From c2a51bd2cc7c4148d9444e7377af44b2f6c264ba Mon Sep 17 00:00:00 2001 From: Gunes Bayir Date: Thu, 28 Sep 2023 10:30:18 +0100 Subject: Optimize CL and Neon Winograd tests Several test optimizations have been introduced into Winograd tests for Gpu and Cpu backends. The testing strategy has been detailed as a comment header in the test design files. In summary - Very large shapes in the nightly are made smaller - If the underlying kernel is the same for different data types, we only need to stress some key aspects of the kernels (e.g. read/write lengths in case of fp32/fp16). - In case the underlying kernel is the same (OpenCL), Fp16 is tested on a subset of the shapes - In Cpu, there is no need to test every combination for both NCHW and NHWC as we just permute the inputs and use NHWC kernels anyways - All activations does not need to be tested for each and every shape Resolves: COMPMID-6464 Change-Id: Ie25fded85c65b9c7386dc21b23f9b695b1e77b07 Signed-off-by: Gunes Bayir Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10393 Reviewed-by: Jakub Sujak Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Benchmark: Arm Jenkins --- tests/datasets/LargeConvolutionLayerDataset.h | 211 ++++++++++++++++++-------- 1 file changed, 146 insertions(+), 65 deletions(-) (limited to 'tests/datasets') diff --git a/tests/datasets/LargeConvolutionLayerDataset.h b/tests/datasets/LargeConvolutionLayerDataset.h index 1cffc9a221..72f73ba6d9 100644 --- a/tests/datasets/LargeConvolutionLayerDataset.h +++ b/tests/datasets/LargeConvolutionLayerDataset.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 Arm Limited. + * Copyright (c) 2017-2020, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -21,8 +21,8 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#ifndef ARM_COMPUTE_TEST_LARGE_CONVOLUTION_LAYER_DATASET -#define ARM_COMPUTE_TEST_LARGE_CONVOLUTION_LAYER_DATASET +#ifndef ACL_TESTS_DATASETS_LARGECONVOLUTIONLAYERDATASET_H +#define ACL_TESTS_DATASETS_LARGECONVOLUTIONLAYERDATASET_H #include "tests/datasets/ConvolutionLayerDataset.h" @@ -44,18 +44,31 @@ public: { // Kernel size 3 // Batch size 1 - add_config(TensorShape(224U, 222U, 64U), TensorShape(3U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U), PadStrideInfo(1, 1, 1, 1)); - add_config(TensorShape(112U, 113U, 64U), TensorShape(3U, 3U, 64U, 128U), TensorShape(128U), TensorShape(112U, 113U, 128U), PadStrideInfo(1, 1, 1, 1)); - add_config(TensorShape(112U, 112U, 128U), TensorShape(3U, 3U, 128U, 129U), TensorShape(129U), TensorShape(112U, 112U, 129U), PadStrideInfo(1, 1, 1, 1)); - add_config(TensorShape(53U, 56U, 125U), TensorShape(3U, 3U, 125U, 256U), TensorShape(256U), TensorShape(51U, 54U, 256U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(56U, 56U, 256U), TensorShape(3U, 3U, 256U, 256U), TensorShape(256U), TensorShape(54U, 54U, 256U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(28U, 28U, 257U), TensorShape(3U, 3U, 257U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 1)); - add_config(TensorShape(28U, 28U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 1)); - add_config(TensorShape(14U, 14U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(12U, 12U, 512U), PadStrideInfo(1, 1, 0, 0)); - // Batch size 3, 2 and 4 - add_config(TensorShape(224U, 222U, 64U, 3U), TensorShape(3U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U, 3U), PadStrideInfo(1, 1, 1, 1)); - add_config(TensorShape(112U, 113U, 64U, 2U), TensorShape(3U, 3U, 64U, 128U), TensorShape(128U), TensorShape(110U, 111U, 128U, 2U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(3U, 3U, 127U, 128U), TensorShape(128U), TensorShape(111U, 112U, 128U, 4U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(224U, 