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IainmonIainmon
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cpp-model-construction working for some reason.
1 parent 310fe1a commit 31fce77

25 files changed

Lines changed: 4375 additions & 3 deletions

‎demos/CMakeLists.txt‎

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@@ -3,4 +3,5 @@ add_subdirectory(video)
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# add_subdirectory(webcam_filter)
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# add_subdirectory(torchtest)
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add_subdirectory(torchtest_bridge)
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add_subdirectory(torchtest_bridge)
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‎demos/video/CMakeLists.txt‎

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@@ -99,4 +99,6 @@ add_custom_command(
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"${CMAKE_CURRENT_SOURCE_DIR}/style-transfer/models"
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"$<TARGET_FILE_DIR:StyleTransfer>/style-transfer/models"
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COMMENT "NOT! Copying ${PROJECT_ROOT_DIR}/examples/vgg/images to $<TARGET_FILE_DIR:vgg>/images"
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)
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)
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add_subdirectory(cpp-model-construction)

‎demos/video/chapel-webcam/incomplete_sunday_afternoon.model‎

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‎demos/video/chapel-webcam/model2.ipynb‎

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‎demos/video/chapel-webcam/model3.ipynb‎

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‎demos/video/chapel-webcam/net.cpp‎

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#include "transformer_net.hpp"
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int main() {
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torch::manual_seed(0);
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TransformerNet model;
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model->eval();
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// dummy input
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auto input = torch::randn({1,3,256,256});
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auto output = model->forward(input);
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std::cout << "Output shape: " << output.sizes() << "\n";
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}

