// RUN: %run_test hipify "%s" "%t" %cuda_args #include #include #include #include // CHECK: #include #include // CHECK: #include "hipDNN.h" #include "cudnn.h" // CHECK: hipError_t err = (f); \ // CHECK: if (err != hipSuccess) { \ #define CUDA_CALL(f) { \ cudaError_t err = (f); \ if (err != cudaSuccess) { \ std::cout \ << " Error occurred: " << err << std::endl; \ std::exit(1); \ } \ } // CHECK: hipdnnStatus_t err = (f); \ // CHECK: if (err != HIPDNN_STATUS_SUCCESS) { \ #define CUDNN_CALL(f) { \ cudnnStatus_t err = (f); \ if (err != CUDNN_STATUS_SUCCESS) { \ std::cout \ << " Error occurred: " << err << std::endl; \ std::exit(1); \ } \ } __global__ void dev_const(float *px, float k) { int tid = threadIdx.x + blockIdx.x * blockDim.x; px[tid] = k; } __global__ void dev_iota(float *px) { int tid = threadIdx.x + blockIdx.x * blockDim.x; px[tid] = tid; } void print(const float *data, int n, int c, int h, int w) { std::vector buffer(1 << 20); // CHECK: CUDA_CALL(hipMemcpy( CUDA_CALL(cudaMemcpy( buffer.data(), data, n * c * h * w * sizeof(float), // CHECK: hipMemcpyDeviceToHost)); cudaMemcpyDeviceToHost)); int a = 0; for (int i = 0; i < n; ++i) { for (int j = 0; j < c; ++j) { std::cout << "n=" << i << ", c=" << j << ":" << std::endl; for (int k = 0; k < h; ++k) { for (int l = 0; l < w; ++l) { std::cout << std::setw(4) << std::right << buffer[a]; ++a; } std::cout << std::endl; } } } std::cout << std::endl; } int main() { // CHECK: hipdnnHandle_t cudnn; cudnnHandle_t cudnn; // CHECK: CUDNN_CALL(hipdnnCreate(&cudnn)); CUDNN_CALL(cudnnCreate(&cudnn)); // input const int in_n = 1; const int in_c = 1; const int in_h = 5; const int in_w = 5; std::cout << "in_n: " << in_n << std::endl; std::cout << "in_c: " << in_c << std::endl; std::cout << "in_h: " << in_h << std::endl; std::cout << "in_w: " << in_w << std::endl; std::cout << std::endl; // CHECK: hipdnnTensorDescriptor_t in_desc; cudnnTensorDescriptor_t in_desc; // CHECK: CUDNN_CALL(hipdnnCreateTensorDescriptor(&in_desc)); CUDNN_CALL(cudnnCreateTensorDescriptor(&in_desc)); // CHECK: CUDNN_CALL(hipdnnSetTensor4dDescriptor( CUDNN_CALL(cudnnSetTensor4dDescriptor( // CHECK: in_desc, HIPDNN_TENSOR_NCHW, HIPDNN_DATA_FLOAT, in_desc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, in_n, in_c, in_h, in_w)); float *in_data; // CHECK: CUDA_CALL(hipMalloc( CUDA_CALL(cudaMalloc( &in_data, in_n * in_c * in_h * in_w * sizeof(float))); // filter const int filt_k = 1; const int filt_c = 1; const int filt_h = 2; const int filt_w = 2; std::cout << "filt_k: " << filt_k << std::endl; std::cout << "filt_c: " << filt_c << std::endl; std::cout << "filt_h: " << filt_h << std::endl; std::cout << "filt_w: " << filt_w << std::endl; std::cout << std::endl; // CHECK: hipdnnFilterDescriptor_t filt_desc; cudnnFilterDescriptor_t filt_desc; // CHECK: CUDNN_CALL(hipdnnCreateFilterDescriptor(&filt_desc)); CUDNN_CALL(cudnnCreateFilterDescriptor(&filt_desc)); // CHECK: CUDNN_CALL(hipdnnSetFilter4dDescriptor( CUDNN_CALL(cudnnSetFilter4dDescriptor( // CHECK: filt_desc, HIPDNN_DATA_FLOAT, HIPDNN_TENSOR_NCHW, filt_desc, CUDNN_DATA_FLOAT, CUDNN_TENSOR_NCHW, filt_k, filt_c, filt_h, filt_w)); float *filt_data; // CUDA_CALL(hipMalloc( CUDA_CALL(cudaMalloc( &filt_data, filt_k * filt_c * filt_h * filt_w * sizeof(float))); // convolution const int pad_h = 1; const int pad_w = 1; const int str_h = 1; const int str_w = 1; const int dil_h = 1; const int dil_w = 1; std::cout << "pad_h: " << pad_h << std::endl; std::cout << "pad_w: " << pad_w << std::endl; std::cout << "str_h: " << str_h << std::endl; std::cout << "str_w: " << str_w << std::endl; std::cout << "dil_h: " << dil_h << std::endl; std::cout << "dil_w: " << dil_w << std::endl; std::cout << std::endl; // CHECK: hipdnnConvolutionDescriptor_t conv_desc; cudnnConvolutionDescriptor_t