222U, 32U), TensorShape(3U, 3U, 32U, 32U), TensorShape(32U), TensorShape(224U, 222U, 32U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(112U, 113U, 32U), TensorShape(3U, 3U, 32U, 64U), TensorShape(64U), TensorShape(112U, 113U, 64U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(112U, 112U, 64U), TensorShape(3U, 3U, 64U, 129U), TensorShape(129U), TensorShape(112U, 112U, 129U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(53U, 56U, 125U), TensorShape(3U, 3U, 125U, 128U), TensorShape(128U), TensorShape(51U, 54U, 128U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(56U, 56U, 128U), TensorShape(3U, 3U, 128U, 128U), TensorShape(128U), TensorShape(54U, 54U, 128U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(28U, 28U, 257U), TensorShape(3U, 3U, 257U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 1, 1)); + + // Batch > 1 + add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(3U, 3U, 127U, 64U), TensorShape(64U), TensorShape(111U, 112U, 64U, 4U), PadStrideInfo(1, 1, 1, 1)); + } +}; + +class LargeWinogradConvolutionLayer3x3DatasetFp16Subset final : public ConvolutionLayerDataset +{ +public: + LargeWinogradConvolutionLayer3x3DatasetFp16Subset() + { + // Kernel size 3 + // Batch size 1 + add_config(TensorShape(224U, 222U, 32U), TensorShape(3U, 3U, 32U, 32U), TensorShape(32U), TensorShape(224U, 222U, 32U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(112U, 112U, 64U), TensorShape(3U, 3U, 64U, 129U), TensorShape(129U), TensorShape(112U, 112U, 129U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(56U, 56U, 128U), TensorShape(3U, 3U, 128U, 128U), TensorShape(128U), TensorShape(54U, 54U, 128U), PadStrideInfo(1, 1, 0, 0)); + + // Batch > 1 + add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(3U, 3U, 127U, 64U), TensorShape(64U), TensorShape(111U, 112U, 64U, 4U), PadStrideInfo(1, 1, 1, 1)); } }; @@ -66,18 +79,31 @@ public: { // Kernel size 3 // Batch size 1 - add_config(TensorShape(224U, 222U, 64U), TensorShape(3U, 1U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U), PadStrideInfo(1, 1, 1, 0)); - add_config(TensorShape(112U, 113U, 64U), TensorShape(3U, 1U, 64U, 128U), TensorShape(128U), TensorShape(112U, 113U, 128U), PadStrideInfo(1, 1, 1, 0)); - add_config(TensorShape(112U, 112U, 128U), TensorShape(3U, 1U, 128U, 129U), TensorShape(129U), TensorShape(112U, 112U, 129U), PadStrideInfo(1, 1, 1, 0)); - add_config(TensorShape(53U, 56U, 125U), TensorShape(3U, 1U, 125U, 256U), TensorShape(256U), TensorShape(51U, 56U, 256U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(56U, 56U, 256U), TensorShape(3U, 1U, 256U, 256U), TensorShape(256U), TensorShape(56U, 56U, 256U), PadStrideInfo(1, 1, 1, 0)); - add_config(TensorShape(28U, 28U, 257U), TensorShape(3U, 1U, 257U, 512U), TensorShape(512U), TensorShape(26U, 28U, 512U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(28U, 28U, 512U), TensorShape(3U, 1U, 512U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 0)); - add_config(TensorShape(14U, 14U, 512U), TensorShape(3U, 1U, 512U, 512U), TensorShape(512U), TensorShape(12U, 14U, 512U), PadStrideInfo(1, 1, 0, 0)); - // Batch size 3, 2 and 4 - add_config(TensorShape(224U, 222U, 64U, 3U), TensorShape(3U, 1U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U, 3U), PadStrideInfo(1, 1, 1, 0)); - add_config(TensorShape(112U, 113U, 64U, 2U), TensorShape(3U, 1U, 64U, 128U), TensorShape(128U), TensorShape(110U, 113U, 128U, 2U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(3U, 1U, 127U, 128U), TensorShape(128U), TensorShape(111U, 112U, 128U, 4U), PadStrideInfo(1, 1, 1, 0)); + add_config(TensorShape(224U, 222U, 32U), TensorShape(3U, 1U, 32U, 32U), TensorShape(32U), TensorShape(224U, 222U, 32U), PadStrideInfo(1, 