diff options
Diffstat (limited to 'tests')
-rw-r--r-- | tests/networks/AlexNetNetwork.h | 2 | ||||
-rw-r--r-- | tests/validation/fixtures/ConvolutionLayerFixture.h | 4 |
2 files changed, 3 insertions, 3 deletions
diff --git a/tests/networks/AlexNetNetwork.h b/tests/networks/AlexNetNetwork.h index 0c06c1860f..448cf31914 100644 --- a/tests/networks/AlexNetNetwork.h +++ b/tests/networks/AlexNetNetwork.h @@ -100,7 +100,7 @@ public: { auto reshape = [&](unsigned int width, unsigned int height, bool convolution_layer) -> TensorShape { - const bool is_optimised = std::is_same<ITensorType, ITensor>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && data_type == DataType::F32; + const bool is_optimised = std::is_same<ITensorType, ITensor>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV7 && data_type == DataType::F32; if(convolution_layer && is_optimised) { diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h index fcaf4ef42b..434291b58e 100644 --- a/tests/validation/fixtures/ConvolutionLayerFixture.h +++ b/tests/validation/fixtures/ConvolutionLayerFixture.h @@ -88,7 +88,7 @@ protected: { // Check if its a "fully connected" convolution const bool is_fully_connected_convolution = (output_shape.x() == 1 && output_shape.y() == 1); - const bool is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && data_type == DataType::F32; + const bool is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV7 && data_type == DataType::F32; reshaped_weights_shape.collapse(3); @@ -143,7 +143,7 @@ protected: if(!reshape_weights) { const bool is_fully_connected_convolution = (output_shape.x() == 1 && output_shape.y() == 1); - const bool is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && data_type == DataType::F32; + const bool is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV7 && data_type == DataType::F32; TensorShape tmp_weights_shape(weights_shape); SimpleTensor<T> tmp_weights(tmp_weights_shape, data_type, 1, fixed_point_position); |