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| author | Freddie Liardet <frederick.liardet@arm.com> | 2021-05-04 12:41:16 +0100 |
|---|---|---|
| committer | frederick.liardet <frederick.liardet@arm.com> | 2021-05-13 13:13:06 +0000 |
| commit | afcbb8f47427405a35be508425376286f0fd7a70 (patch) | |
| tree | b373f2d2a6a94b53116c5a53da7c4b4181753486 /src/core/gpu/cl/kernels/ClPoolingKernel.cpp | |
| parent | fd83bc8894007c2c9591896ba4229c99d8236a7a (diff) | |
| download | ComputeLibrary-afcbb8f47427405a35be508425376286f0fd7a70.tar.gz | |
Fix Pooling Layer Bug when input is 1xN size
Return error in pooling layer when any calculated output dimension is less than 1.
Simplify use of pooling layer output dimension values in
CpuPoolingKernel.cpp.
Remove some invalid tests in cpu/gpu pooling layers.
Resolves COMPMID-4358.
Signed-off-by: Freddie Liardet <frederick.liardet@arm.com>
Change-Id: If8f8ffec579d3eca1c27a45e5b0b684a77103cff
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5559
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/gpu/cl/kernels/ClPoolingKernel.cpp')
| -rw-r--r-- | src/core/gpu/cl/kernels/ClPoolingKernel.cpp | 12 |
1 files changed, 12 insertions, 0 deletions
diff --git a/src/core/gpu/cl/kernels/ClPoolingKernel.cpp b/src/core/gpu/cl/kernels/ClPoolingKernel.cpp index a432877a1d..08a3ce3784 100644 --- a/src/core/gpu/cl/kernels/ClPoolingKernel.cpp +++ b/src/core/gpu/cl/kernels/ClPoolingKernel.cpp @@ -67,6 +67,18 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const ARM_COMPUTE_RETURN_ERROR_ON_MSG((is_data_type_quantized_asymmetric(src->data_type()) && pool_info.pool_type == PoolingType::L2), "Unsupported combination of parameters!"); + const auto data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : pool_info.data_layout; + const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + const bool is_global_pooling = pool_info.is_global_pooling; + unsigned int pool_size_x = is_global_pooling ? src->dimension(idx_width) : pool_info.pool_size.width; + unsigned int pool_size_y = is_global_pooling ? src->dimension(idx_height) : pool_info.pool_size.height; + int output_width = 0; + int output_height = 0; + std::tie(output_width, output_height) = scaled_dimensions_signed(src->tensor_shape()[idx_width], src->tensor_shape()[idx_height], + pool_size_x, pool_size_y, pool_info.pad_stride_info); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((output_width < 1 || output_height < 1), "Calculated output dimension size is invalid"); + // Check indices if(indices) { |