1, 1, 0)); + add_config(TensorShape(112U, 113U, 32U), TensorShape(3U, 1U, 32U, 64U), TensorShape(64U), TensorShape(112U, 113U, 64U), PadStrideInfo(1, 1, 1, 0)); + add_config(TensorShape(112U, 112U, 64U), TensorShape(3U, 1U, 64U, 129U), TensorShape(129U), TensorShape(112U, 112U, 129U), PadStrideInfo(1, 1, 1, 0)); + add_config(TensorShape(53U, 56U, 125U), TensorShape(3U, 1U, 125U, 128U), TensorShape(128U), TensorShape(51U, 56U, 128U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(56U, 56U, 128U), TensorShape(3U, 1U, 128U, 128U), TensorShape(128U), TensorShape(56U, 56U, 128U), PadStrideInfo(1, 1, 1, 0)); + add_config(TensorShape(28U, 28U, 257U), TensorShape(3U, 1U, 257U, 128U), TensorShape(128U), TensorShape(26U, 28U, 128U), PadStrideInfo(1, 1, 0, 0)); + + // Batch > 1 + add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(3U, 1U, 127U, 64U), TensorShape(64U), TensorShape(111U, 112U, 64U, 4U), PadStrideInfo(1, 1, 1, 0)); + } +}; + +class LargeWinogradConvolutionLayer3x1DatasetFp16Subset final : public ConvolutionLayerDataset +{ +public: + LargeWinogradConvolutionLayer3x1DatasetFp16Subset() + { + // Kernel size 3 + // Batch size 1 + add_config(TensorShape(112U, 113U, 32U), TensorShape(3U, 1U, 32U, 64U), TensorShape(64U), TensorShape(112U, 113U, 64U), PadStrideInfo(1, 1, 1, 0)); + add_config(TensorShape(53U, 56U, 125U), TensorShape(3U, 1U, 125U, 128U), TensorShape(128U), TensorShape(51U, 56U, 128U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(28U, 28U, 257U), TensorShape(3U, 1U, 257U, 128U), TensorShape(128U), TensorShape(26U, 28U, 128U), PadStrideInfo(1, 1, 0, 0)); + + // Batch > 1 + add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(3U, 1U, 127U, 64U), TensorShape(64U), TensorShape(111U, 112U, 64U, 4U), PadStrideInfo(1, 1, 1, 0)); } }; @@ -88,18 +114,31 @@ public: { // Kernel size 3 // Batch size 1 - add_config(TensorShape(224U, 222U, 64U), TensorShape(1U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U), PadStrideInfo(1, 1, 0, 1)); - add_config(TensorShape(112U, 113U, 64U), TensorShape(1U, 3U, 64U, 128U), TensorShape(128U), TensorShape(112U, 113U, 128U), PadStrideInfo(1, 1, 0, 1)); - add_config(TensorShape(112U, 112U, 128U), TensorShape(1U, 3U, 128U, 129U), TensorShape(129U), TensorShape(112U, 110U, 129U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(53U, 56U, 125U), TensorShape(1U, 3U, 125U, 256U), TensorShape(256U), TensorShape(53U, 56U, 256U), PadStrideInfo(1, 1, 0, 1)); - add_config(TensorShape(56U, 56U, 256U), TensorShape(1U, 3U, 256U, 256U), TensorShape(256U), TensorShape(56U, 54U, 256U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(28U, 28U, 257U), TensorShape(1U, 3U, 257U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 0, 1)); - add_config(TensorShape(28U, 28U, 512U), TensorShape(1U, 3U, 512U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 0, 1)); - add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 3U, 512U, 512U), TensorShape(512U), TensorShape(14U, 12U, 512U), PadStrideInfo(1, 1, 0, 0)); - // Batch size 3, 2 and 4 - add_config(TensorShape(224U, 222U, 64U, 3U), TensorShape(1U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U, 3U), PadStrideInfo(1, 1, 0, 1)); - add_config(TensorShape(112U, 113U, 64U, 2U), TensorShape(1U, 3U, 64U, 128U), TensorShape(128U), TensorShape(112U, 113U, 128U, 2U), PadStrideInfo(1, 1, 0, 1)); - add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(1U, 3U, 127U, 128U), TensorShape(128U), TensorShape(111U, 112U, 128U, 4U), PadStrideInfo(1, 1, 0, 1)); + add_config(TensorShape(224U, 222U, 32U), TensorShape(1U, 3U, 32U, 32U), TensorShape(32U), TensorShape(224U, 222U, 32U), PadStrideInfo(1, 1, 0, 1)); + add_config(TensorShape(112U, 113U, 