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| author | Michele Di Giorgio <michele.digiorgio@arm.com> | 2018-03-01 16:56:48 +0000 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:49:54 +0000 |
| commit | 0cbb927ac309e332ac6e6f1ab9170f041f0138ab (patch) | |
| tree | 102d50dec9f741f04b1126ae03e6e491dda2d3ba /tests/benchmark/fixtures | |
| parent | 82b51482479951cf133c223eb81aae291cb4d590 (diff) | |
| download | ComputeLibrary-0cbb927ac309e332ac6e6f1ab9170f041f0138ab.tar.gz | |
COMPMID-804: Add NHWC data format support for NEON batch normalisation
Change-Id: I04892e7be3f5aa58cd95917a4f90a6b4ffcf6efc
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/122897
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/benchmark/fixtures')
| -rw-r--r-- | tests/benchmark/fixtures/BatchNormalizationLayerFixture.h | 10 |
1 files changed, 7 insertions, 3 deletions
diff --git a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h index c55bb2acc9..ae8f8a7af1 100644 --- a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h +++ b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h @@ -42,15 +42,19 @@ class BatchNormalizationLayerFixture : public framework::Fixture { public: template <typename...> - void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, bool use_gamma, bool use_beta, ActivationLayerInfo act_info, DataType data_type, int batches) + void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, bool use_gamma, bool use_beta, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout, int batches) { // Set batched in source and destination shapes const unsigned int fixed_point_position = 4; tensor_shape.set(tensor_shape.num_dimensions(), batches); + if(data_layout == DataLayout::NHWC) + { + permute(tensor_shape, PermutationVector(2U, 0U, 1U)); + } // Create tensors - src = create_tensor<TensorType>(tensor_shape, data_type, 1, fixed_point_position); - dst = create_tensor<TensorType>(tensor_shape, data_type, 1, fixed_point_position); + src = create_tensor<TensorType>(tensor_shape, data_type, 1, fixed_point_position, QuantizationInfo(), data_layout); + dst = create_tensor<TensorType>(tensor_shape, data_type, 1, fixed_point_position, QuantizationInfo(), data_layout); mean = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position); variance = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position); beta = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position); |