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| author | Vidhya Sudhan Loganathan <vidhyasudhan.loganathan@arm.com> | 2018-07-02 09:13:49 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:10 +0000 |
| commit | 014333d73883c3872e458cedda5ccef586a7ccd4 (patch) | |
| tree | 0f28bbc1ab769993af91b40e4584061f6ed6d3fa /tests/benchmark/fixtures/ROIPoolingLayerFixture.h | |
| parent | de01468bbfff3a7d8bcbba3bfdf5698fb2e3b267 (diff) | |
| download | ComputeLibrary-014333d73883c3872e458cedda5ccef586a7ccd4.tar.gz | |
COMPMID-970 : Remove QS8 / QS16 support
Removed Fixed point position arguments from test sources
Change-Id: I8343724723b71611fd501ed34de0866d3fb60e7e
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136382
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/benchmark/fixtures/ROIPoolingLayerFixture.h')
| -rw-r--r-- | tests/benchmark/fixtures/ROIPoolingLayerFixture.h | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/tests/benchmark/fixtures/ROIPoolingLayerFixture.h b/tests/benchmark/fixtures/ROIPoolingLayerFixture.h index 4adfa446d6..fa4a5b7044 100644 --- a/tests/benchmark/fixtures/ROIPoolingLayerFixture.h +++ b/tests/benchmark/fixtures/ROIPoolingLayerFixture.h @@ -47,8 +47,8 @@ public: void setup(TensorShape shape, const ROIPoolingLayerInfo pool_info, unsigned int num_rois, DataType data_type, int batches) { // Set batched in source and destination shapes - const unsigned int fixed_point_position = 4; - TensorShape shape_dst; + + TensorShape shape_dst; shape.set(shape.num_dimensions(), batches); shape_dst.set(0, pool_info.pooled_width()); shape_dst.set(1, pool_info.pooled_height()); @@ -56,8 +56,8 @@ public: shape_dst.set(3, num_rois); // Create tensors - src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position); - dst = create_tensor<TensorType>(shape_dst, data_type, 1, fixed_point_position); + src = create_tensor<TensorType>(shape, data_type, 1); + dst = create_tensor<TensorType>(shape_dst, data_type, 1); // Create random ROIs std::vector<ROI> rois = generate_random_rois(shape, pool_info, num_rois, 0U); |