Function TEST_CASE

tests/validation/CL/DirectConvolutionLayer.cpp:97–135

 * bias leads to a successful execution.
 */
TEST_CASE(NoBias, framework::DatasetMode::PRECOMMIT)
{
    const auto     src_shape     = TensorShape(27U, 13U, 2U);
    const auto     weights_shape = TensorShape(3U, 3U, 2U, 4U);
    const auto     bias_shape    = TensorShape(4U);
    const auto     dst_shape     = TensorShape(25U, 11U, 4U);
    constexpr auto dt            = DataType::F32;

    auto src     = create_tensor<CLTensor>(src_shape, dt);
    auto weights = create_tensor<CLTensor>(weights_shape, dt);
    auto dst     = create_tensor<CLTensor>(dst_shape, dt);

    const auto conv_info = PadStrideInfo(1, 1, 0, 0);

    // Create Direct Convolution function
    CLDirectConvolutionLayer conv{};
    conv.configure(&src, &weights, nullptr, &dst, conv_info);

    src.allocator()->allocate();
    weights.allocator()->allocate();
    dst.allocator()->allocate();

    library->fill_tensor_value(CLAccessor(src), 1.f);
    library->fill_tensor_value(CLAccessor(weights), 1.f);

    conv.run();

    // Compute reference to compare
    SimpleTensor<float> ref_src{src_shape, dt};
    SimpleTensor<float> ref_weights{weights_shape, dt};
    SimpleTensor<float> ref_bias{bias_shape, dt};
    library->fill_tensor_value(ref_src, 1.f);
    library->fill_tensor_value(ref_weights, 1.f);
    // No bias
    library->fill_tensor_value(ref_bias, 0.f);
    auto ref_dst = reference::convolution_layer<float>(ref_src, ref_weights, ref_bias, dst_shape, conv_info);

    validate(CLAccessor(dst), ref_dst);
}

/** Check whether the case of rectangle kernels i.e. when width and height of the weight_shape are not equal
 *  would lead to successful run