Method onEncode

source/backend/opencl/execution/image/MultiInputDWDeconvExecution.cpp:39–274

}

ErrorCode MultiInputDWDeconvExecution::onEncode(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
    mUnits.clear();
    mUnits.resize(4);

    auto originLayout = TensorUtils::getDescribe(inputs[1])->dimensionFormat;
    auto openclBackend = static_cast<OpenCLBackend *>(backend());
    auto runtime = openclBackend->getOpenCLRuntime();

    auto inputShape  = tensorShapeFormat(inputs[0]);
    auto outputShape = tensorShapeFormat(outputs[0]);
    const int batch = outputShape.at(0);
    const int outputChannel = outputShape.at(3), inputChannel = inputShape.at(3);
    const int inputHeight = inputShape.at(1), inputWidth = inputShape.at(2);
    const int height = outputShape.at(1), width = outputShape.at(2);
    const int kernelY = inputs[1]->length(2), kernelX = inputs[1]->length(3);
    int kernelShape[2] = {kernelY, kernelX};

    const int weightSize = inputs[1]->elementSize();
    auto bufferPool = openclBackend->getBufferPool();
    auto rawBufferPtr = bufferPool->alloc(weightSize * sizeof(float), false);
    if (rawBufferPtr == nullptr) {
        return OUT_OF_MEMORY;
    }
    auto bufferPtr = bufferPool->alloc(weightSize * sizeof(float), false);
    if (bufferPtr == nullptr) {
        bufferPool->recycle(rawBufferPtr, false);
        return OUT_OF_MEMORY;
    }
    
    mFilter.reset(Tensor::createDevice<float>({1, UP_DIV(outputChannel, 4), 1, 4 * kernelY * kernelX}));
    bool succ = openclBackend->onAcquireBuffer(mFilter.get(), Backend::DYNAMIC);
    bufferPool->recycle(rawBufferPtr, false);
    bufferPool->recycle(bufferPtr, false);
    if (!succ) {
        return OUT_OF_MEMORY;
    }
    openclBackend->onReleaseBuffer(mFilter.get(), Backend::DYNAMIC);

    // transform kernel from image2d (NHCW) to original form (maybe NCHW or NHWC)
    {
        std::string kernelName = "";
        if (originLayout == MNN_DATA_FORMAT_NCHW) {
            kernelName = "image_to_nchw_buffer";
        } else if (originLayout == MNN_DATA_FORMAT_NHWC) {
            kernelName = "image_to_nhwc_buffer";
        }
        auto shape = tensorShapeFormat(inputs[1]);
        std::vector<uint32_t> gws = {static_cast<uint32_t>(shape[2] * UP_DIV(shape[3], 4)), static_cast<uint32_t>(shape[0] * shape[1])};

        auto kernelW = runtime->buildKernel("buffer_to_image", kernelName, {}, openclBackend->getPrecision(), inputs[1], inputs[1]);
        auto kernel = kernelW->get();
        cl_int ret = CL_SUCCESS;
        ret |= kernel.setArg(0, gws[0]);
        ret |= kernel.setArg(1, gws[1]);
        ret |= kernel.setArg(2, *rawBufferPtr);
        ret |= kernel.setArg(3, shape[1]);
        ret |= kernel.setArg(4, shape[2]);
        ret |= kernel.setArg(5, shape[3]);