diff options
Diffstat (limited to 'tests/validation/fixtures/DirectConvolutionLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/DirectConvolutionLayerFixture.h | 110 |
1 files changed, 71 insertions, 39 deletions
diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h index ef7721dd5e..9ea4061e53 100644 --- a/tests/validation/fixtures/DirectConvolutionLayerFixture.h +++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h @@ -21,8 +21,10 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ +#include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "tests/AssetsLibrary.h" #include "tests/Globals.h" #include "tests/IAccessor.h" @@ -31,6 +33,7 @@ #include "tests/validation/Helpers.h" #include "tests/validation/fixtures/ConvolutionLayerFixture.h" #include "tests/validation/reference/ConvolutionLayer.h" +#include "tests/validation/reference/Permute.h" #include <random> @@ -40,6 +43,8 @@ namespace test { namespace validation { +using namespace arm_compute::misc::shape_calculator; + template <typename TensorType, typename AccessorType, typename FunctionType, typename T> class DirectConvolutionValidationGenericFixture : public framework::Fixture { @@ -49,26 +54,42 @@ public: public: template <typename...> void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, - DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info) + DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout) { + ARM_COMPUTE_ERROR_ON(data_layout == DataLayout::UNKNOWN); + _fractional_bits = fractional_bits; _quantization_info = quantization_info; _data_type = data_type; - const TensorShape weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels); + TensorShape weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels); const TensorShape bias_shape(num_kernels); const PadStrideInfo info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR); - const TensorShape output_shape = get_output_shape(input_shape, weights_shape, info); const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); + if(data_layout == DataLayout::NHWC) + { + permute(input_shape, PermutationVector(2U, 0U, 1U)); + permute(weights_shape, PermutationVector(2U, 0U, 1U)); + } + + TensorInfo input_info = TensorInfo(input_shape, 1, data_type, _fractional_bits); + TensorInfo weights_info = TensorInfo(weights_shape, 1, data_type, _fractional_bits); + + input_info.set_data_layout(data_layout); + weights_info.set_data_layout(data_layout); + + const TensorShape output_shape = compute_deep_convolution_shape(input_info, weights_info, info); + + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info, data_layout); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info, data_layout); } template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, - DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info) + DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout) { + ARM_COMPUTE_ERROR_ON(data_layout == DataLayout::UNKNOWN); ARM_COMPUTE_UNUSED(dilation); _fractional_bits = fractional_bits; @@ -77,8 +98,15 @@ public: const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); + if(data_layout == DataLayout::NHWC) + { + permute(input_shape, PermutationVector(2U, 0U, 1U)); + permute(weights_shape, PermutationVector(2U, 0U, 1U)); + permute(output_shape, PermutationVector(2U, 0U, 1U)); + } + + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info, data_layout); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info, data_layout); } protected: @@ -112,13 +140,13 @@ protected: } TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info) + DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info, const DataLayout &data_layout) { // Create tensors - TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position, quantization_info); - TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position, quantization_info); + TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position, quantization_info, data_layout); + TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position, quantization_info, data_layout); TensorType bias = create_tensor<TensorType>(bias_shape, bias_data_type, 1, fixed_point_position, quantization_info); - TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position, quantization_info); + TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position, quantization_info, data_layout); // Create and configure function FunctionType conv; @@ -152,11 +180,13 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info) + DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info, const DataLayout &data_layout) { + ARM_COMPUTE_ERROR_ON(data_layout == DataLayout::UNKNOWN); + // Create reference - SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position, quantization_info }; - SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position, quantization_info }; + SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position, quantization_info, data_layout }; + SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position, quantization_info, data_layout }; SimpleTensor<TBias> bias{ bias_shape, bias_data_type, 1, fixed_point_position, quantization_info }; // Fill reference @@ -164,9 +194,25 @@ protected: fill(weights, 1); fill(bias, 2); - return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info), - act_info) : - reference::convolution_layer<T>(src, weights, bias, output_shape, info); + SimpleTensor<T> dst; + + // FIXME: move to reference once all functions that call reference::convolution_layer<>() support NHWC + if(src.data_layout() == DataLayout::NHWC) + { + SimpleTensor<T> src_nchw = reference::permute<T>(src, PermutationVector(1U, 2U, 0U)); + SimpleTensor<T> weights_nchw = reference::permute<T>(weights, PermutationVector(1U, 2U, 0U)); + + TensorShape output_shape_nchw{ output_shape }; + permute(output_shape_nchw, PermutationVector(1U, 2U, 0U)); + + dst = reference::permute<T>(reference::convolution_layer<T>(src_nchw, weights_nchw, bias, output_shape_nchw, info), PermutationVector(2U, 0U, 1U)); + } + else + { + dst = reference::convolution_layer<T>(src, weights, bias, output_shape, info); + } + + return (act_info.enabled()) ? reference::activation_layer<T>(dst, act_info) : dst; } TensorType _target{}; @@ -174,21 +220,6 @@ protected: int _fractional_bits{}; QuantizationInfo _quantization_info{}; DataType _data_type{}; - -private: - TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info) - { - TensorShape out_shape(in_shape); - const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(), - in_shape.y(), - kernel_shape.x(), - kernel_shape.y(), - info); - out_shape.set(0, scaled_dims.first); - out_shape.set(1, scaled_dims.second); - out_shape.set(2, kernel_shape[3]); - return out_shape; - } }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> @@ -196,10 +227,11 @@ class DirectConvolutionValidationFixture : public DirectConvolutionValidationGen { public: template <typename...> - void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, ActivationLayerInfo act_info) + void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, ActivationLayerInfo act_info, + DataLayout data_layout) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, QuantizationInfo(), - act_info); + act_info, data_layout); } }; @@ -212,7 +244,7 @@ public: ActivationLayerInfo act_info) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, fractional_bits, - QuantizationInfo(), act_info); + QuantizationInfo(), act_info, DataLayout::NCHW); } }; @@ -225,7 +257,7 @@ public: ActivationLayerInfo act_info) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, quantization_info, - act_info); + act_info, DataLayout::NCHW); } }; @@ -238,7 +270,7 @@ public: DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, quantization_info, - act_info); + act_info, DataLayout::NCHW); } }; @@ -251,7 +283,7 @@ public: DataType data_type, ActivationLayerInfo act_info) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, QuantizationInfo(), - act_info); + act_info, DataLayout::NCHW); } }; |