 38, 38}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 38, 38}, NeuralNetworks`RealT]]], "conv_block_2_2_conv" -> Association[ "Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{512, 256, 3, 3}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Private`DummyArray[{512}]], "Parameters" -> Association["OutputChannels" -> 512, "KernelSize" -> {3, 3}, "Stride" -> {1, 1}, "PaddingSize" -> {{1, 1}, {1, 1}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, 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"Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_3_5_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_3_6_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_3_5_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_3_6_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_3_6_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_3_6_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_3_6_bn", "Outputs", "Output"], NeuralNetworks`NetPath["Outputs", "Output"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_3_6_lReLu", "Outputs", "Output"]}, "Inputs" -> Association[ "Input" -> NeuralNetworks`TensorT[{384, 76, 76}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{256, 76, 76}, NeuralNetworks`RealT]]], "out3" -> Association[ "Type" -> "Convolution", "Arrays" -> Association["Weights" -> NeuralNetworks`TensorT[{1818, 256, 1, 1}, NeuralNetworks`RealT], "Biases" -> NeuralNetworks`Nullable[ NeuralNetworks`TensorT[{1818}, NeuralNetworks`RealT]]], "Parameters" -> Association["OutputChannels" -> 1818, "KernelSize" -> {1, 1}, "Stride" -> {1, 1}, "PaddingSize" -> {{0, 0}, {0, 0}}, "Dilation" -> {1, 1}, "ChannelGroups" -> 1, "Dimensionality" -> 2, "Interleaving" -> False, "$InputChannels" -> 256, "$InputSize" -> {76, 76}, "$OutputSize" -> {76, 76}, "$WeightsInputChannels" -> 256], "Inputs" -> Association["Input" -> NeuralNetworks`TensorT[{256, 76, 76}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{1818, 76, 76}, NeuralNetworks`RealT]]]], "Edges" -> { NeuralNetworks`NetPath[ "Nodes", "conv1_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath["Inputs", "Input"], NeuralNetworks`NetPath[ "Nodes", "conv1_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv1_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv1_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv1_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv1_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res2a", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res2b_1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res2a", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3a", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res2b_1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3b_1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3a", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3b_2", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3b_3", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3b_4", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_3", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3b_5", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_4", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3b_6", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_5", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res3b_7", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_6", "Outputs", "Output"], NeuralNetworks`NetPath["Nodes", "concat2", "Inputs", "2"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_7", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4a", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res3b_7", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4b_1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4a", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4b_2", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4b_3", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4b_4", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_3", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4b_5", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_4", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4b_6", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_5", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res4b_7", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_6", "Outputs", "Output"], NeuralNetworks`NetPath["Nodes", "concat1", "Inputs", "2"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_7", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res5a", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res4b_7", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res5b_1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res5a", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res5b_2", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res5b_1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "res5b_3", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res5b_2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "res5b_3", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_1_1_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_1_2_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_1_2_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1_2_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_1_2_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1_2_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "out1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1_2_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath["Outputs", "Output1"] -> NeuralNetworks`NetPath[ "Nodes", "out1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_1_1_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1_1_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_1_1_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1_1_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "deconv1", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_1_1_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath["Nodes", "concat1", "Inputs", "1"] -> NeuralNetworks`NetPath[ "Nodes", "deconv1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "concat1", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_conv", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "out2", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_2_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath["Outputs", "Output2"] -> NeuralNetworks`NetPath[ "Nodes", "out2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_bn", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_conv", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_lReLu", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_bn", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "deconv2", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_2_1_lReLu", "Outputs", "Output"], NeuralNetworks`NetPath["Nodes", "concat2", "Inputs", "1"] -> NeuralNetworks`NetPath[ "Nodes", "deconv2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "conv_block_3", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "concat2", "Outputs", "Output"], NeuralNetworks`NetPath[ "Nodes", "out3", "Inputs", "Input"] -> NeuralNetworks`NetPath[ "Nodes", "conv_block_3", "Outputs", "Output"], NeuralNetworks`NetPath["Outputs", "Output3"] -> NeuralNetworks`NetPath[ "Nodes", "out3", "Outputs", "Output"]}], "Decoder" -> Association[ "Type" -> 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Association["Type" -> "Flatten", "Arrays" -> Association[], "Parameters" -> Association["Level" -> 2], "Inputs" -> Association[ "Input" -> NeuralNetworks`TensorT[{38, 38, 3, 601}, NeuralNetworks`RealT]], "Outputs" -> Association["Output" -> NeuralNetworks`TensorT[{4332, 601}, NeuralNetworks`RealT]]]], "Edges" -> {NeuralNetworks`NetPath[ "Nodes", "1", "Inputs", "Input"] -> NeuralNetworks`NetPath["Inputs", "Input"], NeuralNetworks`NetPath["Nodes", "2", "Inputs", "Input"] -> NeuralNetworks`NetPath["Nodes", "1", "Outputs", "Output"], NeuralNetworks`NetPath["Nodes", "3", "Inputs", "Input"] -> NeuralNetworks`NetPath["Nodes", "2", "Outputs", "Output"], NeuralNetworks`NetPath["Nodes", "4", "Inputs", "Input"] -> NeuralNetworks`NetPath["Nodes", "3", "Outputs", "Output"], NeuralNetworks`NetPath["Nodes", "5", "Inputs", "Input"] -> NeuralNetworks`NetPath["Nodes", "4", "Outputs", "Output"], NeuralNetworks`NetPath["Outputs", "Output"] -> NeuralNetworks`NetPath[ "Nodes", "5", "Outputs", "Output"]}, 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