diff options
author | Moritz Pflanzer <moritz.pflanzer@arm.com> | 2017-09-15 10:42:58 +0100 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | 80373f607cb12693824411510c39e367a4dfbdb5 (patch) | |
tree | ddc4d038783ed91ff227fb259a85fefc09e46319 /tests/validation | |
parent | c09314a288dc2aa7ef75a09a8ff5dede3f80974a (diff) | |
download | ComputeLibrary-80373f607cb12693824411510c39e367a4dfbdb5.tar.gz |
COMPMID-481: Add AArch32 GEMM
Change-Id: Idba0b30bfb27866a46a22388014ab81432ea28dc
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/86196
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Diffstat (limited to 'tests/validation')
-rw-r--r-- | tests/validation/fixtures/ConvolutionLayerFixture.h | 4 |
1 files changed, 2 insertions, 2 deletions
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); |