Method validate

src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp:130–252

CLGEMMDeconvolutionLayer::~CLGEMMDeconvolutionLayer() = default;

Status CLGEMMDeconvolutionLayer::validate(const ITensorInfo   *input,
                                          const ITensorInfo   *weights,
                                          const ITensorInfo   *bias,
                                          const ITensorInfo   *output,
                                          const PadStrideInfo &deconv_info)
{
    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
    ARM_COMPUTE_RETURN_ERROR_ON_DYNAMIC_SHAPE(input, weights, bias, output);
    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8,
                                                         DataType::QASYMM8_SIGNED);
    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, weights);

    DataLayout data_layout  = input->data_layout();
    const bool padded_input = deconv_info.pad_bottom() > 0 || deconv_info.pad_left() > 0 ||
                              deconv_info.pad_right() > 0 || deconv_info.pad_top() > 0;
    const bool is_nchw      = input->data_layout() == DataLayout::NCHW;
    const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type());

    const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
    const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
    const size_t idx_b = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

    ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) != deconv_info.stride().first);
    ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) != deconv_info.stride().second);

    TensorShape nhwc_weights_shape = weights->tensor_shape();
    TensorShape nhwc_input_shape   = input->tensor_shape();

    if (is_nchw)
    {
        permute(nhwc_weights_shape, PermutationVector(2, 0, 1));
        permute(nhwc_input_shape, PermutationVector(2, 0, 1));

        TensorInfo nhwc_input_info = input->clone()
                                         ->set_is_resizable(true)
                                         .reset_padding()
                                         .set_tensor_shape(nhwc_input_shape)
                                         .set_data_layout(DataLayout::NCHW);

        TensorInfo nhwc_weights_info = weights->clone()
                                           ->set_is_resizable(true)
                                           .reset_padding()
                                           .set_tensor_shape(nhwc_weights_shape)
                                           .set_data_layout(DataLayout::NCHW);

        CLPermute::validate(weights, &nhwc_weights_info, PermutationVector(2, 0, 1));
        CLPermute::validate(input, &nhwc_input_info, PermutationVector(2, 0, 1));
    }

    const TensorShape reshaped_shape =
        TensorShape(nhwc_weights_shape[0], nhwc_weights_shape[1] * nhwc_weights_shape[2] * nhwc_weights_shape[3]);
    const TensorInfo reshaped_info =
        weights->clone()->set_tensor_shape(reshaped_shape).set_data_layout(DataLayout::NCHW).set_is_resizable(true);
    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(weights, &reshaped_info));

    TensorShape      transposed_shape(reshaped_shape[1], reshaped_shape[0]);
    const TensorInfo reshaped_t_info = reshaped_info.clone()->set_is_resizable(true).set_tensor_shape(transposed_shape);