32U), TensorShape(1U, 3U, 32U, 64U), TensorShape(64U), TensorShape(112U, 113U, 64U), PadStrideInfo(1, 1, 0, 1)); + add_config(TensorShape(112U, 112U, 64U), TensorShape(1U, 3U, 64U, 129U), TensorShape(129U), TensorShape(112U, 110U, 129U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(53U, 56U, 125U), TensorShape(1U, 3U, 125U, 128U), TensorShape(128U), TensorShape(53U, 56U, 128U), PadStrideInfo(1, 1, 0, 1)); + add_config(TensorShape(56U, 56U, 128U), TensorShape(1U, 3U, 128U, 128U), TensorShape(128U), TensorShape(56U, 54U, 128U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(28U, 28U, 257U), TensorShape(1U, 3U, 257U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 0, 1)); + + // Batch > 1 + add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(1U, 3U, 127U, 64U), TensorShape(64U), TensorShape(111U, 112U, 64U, 4U), PadStrideInfo(1, 1, 0, 1)); + } +}; + +class LargeWinogradConvolutionLayer1x3DatasetFp16Subset final : public ConvolutionLayerDataset +{ +public: + LargeWinogradConvolutionLayer1x3DatasetFp16Subset() + { + // Kernel size 3 + // Batch size 1 + add_config(TensorShape(112U, 112U, 64U), TensorShape(1U, 3U, 64U, 129U), TensorShape(129U), TensorShape(112U, 110U, 129U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(53U, 56U, 125U), TensorShape(1U, 3U, 125U, 128U), TensorShape(128U), TensorShape(53U, 56U, 128U), PadStrideInfo(1, 1, 0, 1)); + add_config(TensorShape(28U, 28U, 257U), TensorShape(1U, 3U, 257U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 0, 1)); + + // Batch > 1 + add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(1U, 3U, 127U, 64U), TensorShape(64U), TensorShape(111U, 112U, 64U, 4U), PadStrideInfo(1, 1, 0, 1)); } }; @@ -110,15 +149,27 @@ public: { // Kernel size 5 // Batch size 1 - add_config(TensorShape(224U, 224U, 3U), TensorShape(5U, 5U, 3U, 64U), TensorShape(64U), TensorShape(220U, 220U, 64U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(123U, 134U, 16U), TensorShape(5U, 5U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U), PadStrideInfo(1, 1, 2, 2)); + add_config(TensorShape(224U, 224U, 3U), TensorShape(5U, 5U, 3U, 32U), TensorShape(32U), TensorShape(220U, 220U, 32U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(181U, 152U, 42U), TensorShape(5U, 5U, 42U, 100U), TensorShape(100U), TensorShape(177U, 148U, 100U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(200U, 201U, 24U), TensorShape(5U, 5U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 2, 2)); - // Batch size 2, 3 and 4 - add_config(TensorShape(224U, 224U, 3U, 2U), TensorShape(5U, 5U, 3U, 64U), TensorShape(64U), TensorShape(220U, 220U, 64U, 2U), PadStrideInfo(1, 1, 0, 0)); + // Batch > 1 + add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(5U, 5U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U, 3U), PadStrideInfo(1, 1, 2, 2)); + } +}; + +class LargeWinogradConvolutionLayer5x5DatasetFp16Subset final : public ConvolutionLayerDataset +{ +public: + LargeWinogradConvolutionLayer5x5DatasetFp16Subset() + { + // Kernel size 5 + // Batch size 1 + add_config(TensorShape(181U, 152U, 42U), TensorShape(5U, 5U, 42U, 100U), TensorShape(100U), TensorShape(177U, 148U, 100U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(200U, 201U, 24U), TensorShape(5U, 5U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 2, 2)); + + // Batch > 1 add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(5U, 5U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U, 3U), PadStrideInfo(1, 1, 2, 2)); - add_config(TensorShape(181U, 152U, 42U, 4U), TensorShape(5U, 5U, 42U, 100U), TensorShape(100U), TensorShape(177U, 148U, 100U, 4U), PadStrideInfo(1, 1, 0, 0)); } }; @@ -128,15 +179,26 @@ public: LargeWinogradConvolutionLayer5x1Dataset() { // Batch