diff options
author | Michele Di Giorgio <michele.digiorgio@arm.com> | 2020-04-29 15:14:18 +0100 |
---|---|---|
committer | Michele Di Giorgio <michele.digiorgio@arm.com> | 2020-05-13 10:02:20 +0000 |
commit | e37662a34659a2d6649b9793e62f6a9110437684 (patch) | |
tree | 325593180725c774d22d3b46ef710e728afae877 /tests | |
parent | ea2ce177dd444b5670e12d5b427359ce77b8cc89 (diff) | |
download | ComputeLibrary-e37662a34659a2d6649b9793e62f6a9110437684.tar.gz |
COMPMID-3128: Test improvement for GEMMConvolutionLayer on CL and NEON(Function-level)
Cleaning up GEMMConvolutionLayer tests by doing the following:
- Remove unnecessary configuration tests
- Remove redundant tests
> Redundant shapes
> For large shapes there are already tests for each internal kernel/function
- Test NHWC 1x1 kernel 1x1 stride to stress _skip_im2col
- Stimulate gemm3d to skip col2im
- Test asymmetric padding
- Test batch size equal to one and different than one
- Test fully connected convolution
- Test with a few different padding values
- Test 1D kernel
- Test with FLOOR rounding policy
Change-Id: I88e7009b8e9c991994ed264476c16a79a0de4a68
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3150
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Diffstat (limited to 'tests')
-rw-r--r-- | tests/datasets/LargeConvolutionLayerDataset.h | 21 | ||||
-rw-r--r-- | tests/datasets/SmallConvolutionLayerDataset.h | 41 | ||||
-rw-r--r-- | tests/validation/CL/ConvolutionLayer.cpp | 192 | ||||
-rw-r--r-- | tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp | 46 | ||||
-rw-r--r-- | tests/validation/NEON/ConvolutionLayer.cpp | 142 |
5 files changed, 79 insertions, 363 deletions
diff --git a/tests/datasets/LargeConvolutionLayerDataset.h b/tests/datasets/LargeConvolutionLayerDataset.h index 40a8855ace..20a73b871b 100644 --- a/tests/datasets/LargeConvolutionLayerDataset.h +++ b/tests/datasets/LargeConvolutionLayerDataset.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -197,31 +197,19 @@ public: class LargeConvolutionLayerDataset final : public ConvolutionLayerDataset { public: + /** Shapes taken from use-cases such as AlexNet, MobileNet, SqueezeNet, etc. */ LargeConvolutionLayerDataset() { // Batch size 1 add_config(TensorShape(227U, 227U, 3U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U), PadStrideInfo(4, 4, 0, 0)); add_config(TensorShape(27U, 27U, 96U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U), PadStrideInfo(1, 1, 2, 2)); add_config(TensorShape(13U, 13U, 256U), TensorShape(1U, 1U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(13U, 13U, 384U), TensorShape(1U, 1U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(224U, 224U, 3U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U), PadStrideInfo(2, 2, 3, 3)); - add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0)); // Batch size 4 add_config(TensorShape(227U, 227U, 3U, 4U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 4U), PadStrideInfo(4, 4, 0, 0)); add_config(TensorShape(27U, 27U, 96U, 4U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 4U), PadStrideInfo(1, 1, 2, 2)); add_config(TensorShape(13U, 13U, 256U, 4U), TensorShape(1U, 1U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(13U, 13U, 384U, 4U), TensorShape(1U, 1U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(224U, 224U, 3U, 4U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U, 4U), PadStrideInfo(2, 2, 3, 3)); - add_config(TensorShape(28U, 28U, 256U, 4U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U, 4U), PadStrideInfo(1, 1, 0, 0)); - // Batch size 8 - add_config(TensorShape(227U, 227U, 3U, 8U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 8U), PadStrideInfo(4, 4, 0, 0)); - add_config(TensorShape(27U, 27U, 96U, 8U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 8U), PadStrideInfo(1, 1, 2, 2)); - add_config(TensorShape(13U, 13U, 256U, 8U), TensorShape(1U, 1U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(13U, 13U, 384U, 8U), TensorShape(1U, 1U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 0, 0)); - add_config(TensorShape(224U, 224U, 3U, 8U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U, 8U), PadStrideInfo(2, 2, 3, 3)); - add_config(TensorShape(28U, 28U, 256U, 8U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U, 8U), PadStrideInfo(1, 1, 0, 0)); - // Arbitrary batch size - add_config(TensorShape(227U, 227U, 3U, 5U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 5U), PadStrideInfo(4, 4, 0, 0)); } }; @@ -240,11 +228,6 @@ public: add_config(TensorShape(27U, 27U, 96U, 4U), TensorShape(5U, 5U, 24U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 4U), PadStrideInfo(1, 1, 2, 2)); add_config(TensorShape(13U, 13U, 256U, 4U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 1, 1)); add_config(TensorShape(13U, 13U, 384U, 4U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 1, 1)); - // Batch size 8 - add_config(TensorShape(227U, 227U, 4U, 