‎demos/video/chapel-webcam/transformer_net.hpp‎

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// transformer_net.h
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#pragma once
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#include <torch/torch.h>
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//
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// --- ConvLayer -------------------------------------------------------------
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//
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struct ConvLayerImpl : torch::nn::Module {
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torch::nn::ReflectionPad2d reflection_pad{nullptr};
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torch::nn::Conv2d conv2d{nullptr};
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ConvLayerImpl(int64_t in_channels,
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int64_t out_channels,
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int64_t kernel_size,
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int64_t stride)
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: reflection_pad(torch::nn::ReflectionPad2dOptions(kernel_size / 2)),
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conv2d(torch::nn::Conv2dOptions(in_channels, out_channels, kernel_size)
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.stride(stride))
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{
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register_module("reflection_pad", reflection_pad);
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register_module("conv2d", conv2d);
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}
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torch::Tensor forward(torch::Tensor x) {
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x = reflection_pad->forward(x);
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x = conv2d->forward(x);
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return x;
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}
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};
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TORCH_MODULE(ConvLayer);
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//
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// --- ResidualBlock ---------------------------------------------------------
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//
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struct ResidualBlockImpl : torch::nn::Module {
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ConvLayer conv1{nullptr};
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torch::nn::InstanceNorm2d in1{nullptr};
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ConvLayer conv2{nullptr};
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torch::nn::InstanceNorm2d in2{nullptr};
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torch::nn::ReLU relu{nullptr};
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ResidualBlockImpl(int64_t channels)
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: conv1(ConvLayer(channels, channels, 3, 1)),
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in1(torch::nn::InstanceNorm2dOptions(channels).affine(true)),
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conv2(ConvLayer(channels, channels, 3, 1)),
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in2(torch::nn::InstanceNorm2dOptions(channels).affine(true)),
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relu(torch::nn::ReLUOptions(true))
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{
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register_module("conv1", conv1);
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register_module("in1", in1);
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register_module("conv2", conv2);
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register_module("in2", in2);
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register_module("relu", relu);
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}
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torch::Tensor forward(torch::Tensor x) {
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auto residual = x;
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auto out = relu->forward(in1->forward(conv1->forward(x)));
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out = in2->forward(conv2->forward(out));
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return out + residual;
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}
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};
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TORCH_MODULE(ResidualBlock);
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//
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// --- UpsampleConvLayer -----------------------------------------------------
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//
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struct UpsampleConvLayerImpl : torch::nn::Module {
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torch::nn::Upsample upsample{nullptr};
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torch::nn::ReflectionPad2d reflection_pad{nullptr};
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torch::nn::Conv2d conv2d{nullptr};
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UpsampleConvLayerImpl(int64_t in_channels,
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int64_t out_channels,
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int64_t kernel_size,
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int64_t stride,
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int64_t upsample_scale)
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: upsample(torch::nn::UpsampleOptions()
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.scale_factor(std::vector<double>{(double)upsample_scale, (double)upsample_scale})
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.mode(torch::kNearest)),
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reflection_pad(torch::nn::ReflectionPad2dOptions(kernel_size / 2)),
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conv2d(torch::nn::Conv2dOptions(in_channels, out_channels, kernel_size)
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.stride(stride))
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{
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register_module("upsample", upsample);
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register_module("reflection_pad", reflection_pad);
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register_module("conv2d", conv2d);
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}
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torch::Tensor forward(torch::Tensor x) {
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x = upsample->forward(x);
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x = reflection_pad->forward(x);
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x = conv2d->forward(x);
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return x;
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}
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};
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TORCH_MODULE(UpsampleConvLayer);
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//
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// --- TransformerNet --------------------------------------------------------
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//
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struct TransformerNetImpl : torch::nn::Module {
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ConvLayer conv1{nullptr};
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torch::nn::InstanceNorm2d in1{nullptr};
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ConvLayer conv2{nullptr};
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torch::nn::InstanceNorm2d in2{nullptr};
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ConvLayer conv3{nullptr};
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torch::nn::InstanceNorm2d in3{nullptr};
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ResidualBlock res1{nullptr}, res2{nullptr}, res3{nullptr},
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res4{nullptr}, res5{nullptr};
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UpsampleConvLayer deconv1{nullptr}, deconv2{nullptr};
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torch::nn::InstanceNorm2d in4{nullptr}, in5{nullptr};
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ConvLayer deconv3{nullptr};
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torch::nn::ReLU relu{nullptr};
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TransformerNetImpl()
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: conv1(ConvLayer( 3, 32, 9, 1)),
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in1 (torch::nn::InstanceNorm2dOptions(32).affine(true)),
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conv2(ConvLayer( 32, 64, 3, 2)),
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in2 (torch::nn::InstanceNorm2dOptions(64).affine(true)),
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conv3(ConvLayer( 64, 128, 3, 2)),
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in3 (torch::nn::InstanceNorm2dOptions(128).affine(true)),
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res1 (ResidualBlock(128)),
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res2 (ResidualBlock(128)),
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res3 (ResidualBlock(128)),
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res4 (ResidualBlock(128)),
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res5 (ResidualBlock(128)),
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deconv1(UpsampleConvLayer(128, 64, 3, 1, 2)),
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in4 (torch::nn::InstanceNorm2dOptions(64).affine(true)),
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deconv2(UpsampleConvLayer( 64, 32, 3, 1, 2)),
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in5 (torch::nn::InstanceNorm2dOptions(32).affine(true)),
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deconv3(ConvLayer( 32, 3, 9, 1)),
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relu (torch::nn::ReLUOptions(true))
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{
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register_module("conv1", conv1);
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register_module("in1", in1);
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register_module("conv2", conv2);
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register_module("in2", in2);
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register_module("conv3", conv3);
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register_module("in3", in3);
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register_module("res1", res1);
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register_module("res2", res2);
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register_module("res3", res3);
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register_module("res4", res4);
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register_module("res5", res5);
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register_module("deconv1", deconv1);
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register_module("in4", in4);
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register_module("deconv2", deconv2);
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register_module("in5", in5);
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register_module("deconv3", deconv3);
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register_module("relu", relu);
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}
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torch::Tensor forward(torch::Tensor x) {
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x = relu->forward(in1->forward(conv1->forward(x)));
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x = relu->forward(in2->forward(conv2->forward(x)));
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x = relu->forward(in3->forward(conv3->forward(x)));
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x = res1->forward(x);
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x = res2->forward(x);
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x = res3->forward(x);
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x = res4->forward(x);
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x = res5->forward(x);
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x = relu->forward(in4->forward(deconv1->forward(x)));
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x = relu->forward(in5->forward(deconv2->forward(x)));
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x = deconv3->forward(x);
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return x;
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}
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};
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TORCH_MODULE(TransformerNet);

‎demos/video/cpp-model-construction/CMakeLists.txt‎

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include(CMakePrintHelpers)
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# project(MyProject)
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# set(CMAKE_CXX_STANDARD 17)
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# list(APPEND CMAKE_PREFIX_PATH "${CMAKE_CURRENT_SOURCE_DIR}/libtorch/share/cmake")
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find_package(Torch REQUIRED)
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# find_package(OpenCV REQUIRED)
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SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++23 -lm -ldl")
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cmake_print_variables(TORCH_LIBRARIES)
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cmake_print_variables(TORCH_INCLUDE_DIRS)
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cmake_print_variables(TORCH_INSTALL_PREFIX)
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cmake_print_variables(TORCH_CXX_FLAGS)
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cmake_print_variables(TORCH_LIBRARY)
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add_executable(CPPModelConstruction ${CMAKE_CURRENT_SOURCE_DIR}/net.cpp ${CMAKE_CURRENT_SOURCE_DIR}/transformer_net.hpp)
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target_link_libraries(CPPModelConstruction ${TORCH_LIBRARIES})
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set_property(TARGET CPPModelConstruction PROPERTY CXX_STANDARD 23)
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set_property(TARGET CPPModelConstruction PROPERTY
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RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}
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)

‎demos/video/cpp-model-construction/incomplete_sunday_afternoon.model‎

6.43 MB
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