conv_desc; // CUDNN_CALL(hipdnnCreateConvolutionDescriptor(&conv_desc)); CUDNN_CALL(cudnnCreateConvolutionDescriptor(&conv_desc)); // CHECK: CUDNN_CALL(hipdnnSetConvolution2dDescriptor( CUDNN_CALL(cudnnSetConvolution2dDescriptor( conv_desc, pad_h, pad_w, str_h, str_w, dil_h, dil_w, // CHECK: HIPDNN_CONVOLUTION, HIPDNN_DATA_FLOAT)); CUDNN_CONVOLUTION, CUDNN_DATA_FLOAT)); // output int out_n; int out_c; int out_h; int out_w; // CHECK: CUDNN_CALL(hipdnnGetConvolution2dForwardOutputDim( CUDNN_CALL(cudnnGetConvolution2dForwardOutputDim( conv_desc, in_desc, filt_desc, &out_n, &out_c, &out_h, &out_w)); std::cout << "out_n: " << out_n << std::endl; std::cout << "out_c: " << out_c << std::endl; std::cout << "out_h: " << out_h << std::endl; std::cout << "out_w: " << out_w << std::endl; std::cout << std::endl; // CHECK: hipdnnTensorDescriptor_t out_desc; cudnnTensorDescriptor_t out_desc; // CHECK: CUDNN_CALL(hipdnnCreateTensorDescriptor(&out_desc)); CUDNN_CALL(cudnnCreateTensorDescriptor(&out_desc)); // CHECK: CUDNN_CALL(hipdnnSetTensor4dDescriptor( CUDNN_CALL(cudnnSetTensor4dDescriptor( // CHECK: out_desc, HIPDNN_TENSOR_NCHW, HIPDNN_DATA_FLOAT, out_desc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, out_n, out_c, out_h, out_w)); float *out_data; // CHECK: CUDA_CALL(hipMalloc( CUDA_CALL(cudaMalloc( &out_data, out_n * out_c * out_h * out_w * sizeof(float))); // algorithm // CHECK: hipdnnConvolutionFwdAlgo_t algo; cudnnConvolutionFwdAlgo_t algo; // CHECK: CUDNN_CALL(hipdnnGetConvolutionForwardAlgorithm( CUDNN_CALL(cudnnGetConvolutionForwardAlgorithm( cudnn, in_desc, filt_desc, conv_desc, out_desc, // CHECK: HIPDNN_CONVOLUTION_FWD_PREFER_FASTEST, 0, &algo)); CUDNN_CONVOLUTION_FWD_PREFER_FASTEST, 0, &algo)); std::cout << "Convolution algorithm: " << algo << std::endl; std::cout << std::endl; // workspace size_t ws_size; // CHECK: CUDNN_CALL(hipdnnGetConvolutionForwardWorkspaceSize( CUDNN_CALL(cudnnGetConvolutionForwardWorkspaceSize( cudnn, in_desc, filt_desc, conv_desc, out_desc, algo, &ws_size)); float *ws_data; // CHECK: CUDA_CALL(hipMalloc(&ws_data, ws_size)); CUDA_CALL(cudaMalloc(&ws_data, ws_size)); std::cout << "Workspace size: " << ws_size << std::endl; std::cout << std::endl; // perform float alpha = 1.f; float beta = 0.f; // CHECK: hipLaunchKernelGGL(dev_iota, dim3(in_w * in_h), dim3(in_n * in_c), 0, 0, in_data); // CHECK: hipLaunchKernelGGL(dev_const, dim3(filt_w * filt_h), dim3(filt_k * filt_c), 0, 0, filt_data, 1.f); dev_iota<<>>(in_data); dev_const<<>>(filt_data, 1.f); // CHECK: CUDNN_CALL(hipdnnConvolutionForward( CUDNN_CALL(cudnnConvolutionForward( cudnn, &alpha, in_desc, in_data, filt_desc, filt_data, conv_desc, algo, ws_data, ws_size, &beta, out_desc, out_data)); // results std::cout << "in_data:" << std::endl; print(in_data, in_n, in_c, in_h, in_w); std::cout << "filt_data:" << std::endl; print(filt_data, filt_k, filt_c, filt_h, filt_w); std::cout << "out_data:" << std::endl; print(out_data, out_n, out_c, out_h, out_w); // finalizing // CHECK: CUDA_CALL(hipFree(ws_data)); CUDA_CALL(cudaFree(ws_data)); // CHECK: CUDA_CALL(hipFree(out_data)); CUDA_CALL(cudaFree(out_data)); // CHECK: CUDNN_CALL(hipdnnDestroyTensorDescriptor(out_desc)); CUDNN_CALL(cudnnDestroyTensorDescriptor(out_desc)); // CHECK: CUDNN_CALL(hipdnnDestroyConvolutionDescriptor(conv_desc)); CUDNN_CALL(cudnnDestroyConvolutionDescriptor(conv_desc)); // CHECK: CUDA_CALL(hipFree(filt_data)); CUDA_CALL(cudaFree(filt_data)); // CHECK: CUDNN_CALL(hipdnnDestroyFilterDescriptor(filt_desc)); CUDNN_CALL(cudnnDestroyFilterDescriptor(filt_desc)); // CHECK: CUDA_CALL(hipFree(in_data)); CUDA_CALL(cudaFree(in_data)); // CHECK: CUDNN_CALL(hipdnnDestroyTensorDescriptor(in_desc)); CUDNN_CALL(cudnnDestroyTensorDescriptor(in_desc)); // CHECK: CUDNN_CALL(hipdnnDestroy(cudnn)); CUDNN_CALL(cudnnDestroy(cudnn)); return 0; }