8U), TensorShape(11U, 11U, 2U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 8U), PadStrideInfo(4, 4, 0, 0)); - add_config(TensorShape(27U, 27U, 96U, 8U), TensorShape(5U, 5U, 24U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 8U), PadStrideInfo(1, 1, 2, 2)); - add_config(TensorShape(13U, 13U, 256U, 8U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 1, 1)); - add_config(TensorShape(13U, 13U, 384U, 8U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 1, 1)); } }; } // namespace datasets diff --git a/tests/datasets/SmallConvolutionLayerDataset.h b/tests/datasets/SmallConvolutionLayerDataset.h index e85978c49a..e426b288b4 100644 --- a/tests/datasets/SmallConvolutionLayerDataset.h +++ b/tests/datasets/SmallConvolutionLayerDataset.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -149,38 +149,33 @@ class SmallConvolutionLayerDataset final : public ConvolutionLayerDataset public: SmallConvolutionLayerDataset() { - add_config(TensorShape(224U, 224U, 3U), TensorShape(3U, 3U, 3U, 32U), TensorShape(32U), TensorShape(112U, 112U, 32U), - PadStrideInfo(2, 2, /*left*/ 0, /*right*/ 1, /*top*/ 0, /*bottom*/ 1, DimensionRoundingType::FLOOR)); - // 1D Kernel add_config(TensorShape(1U, 5U, 2U), TensorShape(1U, 3U, 2U, 3U), TensorShape(3U), TensorShape(1U, 7U, 3U), PadStrideInfo(1, 1, 0, 0, 2, 2, DimensionRoundingType::FLOOR)); + // 1x1 Kernel with Stride (1, 1) and NHWC data layout in order to test skipping Im2Col + add_config(TensorShape(1U, 5U, 2U), TensorShape(1U, 1U, 2U, 3U), TensorShape(3U), TensorShape(1U, 5U, 3U), PadStrideInfo(1, 1, 0, 0)); + // Batch size 1 - add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0)); - add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0)); - add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U), PadStrideInfo(1, 2, 1, 1)); - add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U), PadStrideInfo(2, 1, 0, 0)); - add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U), PadStrideInfo(3, 2, 1, 0)); - add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U), PadStrideInfo(1, 2, 1, 1)); - add_config(TensorShape(3U, 3U, 1U), TensorShape(2U, 2U, 1U, 11U), TensorShape(11U), TensorShape(2U, 2U, 11U), PadStrideInfo(1, 1, 0, 0)); - // Batch size 4 + add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 2U), TensorShape(2U), TensorShape(11U, 25U, 2U), PadStrideInfo(2, 1, 0, 0)); + add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 3U), TensorShape(3U), TensorShape(11U, 12U, 3U), PadStrideInfo(3, 2, 1, 0)); + add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 4U), TensorShape(4U), TensorShape(15U, 15U, 4U), PadStrideInfo(1, 2, 1, 1)); + add_config(TensorShape(3U, 3U, 1U), TensorShape(2U, 2U, 1U, 5U), TensorShape(5U), TensorShape(2U, 2U, 5U), PadStrideInfo(1, 1, 0, 0)); + + // Batch size different than one add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U, 4U), PadStrideInfo(2, 1, 0, 0)); add_config(TensorShape(33U, 27U, 7U, 4U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 4U), PadStrideInfo(3, 2, 1, 0)); add_config(TensorShape(17U, 31U, 2U, 4U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U, 4U), PadStrideInfo(1, 2, 1, 1)); - add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U, 4U), PadStrideInfo(2, 1, 0, 0)); - add_config(TensorShape(33U, 27U, 7U, 4U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U, 4U), PadStrideInfo(3, 2, 1, 0)); - add_config(TensorShape(17U, 31U, 2U, 4U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U, 4U), PadStrideInfo(1, 2, 1, 1)); - // Arbitrary batch size - add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U, 5U), PadStrideInfo(3, 2, 1, 0)); + // FC convolution add_config(TensorShape(1U, 1U, 1024U), TensorShape(1U, 1U, 1024U, 1001U), TensorShape(1001U), TensorShape(1U, 1U, 1001U), PadStrideInfo(1, 1, 0, 0)); + // Asymmetric padding - add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR)); - add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR)); - add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR)); - add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 3, 0, 2, DimensionRoundingType::FLOOR)); - add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 1, 0, 1, 0, DimensionRoundingType::FLOOR)); - add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR)); + add_config(TensorShape(33U, 27U, 3U), TensorShape(5U, 7U, 3U, 4U), TensorShape(4U), TensorShape(11U, 12U, 4U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR)); + add_config(TensorShape(33U, 27U, 3U), TensorShape(5U, 7U, 3U, 4U), TensorShape(4U), TensorShape(11U, 12U, 4U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR)); + add_config(TensorShape(33U, 27U, 3U), TensorShape(5U, 7U, 3U, 4U), TensorShape(4U), TensorShape(11U, 12U, 4U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR)); + add_config(TensorShape(33U, 27U, 3U), TensorShape(5U, 7U, 3U, 4U), TensorShape(4U), TensorShape(11U, 12U, 4U), PadStrideInfo(3, 