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Commit c73b8b33 authored by Olivier BICHLER's avatar Olivier BICHLER
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Improved style

parent 94866135
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Pipeline #37584 failed
Stage: build
    Stage: test
      Stage: coverage
        This commit is part of merge request !5. Comments created here will be created in the context of that merge request.
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        Inline Side-by-side
        src/operator/ConvImpl.cpp
        + 34
        − 32
        View file @ c73b8b33
        ......@@ -24,14 +24,16 @@
        template <Aidge::DimIdx_t DIM>
        void Aidge::ConvImpl_cuda<DIM>::forward() {
        const OperatorTensor& op = static_cast<const OperatorTensor&>(mOp);
        // FIXME: uncomment the following code once memory handling will work
        assert(mOp.getRawInput(0) && "missing input #0");
        assert(mOp.getRawInput(1) && "missing input #1");
        // Convert input data (no overhead if not needed!)
        const auto& input0 = std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->refCastFrom(mInput0Fallback, *std::static_pointer_cast<Tensor>(mOp.getRawOutput(0)));
        const auto& input1 = std::static_pointer_cast<Tensor>(mOp.getRawInput(1))->refCastFrom(mInput1Fallback, *std::static_pointer_cast<Tensor>(mOp.getRawOutput(0)));
        const auto& input2 = std::static_pointer_cast<Tensor>(mOp.getRawInput(2))->refCastFrom(mInput2Fallback, *std::static_pointer_cast<Tensor>(mOp.getRawOutput(0)));
        const auto& input0 = op.getInput(0)->refCastFrom(mInput0Fallback, *op.getOutput(0));
        const auto& input1 = op.getInput(1)->refCastFrom(mInput1Fallback, *op.getOutput(0));
        const auto& input2 = op.getInput(2)->refCastFrom(mInput2Fallback, *op.getOutput(0));
        // Lazy-initialize CuDNN convolution descriptor
        if (mConvDesc == nullptr) {
        ......@@ -41,14 +43,13 @@ void Aidge::ConvImpl_cuda<DIM>::forward() {
        const std::vector<int> upscales(convOp.template getAttr<ConvAttr::DilationDims>().begin(), convOp.template getAttr<ConvAttr::DilationDims>().end());
        CHECK_CUDNN_STATUS(cudnnCreateConvolutionDescriptor(&mConvDesc));
        CHECK_CUDNN_STATUS(
        cudnnSetConvolutionNdDescriptor(mConvDesc,
        DIM,
        &paddings[0],
        &strides[0],
        &upscales[0],
        CUDNN_CROSS_CORRELATION,
        DataTypeToCudnn(std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->dataType())));
        CHECK_CUDNN_STATUS(cudnnSetConvolutionNdDescriptor(mConvDesc,
        DIM,
        &paddings[0],
        &strides[0],
        &upscales[0],
        CUDNN_CROSS_CORRELATION,
        DataTypeToCudnn(op.getOutput(0)->dataType())));
        }
        // Lazy-initialize CuDNN filter descriptor
        ......@@ -57,10 +58,10 @@ void Aidge::ConvImpl_cuda<DIM>::forward() {
        CHECK_CUDNN_STATUS(cudnnCreateFilterDescriptor(&mFilterDesc));
        CHECK_CUDNN_STATUS(cudnnSetFilterNdDescriptor(mFilterDesc,
        DataTypeToCudnn(input1.dataType()),
        CUDNN_TENSOR_NCHW,
        kernels.size(),
        &kernels[0]));
        DataTypeToCudnn(input1.dataType()),
        CUDNN_TENSOR_NCHW,
        kernels.size(),
        &kernels[0]));
        }
        // Set forward algorithm and allocate the required workspace
        ......@@ -76,14 +77,14 @@ void Aidge::ConvImpl_cuda<DIM>::forward() {
        std::vector<cudnnConvolutionFwdAlgoPerf_t> returnFwdAlgo(maxAlgoIterations);
        CHECK_CUDNN_STATUS(cudnnFindConvolutionForwardAlgorithm(
        CudaContext::cudnnHandle(),
        dynamic_cast<TensorImpl_cuda_*>(input0.getImpl().get())->getCudnnTensorDesc(input0),
        mFilterDesc,
        mConvDesc,
        dynamic_cast<TensorImpl_cuda_*>(std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl().get())->getCudnnTensorDesc(*std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))),
        maxAlgoIterations,
        &returnAlgoCounts,
        &returnFwdAlgo[0]));
        CudaContext::cudnnHandle(),
        std::dynamic_pointer_cast<TensorImpl_cuda_>(input0.getImpl())->getCudnnTensorDesc(input0),