size 1 - add_config(TensorShape(224U, 224U, 3U), TensorShape(5U, 1U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U), PadStrideInfo(1, 1, 2, 0)); - add_config(TensorShape(123U, 134U, 16U), TensorShape(5U, 1U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U), PadStrideInfo(1, 1, 2, 0)); + add_config(TensorShape(224U, 224U, 3U), TensorShape(5U, 1U, 3U, 32U), TensorShape(32U), TensorShape(224U, 224U, 32U), PadStrideInfo(1, 1, 2, 0)); add_config(TensorShape(181U, 152U, 42U), TensorShape(5U, 1U, 42U, 100U), TensorShape(100U), TensorShape(177U, 152U, 100U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(200U, 201U, 24U), TensorShape(5U, 1U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 2, 0)); - // Batch size 2, 3 and 4 - add_config(TensorShape(224U, 224U, 3U, 2U), TensorShape(5U, 1U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U, 2U), PadStrideInfo(1, 1, 2, 0)); + // Batch > 1 + add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(5U, 1U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U, 3U), PadStrideInfo(1, 1, 2, 0)); + } +}; + +class LargeWinogradConvolutionLayer5x1DatasetFp16Subset final : public ConvolutionLayerDataset +{ +public: + LargeWinogradConvolutionLayer5x1DatasetFp16Subset() + { + // Batch size 1 + add_config(TensorShape(224U, 224U, 3U), TensorShape(5U, 1U, 3U, 32U), TensorShape(32U), TensorShape(224U, 224U, 32U), PadStrideInfo(1, 1, 2, 0)); + add_config(TensorShape(200U, 201U, 24U), TensorShape(5U, 1U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 2, 0)); + + // Batch > 1 add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(5U, 1U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U, 3U), PadStrideInfo(1, 1, 2, 0)); - add_config(TensorShape(181U, 152U, 42U, 4U), TensorShape(5U, 1U, 42U, 100U), TensorShape(100U), TensorShape(177U, 152U, 100U, 4U), PadStrideInfo(1, 1, 0, 0)); } }; @@ -146,15 +208,12 @@ public: LargeWinogradConvolutionLayer7x1Dataset() { // Batch size 1 - add_config(TensorShape(224U, 224U, 3U), TensorShape(7U, 1U, 3U, 64U), TensorShape(64U), TensorShape(218U, 224U, 64U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(123U, 134U, 16U), TensorShape(7U, 1U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U), PadStrideInfo(1, 1, 3, 0)); + add_config(TensorShape(224U, 224U, 3U), TensorShape(7U, 1U, 3U, 32U), TensorShape(32U), TensorShape(218U, 224U, 32U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(181U, 152U, 42U), TensorShape(7U, 1U, 42U, 100U), TensorShape(100U), TensorShape(175U, 152U, 100U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(200U, 201U, 24U), TensorShape(7U, 1U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 3, 0)); - // Batch size 2, 3 and 4 - add_config(TensorShape(224U, 224U, 3U, 2U), TensorShape(7U, 1U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U, 2U), PadStrideInfo(1, 1, 3, 0)); + // Batch > 1 add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(7U, 1U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U, 3U), PadStrideInfo(1, 1, 3, 0)); - add_config(TensorShape(181U, 152U, 42U, 4U), TensorShape(7U, 1U, 42U, 100U), TensorShape(100U), TensorShape(175U, 152U, 100U, 4U), PadStrideInfo(1, 1, 0, 0)); } }; @@ -164,15 +223,26 @@ public: LargeWinogradConvolutionLayer1x7Dataset() { // Batch size 1 - add_config(TensorShape(224U, 224U, 3U), TensorShape(1U, 7U, 3U, 64U), TensorShape(64U), TensorShape(224U, 218U, 64U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(123U, 134U, 16U), TensorShape(1U, 7U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U), PadStrideInfo(1, 1, 0, 3)); + add_config(TensorShape(224U, 224U, 3U), TensorShape(1U, 7U, 3U, 32U), TensorShape(32U), TensorShape(224U, 218U, 