2, 1, 3, 0, 2, DimensionRoundingType::FLOOR)); + add_config(TensorShape(33U, 27U, 3U), TensorShape(5U, 7U, 3U, 4U), TensorShape(4U), TensorShape(10U, 11U, 4U), PadStrideInfo(3, 2, 1, 0, 1, 0, DimensionRoundingType::FLOOR)); + add_config(TensorShape(33U, 27U, 3U), TensorShape(5U, 7U, 3U, 4U), TensorShape(4U), TensorShape(10U, 11U, 4U), PadStrideInfo(3, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR)); add_config(TensorShape(5U, 4U, 3U, 2U), TensorShape(4U, 4U, 3U, 1U), TensorShape(1U), TensorShape(2U, 1U, 1U, 2U), PadStrideInfo(1, 1, 0, 0, 0, 0, DimensionRoundingType::FLOOR)); } diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp index 0d8a322694..6d80bf1a4c 100644 --- a/tests/validation/CL/ConvolutionLayer.cpp +++ b/tests/validation/CL/ConvolutionLayer.cpp @@ -175,75 +175,18 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z TEST_SUITE_END() // ConvolutionLayer TEST_SUITE(GEMMConvolutionLayer) - -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::SmallConvolutionLayerDataset(), - CNNDataTypes), - ActivationFunctionsDataset), - input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info) -{ - auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; - - // Create tensors - CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - const QuantizationInfo src_quantization_info = src.info()->quantization_info(); - const QuantizationInfo weights_quantization_info = weights.info()->quantization_info(); - - // Create and configure function - CLGEMMConvolutionLayer conv; - conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info); - - // Validate valid region - const ValidRegion src_valid_region = shape_to_valid_region(input_shape); - const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); - const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); - const ValidRegion dst_valid_region = shape_to_valid_region(output_shape); - - validate(src.info()->valid_region(), src_valid_region); - validate(weights.info()->valid_region(), weights_valid_region); - validate(bias.info()->valid_region(), bias_valid_region); - validate(dst.info()->valid_region(), dst_valid_region); - - // Validate QuantizationInfo - ARM_COMPUTE_EXPECT(src.info()->quantization_info() == src_quantization_info, framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->quantization_info() == weights_quantization_info, framework::LogLevel::ERRORS); - - // Validate padding - //TODO(COMPMID-415) Need to validate padding? -} - template <typename T> using CLGEMMConvolutionLayerFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>; TEST_SUITE(Float) TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - ActivationFunctionsSmallDataset)) -{ - // Validate output - validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); -} - -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, - combine(combine(combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - ActivationFunctionsDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", + DataType::F16)), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + ActivationFunctionsSmallDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); @@ -252,28 +195,16 @@ TEST_SUITE_END() // FP16 TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - ActivationFunctionsSmallDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", + DataType::F32)), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + ActivationFunctionsSmallDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } - -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, - combine(combine(combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - ActivationFunctionsDataset)) -{ - // Validate output - validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, absolute_tolerance_float); -} TEST_SUITE_END() // FP32 TEST_SUITE_END() // Float @@ -304,8 +235,8 @@ const auto QuantizationData = framework::dataset::make("QuantizationInfo", }); TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, - combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), @@ -315,22 +246,11 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t> // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, - combine(combine(combine(combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - QuantizationData), - QuantizedActivationFunctionsDataset)) -{ - // Validate output - validate(CLAccessor(_target), _reference, tolerance_qasymm8); -} TEST_SUITE_END() // QASYMM8 TEST_SUITE(QASYMM8_SIGNED) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, - combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), @@ -343,25 +263,13 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<int8_t>, TEST_SUITE_END() // QASYMM8_SIGNED TEST_SUITE(QSYMM8_PER_CHANNEL) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, - combine(combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", { DataType::QASYMM8 })), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - QuantizationData), - QuantizedActivationFunctionsSmallDataset), - framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL }))) -{ - // Validate output - validate(CLAccessor(_target), _reference, tolerance_qasymm8); -} -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::NIGHTLY, +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", { DataType::QASYMM8 })), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), QuantizationData), - QuantizedActivationFunctionsDataset), + QuantizedActivationFunctionsSmallDataset), framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL }))) { // Validate output @@ -377,61 +285,21 @@ using CLGEMMGroupedConvolutionLayerFixture = ConvolutionValidationFixture<CLTens TEST_SUITE(GroupedGEMMConvolutionLayer) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::SmallGroupedConvolutionLayerDataset(), - GroupedCNNDataTypes), - ActivationFunctionsDataset), - input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info) -{ - ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0); - - // The number of groups is calculated dividing the number of input channels of the input tensor by the number of input channels of the weights shape - const int num_groups = input_shape[2] / weights_shape[2]; - - // Create tensors - CLTensor src = create_tensor<CLTensor>(input_shape, data_type); - CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1); - CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type, 1); - CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1); - - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Create and configure function - CLGEMMConvolutionLayer conv; - conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info, num_groups); - - // Validate valid region - const ValidRegion src_valid_region = shape_to_valid_region(input_shape); - const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); - const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); - const ValidRegion dst_valid_region = shape_to_valid_region(output_shape); - - validate(src.info()->valid_region(), src_valid_region); - validate(weights.info()->valid_region(), weights_valid_region); - validate(bias.info()->valid_region(), bias_valid_region); - validate(dst.info()->valid_region(), dst_valid_region); - - // Validate padding - //TODO(COMPMID-415) Need to validate padding? -} - TEST_SUITE(Float) TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), - ActivationFunctionsSmallDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("DataLayout", { DataLayout::NCHW })), + ActivationFunctionsSmallDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num); } FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, - combine(combine(combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()), + combine(combine(combine(combine(datasets::LargeGroupedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), @@ -444,18 +312,18 @@ TEST_SUITE_END() // FP32 TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), - ActivationFunctionsSmallDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataLayout", { DataLayout::NCHW })), + ActivationFunctionsSmallDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num); } FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, - combine(combine(combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()), + combine(combine(combine(combine(datasets::LargeGroupedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), diff --git a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp index 364eb6e6d2..2813d29e72 100644 --- a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp +++ b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -65,50 +65,6 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo TEST_SUITE(GC) TEST_SUITE(ConvolutionLayer) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::SmallConvolutionLayerReducedDataset(), - CNNDataTypes), - ActivationFunctionsDataset), - input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info) -{ - auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; - - // Create tensors - GCTensor src = create_tensor<GCTensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - GCTensor weights = create_tensor<GCTensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - GCTensor bias = create_tensor<GCTensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - GCTensor dst = create_tensor<GCTensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - const QuantizationInfo src_quantization_info = src.info()->quantization_info(); - const QuantizationInfo weights_quantization_info = weights.info()->quantization_info(); - - // Create and configure function - GCConvolutionLayer conv; - conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info); - - // Validate valid region - const ValidRegion src_valid_region = shape_to_valid_region(input_shape); - const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); - const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); - const