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author | Anitha Raj <anitha.raj@arm.com> | 2023-08-15 09:40:55 +0100 |
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committer | Anitha Raj <Anitha.Raj@arm.com> | 2023-08-17 09:18:34 +0000 |
commit | 607509748bf81d72a7bd0f54d5fe5f7504c3b6ff (patch) | |
tree | 2a307fcfa45daee4a6847766616a52348802529a /tests/validation/Helpers.h | |
parent | 246fe086589a7f2b4e24498ba9ab296091dc5540 (diff) | |
download | ComputeLibrary-607509748bf81d72a7bd0f54d5fe5f7504c3b6ff.tar.gz |
Remove functionality to add padding in Y dimension in validation tests
Signed-off-by: Anitha Raj <anitha.raj@arm.com>
Change-Id: I5b9e04f9057777bb080c40fa1f55dfee4bd866dc
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10138
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/validation/Helpers.h')
-rw-r--r-- | tests/validation/Helpers.h | 10 |
1 files changed, 0 insertions, 10 deletions
diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h index df3b08ba53..3f91d55db1 100644 --- a/tests/validation/Helpers.h +++ b/tests/validation/Helpers.h @@ -243,16 +243,6 @@ std::pair<int, int> get_symm_quantized_per_channel_bounds(const QuantizationInfo */ void add_padding_x(std::initializer_list<ITensor *> tensors, const DataLayout &data_layout = DataLayout::NHWC, bool only_right_pad = false); -/** Add random padding along the Y axis (between 1 and 4 rows per side) to all the input tensors. - * This is used in our validation suite in order to simulate implicit padding addition after configuring, but before allocating. - * - * @param[in] tensors List of tensors to add padding to - * @param[in] data_layout (Optional) Data layout of the operator - * - * @note This function adds padding to the input tensors only if data_layout == DataLayout::NHWC - */ -void add_padding_y(std::initializer_list<ITensor *> tensors, const DataLayout &data_layout = DataLayout::NHWC); - /** For MatMulLowp, given the Lhs/Rhs matrix quantization informations and the matrix multiplication dimensions, * calculate a suitable output quantization for obtaining non-saturated outputs with high probability. */ |