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#include <torch/torch.h> |
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#include <vector> |
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std::vector<float*> dynamicconv_cpu_forward( |
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float* input, |
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float* filters, |
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int padding_l); |
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std::vector<float*> dynamicconv_cpu_backward( |
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float* gradOutput, |
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int padding_l, |
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float* input, |
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float* filters); |
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std::vector<float*> dynamicconv_forward( |
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float* input, |
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float* filters, |
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int padding_l) { |
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return dynamicconv_cpu_forward(input, filters, padding_l); |
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} |
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std::vector<float*> dynamicconv_backward( |
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float* gradOutput, |
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int padding_l, |
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float* input, |
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float* filters) { |
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return dynamicconv_cpu_backward(gradOutput, padding_l, input, filters); |
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} |
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { |
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m.def("forward", &dynamicconv_forward, "dynamicconv forward (CPU)"); |
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m.def("backward", &dynamicconv_backward, "dynamicconv backward (CPU)"); |
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} |
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