32U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(181U, 152U, 42U), TensorShape(1U, 7U, 42U, 100U), TensorShape(100U), TensorShape(181U, 146U, 100U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(200U, 201U, 24U), TensorShape(1U, 7U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 0, 3)); + + // Batch > 1 + add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(1U, 7U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U, 3U), PadStrideInfo(1, 1, 0, 3)); + } +}; + +class LargeWinogradConvolutionLayer1x7DatasetFp16Subset final : public ConvolutionLayerDataset +{ +public: + LargeWinogradConvolutionLayer1x7DatasetFp16Subset() + { + // Batch size 1 add_config(TensorShape(181U, 152U, 42U), TensorShape(1U, 7U, 42U, 100U), TensorShape(100U), TensorShape(181U, 146U, 100U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(200U, 201U, 24U), TensorShape(1U, 7U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 0, 3)); - // Batch size 2, 3 and 4 - add_config(TensorShape(224U, 224U, 3U, 2U), TensorShape(1U, 7U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U, 2U), PadStrideInfo(1, 1, 0, 3)); + // Batch > 1 add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(1U, 7U, 16U, 7U), TensorShape(7U), TensorShape(123U, 134U, 7U, 3U), PadStrideInfo(1, 1, 0, 3)); - add_config(TensorShape(181U, 152U, 42U, 4U), TensorShape(1U, 7U, 42U, 100U), TensorShape(100U), TensorShape(181U, 146U, 100U, 4U), PadStrideInfo(1, 1, 0, 0)); } }; @@ -182,15 +252,26 @@ public: LargeWinogradConvolutionLayer1x5Dataset() { // Batch size 1 - add_config(TensorShape(224U, 224U, 3U), TensorShape(1U, 5U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U), PadStrideInfo(1, 1, 0, 2)); - add_config(TensorShape(123U, 134U, 16U), TensorShape(1U, 5U, 16U, 7U), TensorShape(7U), TensorShape(123U, 130U, 7U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(224U, 224U, 3U), TensorShape(1U, 5U, 3U, 32U), TensorShape(32U), TensorShape(224U, 224U, 32U), PadStrideInfo(1, 1, 0, 2)); add_config(TensorShape(181U, 152U, 42U), TensorShape(1U, 5U, 42U, 100U), TensorShape(100U), TensorShape(181U, 148U, 100U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(200U, 201U, 24U), TensorShape(1U, 5U, 24U, 61), TensorShape(61U), TensorShape(200U, 201U, 61), PadStrideInfo(1, 1, 0, 2)); - // Batch size 2, 3 and 4 - add_config(TensorShape(224U, 224U, 3U, 2U), TensorShape(1U, 5U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U, 2U), PadStrideInfo(1, 1, 0, 2)); + // Batch size > 1 + add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(1U, 5U, 16U, 7U), TensorShape(7U), TensorShape(123U, 130U, 7U, 3U), PadStrideInfo(1, 1, 0, 0)); + } +}; + +class LargeWinogradConvolutionLayer1x5DatasetFp16Subset final : public ConvolutionLayerDataset +{ +public: + LargeWinogradConvolutionLayer1x5DatasetFp16Subset() + { + // Batch size 1 + add_config(TensorShape(224U, 224U, 3U), TensorShape(1U, 5U, 3U, 32U), TensorShape(32U), TensorShape(224U, 224U, 32U), PadStrideInfo(1, 1, 0, 2)); + add_config(TensorShape(181U, 152U, 42U), TensorShape(1U, 5U, 42U, 100U), TensorShape(100U), TensorShape(181U, 148U, 100U), PadStrideInfo(1, 1, 0, 0)); + + // Batch size > 1 add_config(TensorShape(123U, 134U, 16U, 3U), TensorShape(1U, 5U, 16U, 7U), TensorShape(7U), TensorShape(123U, 130U, 7U, 3U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(181U, 152U, 42U, 4U), TensorShape(1U, 5U, 42U, 100U), TensorShape(100U), TensorShape(181U, 148U, 100U, 4U), PadStrideInfo(1, 1, 0, 0)); } }; @@ -233,4 +314,4 @@ public: } // namespace datasets } // namespace test } // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_LARGE_CONVOLUTION_LAYER_DATASET */ +#endif // ACL_TESTS_DATASETS_LARGECONVOLUTIONLAYERDATASET_H -- cgit v1.2.1