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| author | Georgios Pinitas <georgios.pinitas@arm.com> | 2018-07-20 13:23:44 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:54 +0000 |
| commit | e2220551b7a64b929650ba9a60529c31e70c13c5 (patch) | |
| tree | 5d609887f15b4392cdade7bb388710ceafc62260 /src/core/NEON/kernels/NENormalizationLayerKernel.cpp | |
| parent | eff8d95991205e874091576e2d225f63246dd0bb (diff) | |
| download | ComputeLibrary-e2220551b7a64b929650ba9a60529c31e70c13c5.tar.gz | |
COMPMID-1367: Enable NHWC in graph examples
Change-Id: Iabc54a3a1bdcd46a9a921cda39c7c85fef672b72
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/141449
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/NEON/kernels/NENormalizationLayerKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NENormalizationLayerKernel.cpp | 50 |
1 files changed, 32 insertions, 18 deletions
diff --git a/src/core/NEON/kernels/NENormalizationLayerKernel.cpp b/src/core/NEON/kernels/NENormalizationLayerKernel.cpp index cb1996f33e..15e8298e2d 100644 --- a/src/core/NEON/kernels/NENormalizationLayerKernel.cpp +++ b/src/core/NEON/kernels/NENormalizationLayerKernel.cpp @@ -43,6 +43,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *input_squ ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_layout() == DataLayout::NHWC && norm_info.type() == NormType::IN_MAP_2D, + "Only Cross-map and 1D In-map normalization is supported for NHWC layout"); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, input_squared); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, input_squared); ARM_COMPUTE_RETURN_ERROR_ON_MSG(!(norm_info.norm_size() % 2), "Normalization size should be odd"); @@ -61,8 +63,9 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen { unsigned int num_elems_processed_per_iteration = 16 / input->element_size(); const unsigned int num_elems_read_per_iteration = num_elems_processed_per_iteration + 2 * (norm_info.norm_size() / 2); + const unsigned int norm_idx = get_normalization_dimension_index(input->data_layout(), norm_info); const unsigned int num_rows = (norm_info.type() == NormType::IN_MAP_2D) ? norm_info.norm_size() : 1; - const unsigned int border_width = (norm_info.is_cross_map()) ? 0 : std::min<unsigned int>(norm_info.norm_size() / 2, 3U); + const unsigned int border_width = (norm_idx == 2) ? 0 : std::min<unsigned int>(norm_info.norm_size() / 2, 3U); BorderSize border_size = BorderSize(0, border_width); bool window_changed = false; @@ -107,7 +110,8 @@ void NENormalizationLayerKernel::configure(const ITensor *input, const ITensor * // Perform validation step ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), input_squared->info(), output->info(), norm_info)); - const unsigned int border_width = (norm_info.is_cross_map()) ? 0 : std::min<unsigned int>(norm_info.norm_size() / 2, 3U); + const unsigned int norm_idx = get_normalization_dimension_index(input->info()->data_layout(), norm_info); + const unsigned int border_width = (norm_idx == 2) ? 0 : std::min<unsigned int>(norm_info.norm_size() / 2, 3U); _input = input; _input_squared = input_squared; @@ -119,16 +123,21 @@ void NENormalizationLayerKernel::configure(const ITensor *input, const ITensor * { case DataType::F32: { - switch(norm_info.type()) + switch(norm_idx) { - case NormType::IN_MAP_1D: - _func = &NENormalizationLayerKernel::normalize_float<DataType::F32, 0, false>; - break; - case NormType::IN_MAP_2D: - // Normalize over X and Y - _func = &NENormalizationLayerKernel::normalize_float<DataType::F32, 0, true>; + case 0: + { + if(norm_info.type() == NormType::IN_MAP_2D) + { + _func = &NENormalizationLayerKernel::normalize_float<DataType::F32, 0, true>; + } + else + { + _func = &NENormalizationLayerKernel::normalize_float<DataType::F32, 0, false>; + } break; - case NormType::CROSS_MAP: + } + case 2: _func = &NENormalizationLayerKernel::normalize_float<DataType::F32, 2, false>; break; default: @@ -138,16 +147,21 @@ void NENormalizationLayerKernel::configure(const ITensor *input, const ITensor * } case DataType::F16: { - switch(norm_info.type()) + switch(norm_idx) { - case NormType::IN_MAP_1D: - _func = &NENormalizationLayerKernel::normalize_float<DataType::F16, 0, false>; - break; - case NormType::IN_MAP_2D: - // Normalize over X and Y - _func = &NENormalizationLayerKernel::normalize_float<DataType::F16, 0, true>; + case 0: + { + if(norm_info.type() == NormType::IN_MAP_2D) + { + _func = &NENormalizationLayerKernel::normalize_float<DataType::F16, 0, true>; + } + else + { + _func = &NENormalizationLayerKernel::normalize_float<DataType::F16, 0, false>; + } break; - case NormType::CROSS_MAP: + } + case 2: _func = &NENormalizationLayerKernel::normalize_float<DataType::F16, 2, false>; break; default: |