diff options
Diffstat (limited to 'tests/validation/CPP/ConvolutionLayer.cpp')
-rw-r--r-- | tests/validation/CPP/ConvolutionLayer.cpp | 30 |
1 files changed, 19 insertions, 11 deletions
diff --git a/tests/validation/CPP/ConvolutionLayer.cpp b/tests/validation/CPP/ConvolutionLayer.cpp index 656cd2ee26..ab3690a493 100644 --- a/tests/validation/CPP/ConvolutionLayer.cpp +++ b/tests/validation/CPP/ConvolutionLayer.cpp @@ -26,6 +26,8 @@ #include "tests/validation/FixedPoint.h" #include "tests/validation/Helpers.h" +#include "tests/framework/Asserts.h" + namespace arm_compute { namespace test @@ -149,21 +151,24 @@ SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor const int width_weights = weights.shape().x(); const int height_weights = weights.shape().y(); const int depth_weights = weights.shape().z(); - const int pad_xi = std::min(static_cast<int>(info.pad().first), width_weights / 2); - const int pad_yi = std::min(static_cast<int>(info.pad().second), height_weights / 2); - const int start_xi = width_weights / 2 - pad_xi; - const int start_yi = height_weights / 2 - pad_yi; - const int end_xi = width_in - start_xi; - const int end_yi = height_in - start_yi; - const int stride_xi = info.stride().first; - const int stride_yi = info.stride().second; - const int num_batches = src.shape().total_size() / (width_in * height_in * depth_in); + const int pad_left = std::min(static_cast<int>(info.pad_left()), width_weights / 2); + const int pad_top = std::min(static_cast<int>(info.pad_top()), height_weights / 2); + const int pad_right = std::min(static_cast<int>(info.pad_right()), width_weights / 2); + const int pad_bottom = std::min(static_cast<int>(info.pad_bottom()), height_weights / 2); + + const int start_xi = width_weights / 2 - pad_left; + const int start_yi = height_weights / 2 - pad_top; + const int end_xi = width_in + pad_left - width_weights / 2 + pad_right - width_weights / 2; + const int end_yi = height_in + pad_top - height_weights / 2 + pad_bottom - height_weights / 2; + const int stride_xi = info.stride().first; + const int stride_yi = info.stride().second; + const int num_batches = src.shape().total_size() / (width_in * height_in * depth_in); for(int r = 0; r < num_batches; ++r) { - for(int yi = start_yi; yi < end_yi; yi += stride_yi) + for(int yi = start_yi; yi < start_yi + end_yi; yi += stride_yi) { - for(int xi = start_xi; xi < end_xi; xi += stride_xi) + for(int xi = start_xi; xi < start_xi + end_xi; xi += stride_xi) { for(int ofm = 0; ofm < depth_out; ++ofm) { @@ -173,6 +178,9 @@ SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor const int yo = (yi - start_yi) / stride_yi; const int offset_out = xo + yo * width_out + ofm * width_out * height_out + r * width_out * height_out * depth_out; + ARM_COMPUTE_ASSERT(xo < width_out); + ARM_COMPUTE_ASSERT(yo < height_out); + // Compute 3D convolution convolution3d(src.data() + offset_in, weights.data() + ofm * width_weights * height_weights * depth_weights, |