        mFilterDesc,
        mConvDesc,
        std::dynamic_pointer_cast<TensorImpl_cuda_>(op.getOutput(0)->getImpl())->getCudnnTensorDesc(*op.getOutput(0)),
        maxAlgoIterations,
        &returnAlgoCounts,
        &returnFwdAlgo[0]));
        mFwdAlgo = returnFwdAlgo[0].algo;
        // Allocate the workspace required by the chosen CuDNN forward algorithm
        ......@@ -91,10 +92,10 @@ void Aidge::ConvImpl_cuda<DIM>::forward() {
        CHECK_CUDNN_STATUS(cudnnGetConvolutionForwardWorkspaceSize(
        CudaContext::cudnnHandle(),
        dynamic_cast<TensorImpl_cuda_*>(input0.getImpl().get())->getCudnnTensorDesc(input0),
        std::dynamic_pointer_cast<TensorImpl_cuda_>(input0.getImpl())->getCudnnTensorDesc(input0),
        mFilterDesc,
        mConvDesc,
        dynamic_cast<TensorImpl_cuda_*>(std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl().get())->getCudnnTensorDesc(*std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))),
        std::dynamic_pointer_cast<TensorImpl_cuda_>(op.getOutput(0)->getImpl())->getCudnnTensorDesc(*op.getOutput(0)),
        mFwdAlgo,
        &workspaceSize));
        ......@@ -105,7 +106,7 @@ void Aidge::ConvImpl_cuda<DIM>::forward() {
        // Do the actual forward computation
        // Template is only for scaling parameters, which are always in float
        // excepted when the convolution is performed in double precision.
        if (std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->dataType() == DataType::Float64) {
        if (op.getOutput(0)->dataType() == DataType::Float64) {
        forward_<double>(input0, input1, input2);
        }
        else {
        ......@@ -116,12 +117,13 @@ void Aidge::ConvImpl_cuda<DIM>::forward() {
        template <Aidge::DimIdx_t DIM>
        template <class T>
        void Aidge::ConvImpl_cuda<DIM>::forward_(const Tensor& input0, const Tensor& input1, const Tensor& input2) {
        const OperatorTensor& op = static_cast<const OperatorTensor&>(mOp);
        const T alpha = 1.0f;
        const T beta = 0.0f;
        CHECK_CUDNN_STATUS(cudnnConvolutionForward(CudaContext::cudnnHandle(),
        &alpha,
        dynamic_cast<TensorImpl_cuda_*>(input0.getImpl().get())->getCudnnTensorDesc(input0),
        std::dynamic_pointer_cast<TensorImpl_cuda_>(input0.getImpl())->getCudnnTensorDesc(input0),
        input0.getImpl()->rawPtr(),
        mFilterDesc,
        input1.getImpl()->rawPtr(),
        ......@@ -130,8 +132,8 @@ void Aidge::ConvImpl_cuda<DIM>::forward_(const Tensor& input0, const Tensor& inp
        mFwdWorkspace,
        mWorkspaceSize,
        &beta,
        dynamic_cast<TensorImpl_cuda_*>(std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl().get())->getCudnnTensorDesc(*std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))),
        std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl()->rawPtr()));
        std::dynamic_pointer_cast<TensorImpl_cuda_>(op.getOutput(0)->getImpl())->getCudnnTensorDesc(*op.getOutput(0)),
        op.getOutput(0)->getImpl()->rawPtr()));
        // Add bias (if there is any)
        if (mOp.getRawInput(2) && input2.size() > 0) {
        ......@@ -147,11 +149,11 @@ void Aidge::ConvImpl_cuda<DIM>::forward_(const Tensor& input0, const Tensor& inp
        CHECK_CUDNN_STATUS(cudnnAddTensor(CudaContext::cudnnHandle(),
        &alpha,
        dynamic_cast<TensorImpl_cuda_*>(bias.getImpl().get())->getCudnnTensorDesc(bias),
        std::dynamic_pointer_cast<TensorImpl_cuda_>(bias.getImpl())->getCudnnTensorDesc(bias),
        input2.getImpl()->rawPtr(),
        &alpha,
        dynamic_cast<TensorImpl_cuda_*>(std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl().get())->getCudnnTensorDesc(*std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))),
        std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl()->rawPtr()));
        std::dynamic_pointer_cast<TensorImpl_cuda_>(op.getOutput(0)->getImpl())->getCudnnTensorDesc(*op.getOutput(0)),
        op.getOutput(0)->getImpl()->rawPtr()));
        }
        }
        ......
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