From ddec4d68b287f992df2493de819c908f79d2f443 Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Wed, 10 Jul 2019 19:23:02 +0100 Subject: COMPMID-2458: Initialize uninitialized variables Change-Id: I18c39a7708a68861764b548c8d2bea3100be3612 Signed-off-by: Georgios Pinitas Reviewed-on: https://review.mlplatform.org/c/1511 Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio Comments-Addressed: Arm Jenkins --- .../fixtures/DepthwiseConvolutionLayerFixture.h | 19 ++++++------------- .../reference/DepthwiseConvolutionLayer.cpp | 10 +++++----- 2 files changed, 11 insertions(+), 18 deletions(-) (limited to 'tests') diff --git a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h index 04c073b521..b01e1760aa 100644 --- a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h +++ b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h @@ -59,10 +59,6 @@ public: void setup(TensorShape in_shape, Size2D kernel_size, PadStrideInfo pad_stride_info, Size2D dilation, unsigned int depth_multiplier, DataType data_type, QuantizationInfo input_quantization_info, QuantizationInfo output_quantization_info, DataLayout data_layout, ActivationLayerInfo act_info) { - _input_quantization_info = input_quantization_info; - _output_quantization_info = output_quantization_info; - - _data_type = data_type; const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; TensorShape weights_shape(kernel_size.width, kernel_size.height); @@ -113,8 +109,8 @@ protected: TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape output_shape, PadStrideInfo &pad_stride_info, Size2D dilation, unsigned int depth_multiplier, const DataType data_type, const DataType bias_data_type, - const QuantizationInfo input_quantization_info, const QuantizationInfo output_quantization_info, - const DataLayout data_layout, ActivationLayerInfo act_info) + const QuantizationInfo &input_quantization_info, const QuantizationInfo &output_quantization_info, + const DataLayout data_layout, const ActivationLayerInfo &act_info) { if(data_layout == DataLayout::NHWC) { @@ -164,8 +160,8 @@ protected: const PadStrideInfo &pad_stride_info, const Size2D &dilation, unsigned int depth_multiplier, const DataType data_type, const DataType bias_data_type, - const QuantizationInfo input_quantization_info, const QuantizationInfo output_quantization_info, - ActivationLayerInfo act_info) + const QuantizationInfo &input_quantization_info, const QuantizationInfo &output_quantization_info, + const ActivationLayerInfo &act_info) { SimpleTensor src{ in_shape, data_type, 1, input_quantization_info }; SimpleTensor weights{ weights_shape, data_type, 1, input_quantization_info }; @@ -179,11 +175,8 @@ protected: return (act_info.enabled()) ? reference::activation_layer(depth_out, act_info) : depth_out; } - TensorType _target{}; - SimpleTensor _reference{}; - DataType _data_type{}; - QuantizationInfo _input_quantization_info{}; - QuantizationInfo _output_quantization_info{}; + TensorType _target{}; + SimpleTensor _reference{}; }; template diff --git a/tests/validation/reference/DepthwiseConvolutionLayer.cpp b/tests/validation/reference/DepthwiseConvolutionLayer.cpp index 2192d681b6..b1d2b923f7 100644 --- a/tests/validation/reference/DepthwiseConvolutionLayer.cpp +++ b/tests/validation/reference/DepthwiseConvolutionLayer.cpp @@ -137,12 +137,12 @@ SimpleTensor depthwise_convolution(const SimpleTensor &src, co const float input_scale = src.quantization_info().uniform().scale; const int weights_offset = -weights.quantization_info().uniform().offset; const float weights_scale = weights.quantization_info().uniform().scale; - const int output_offset = dst.quantization_info().uniform().offset; - const float output_scale = dst.quantization_info().uniform().scale; + const int output_offset = dst_qinfo.uniform().offset; + const float output_scale = dst_qinfo.uniform().scale; - int output_multiplier; - int output_shift; - const float multiplier = input_scale * weights_scale / output_scale; + int output_multiplier = 0; + int output_shift = 0; + const float multiplier = input_scale * weights_scale / output_scale; arm_compute::quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); // Compute reference -- cgit v1.2.1