diff options
Diffstat (limited to 'tests/validation/fixtures/FullyConnectedLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/FullyConnectedLayerFixture.h | 126 |
1 files changed, 20 insertions, 106 deletions
diff --git a/tests/validation/fixtures/FullyConnectedLayerFixture.h b/tests/validation/fixtures/FullyConnectedLayerFixture.h index ccd9182ae9..7d767642f3 100644 --- a/tests/validation/fixtures/FullyConnectedLayerFixture.h +++ b/tests/validation/fixtures/FullyConnectedLayerFixture.h @@ -273,7 +273,7 @@ public: }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class FullyConnectedWithDynamicTensorsFixture : public framework::Fixture +class FullyConnectedWithDynamicWeightsFixture : public framework::Fixture { private: template <typename U> @@ -289,16 +289,6 @@ private: std::uniform_real_distribution<float> distribution(-1.0f, 1.0f); library->fill(tensor, distribution, i); } - else if(_data_type == DataType::QASYMM8) - { - std::uniform_int_distribution<uint8_t> distribution(0, 30); - library->fill(tensor, distribution, i); - } - else if(_data_type == DataType::S32) - { - std::uniform_int_distribution<int32_t> distribution(-50, 50); - library->fill(tensor, distribution, i); - } else { library->fill_tensor_uniform(tensor, i); @@ -334,11 +324,6 @@ private: constexpr AbsoluteTolerance<float> abs_tolerance_f32(0.0001f); validate(AccessorType(target), ref, rel_tolerance_f32, 0, abs_tolerance_f32); } - else if(_data_type == DataType::QASYMM8) - { - constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); - validate(AccessorType(target), ref, tolerance_qasymm8); - } else { validate(AccessorType(target), ref); @@ -346,51 +331,32 @@ private: } public: - using TDecay = typename std::decay<T>::type; - using TBias = typename std::conditional < (std::is_same<TDecay, uint8_t>::value || std::is_same<TDecay, int8_t>::value), int32_t, T >::type; - template <typename...> void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape dst_shape, - DataType data_type, ActivationLayerInfo activation_info, bool constant_weights, bool constant_bias) + DataType data_type, ActivationLayerInfo activation_info) { _data_type = data_type; - const bool is_quantized = is_data_type_quantized(data_type); - - const DataType bias_data_type = (is_quantized) ? DataType::S32 : data_type; - - const QuantizationInfo src_qinfo = is_quantized ? QuantizationInfo(0.1f, 10) : QuantizationInfo(); - const QuantizationInfo weights_qinfo = is_quantized ? QuantizationInfo(0.3f, 20) : QuantizationInfo(); - const QuantizationInfo dst_qinfo = is_quantized ? QuantizationInfo(0.2f, 5) : QuantizationInfo(); - // Setup tensor meta-data - const TensorInfo src_info(src_shape, 1, data_type, src_qinfo); + TensorInfo src_info(src_shape, 1, data_type); _src.allocator()->init(src_info); - TensorInfo wei_info(weights_shape, 1, data_type, weights_qinfo); - if(!constant_weights) - { - const TensorShape tr_weights_shape{ weights_shape[1], weights_shape[0] }; - wei_info.set_tensor_shape(tr_weights_shape); - } - wei_info.set_are_values_constant(constant_weights); + TensorShape tr_weights_shape{ weights_shape[1], weights_shape[0] }; + TensorInfo wei_info(tr_weights_shape, 1, data_type); _weights.allocator()->init(wei_info); - TensorInfo bias_info(bias_shape, 1, bias_data_type); - bias_info.set_are_values_constant(constant_bias); + TensorInfo bias_info(bias_shape, 1, data_type); _bias.allocator()->init(bias_info); - const TensorInfo dst_info(dst_shape, 1, data_type, dst_qinfo); + TensorInfo dst_info(dst_shape, 1, data_type); _dst.allocator()->init(dst_info); // Configure FC layer and mark the weights as non constant FullyConnectedLayerInfo fc_info; - fc_info.activation_info = activation_info; - if(!constant_weights) - { - fc_info.are_weights_reshaped = true; - fc_info.transpose_weights = false; - } + fc_info.activation_info = activation_info; + fc_info.are_weights_reshaped = true; + fc_info.transpose_weights = false; + fc_info.constant_weights = false; FunctionType fc; fc.configure(&_src, &_weights, &_bias, &_dst, fc_info); @@ -403,55 +369,29 @@ public: // Run multiple iterations with different inputs constexpr int num_iterations = 5; int randomizer_offset = 0; - - // Create reference tensors - SimpleTensor<T> src{ src_shape, data_type, 1, src_qinfo }; - SimpleTensor<T> weights{ weights_shape, data_type, 1, weights_qinfo }; - SimpleTensor<TBias> bias{ bias_shape, bias_data_type }; - - // Fill weights and/or bias if they remain constant - if(constant_weights) - { - fill(AccessorType(_weights), 1); - fill(weights, 1); - } - if(constant_bias) - { - fill(AccessorType(_bias), 2); - fill(bias, 2); - } - for(int i = 0; i < num_iterations; ++i) { // Run target { fill(AccessorType(_src), randomizer_offset); - if(!constant_weights) - { - fill_transposed_weights(_weights, weights_shape, randomizer_offset + 1); - } - if(!constant_bias) - { - fill(AccessorType(_bias), randomizer_offset + 2); - } + fill_transposed_weights(_weights, weights_shape, randomizer_offset + 1); + fill(AccessorType(_bias), randomizer_offset + 2); fc.run(); } // Run reference and compare { + SimpleTensor<T> src{ src_shape, data_type }; + SimpleTensor<T> weights{ weights_shape, data_type }; + SimpleTensor<T> bias{ bias_shape, data_type }; + // Fill reference fill(src, randomizer_offset); - if(!constant_weights) - { - fill(weights, randomizer_offset + 1); - } - if(!constant_bias) - { - fill(bias, randomizer_offset + 2); - } + fill(weights, randomizer_offset + 1); + fill(bias, randomizer_offset + 2); - auto dst = reference::activation_layer(reference::fully_connected_layer<T>(src, weights, bias, dst_shape), activation_info, dst_qinfo); + auto dst = reference::activation_layer(reference::fully_connected_layer<T>(src, weights, bias, dst_shape), activation_info); // Validate validate_with_tolerance(_dst, dst); @@ -465,32 +405,6 @@ private: TensorType _src{}, _weights{}, _bias{}, _dst{}; DataType _data_type{ DataType::UNKNOWN }; }; - -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class FullyConnectedWithDynamicWeightsFixture : public FullyConnectedWithDynamicTensorsFixture<TensorType, AccessorType, FunctionType, T> -{ -public: - template <typename...> - void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape dst_shape, - DataType data_type, ActivationLayerInfo activation_info) - { - FullyConnectedWithDynamicTensorsFixture<TensorType, AccessorType, FunctionType, T>::setup(src_shape, weights_shape, bias_shape, - dst_shape, data_type, activation_info, false, true); - } -}; - -template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class FullyConnectedWithDynamicBiasFixture : public FullyConnectedWithDynamicTensorsFixture<TensorType, AccessorType, FunctionType, T> -{ -public: - template <typename...> - void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape dst_shape, - DataType data_type, ActivationLayerInfo activation_info) - { - FullyConnectedWithDynamicTensorsFixture<TensorType, AccessorType, FunctionType, T>::setup(src_shape, weights_shape, bias_shape, - dst_shape, data_type, activation_info, true, false); - } -}; } // namespace validation } // namespace test } // namespace arm_compute |