ValidRegion dst_valid_region = shape_to_valid_region(output_shape); - - validate(src.info()->valid_region(), src_valid_region); - validate(weights.info()->valid_region(), weights_valid_region); - validate(bias.info()->valid_region(), bias_valid_region); - validate(dst.info()->valid_region(), dst_valid_region); - - // Validate QuantizationInfo - ARM_COMPUTE_EXPECT(src.info()->quantization_info() == src_quantization_info, framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->quantization_info() == weights_quantization_info, framework::LogLevel::ERRORS); - - //Validate padding - //TODO(COMPMID-415) Need to validate padding? -} - template <typename T> using GCConvolutionLayerFixture = ConvolutionValidationFixture<GCTensor, GCAccessor, GCConvolutionLayer, T>; diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp index d3772bb067..19f69d120f 100644 --- a/tests/validation/NEON/ConvolutionLayer.cpp +++ b/tests/validation/NEON/ConvolutionLayer.cpp @@ -367,63 +367,17 @@ TEST_SUITE_END() // FP16 TEST_SUITE_END() // WinogradLayer TEST_SUITE(GEMMConvolutionLayer) - -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::SmallConvolutionLayerDataset(), - CNNDataTypes), - framework::dataset::make("ActivationInfo", -{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })), -input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info) -{ - auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; - - // Create tensors - Tensor src = create_tensor<Tensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - Tensor bias = create_tensor<Tensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127)); - - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - const QuantizationInfo src_quantization_info = src.info()->quantization_info(); - const QuantizationInfo weights_quantization_info = weights.info()->quantization_info(); - - // Create and configure function - NEGEMMConvolutionLayer conv; - conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info); - - // Validate valid region - const ValidRegion src_valid_region = shape_to_valid_region(input_shape); - const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); - const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); - const ValidRegion dst_valid_region = shape_to_valid_region(output_shape); - - validate(src.info()->valid_region(), src_valid_region); - validate(weights.info()->valid_region(), weights_valid_region); - validate(bias.info()->valid_region(), bias_valid_region); - validate(dst.info()->valid_region(), dst_valid_region); - - // Validate QuantizationInfo - ARM_COMPUTE_EXPECT(src.info()->quantization_info() == src_quantization_info, framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->quantization_info() == weights_quantization_info, framework::LogLevel::ERRORS); - - // Validate padding - //TODO(COMPMID-415) Need to validate padding? -} - template <typename T> using NEGEMMConvolutionLayerFixture = ConvolutionValidationFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>; TEST_SUITE(Float) #if defined(__ARM_FEATURE_BF16_VECTOR_ARITHMETIC) || defined(ARM_COMPUTE_FORCE_BF16) TEST_SUITE(BFLOAT16) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::BFLOAT16)), - framework::dataset::make("DataLayout", { DataLayout::NHWC })), - ActivationFunctionsDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::BFLOAT16)), + framework::dataset::make("DataLayout", { DataLayout::NHWC })), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, float(abs_tolerance_f32)); @@ -433,20 +387,11 @@ TEST_SUITE_END() // BFLOAT16 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), - ActivationFunctionsDataset)) -{ - // Validate output - validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_f16); -} -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), - ActivationFunctionsDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataLayout", { DataLayout::NCHW })), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_f16); @@ -455,20 +400,11 @@ TEST_SUITE_END() // FP16 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - ActivationFunctionsDataset)) -{ - // Validate output - validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, float(abs_tolerance_f32)); -} -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - ActivationFunctionsDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, float(abs_tolerance_f32)); @@ -490,22 +426,12 @@ const auto QuantizedActivationFunctionsDataset = framework::dataset::make("Activ }); TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), - QuantizedActivationFunctionsDataset)) -{ - // Validate output - validate(Accessor(_target), _reference, tolerance_qasymm8); -} -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), - QuantizedActivationFunctionsDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); @@ -513,12 +439,12 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerQuantizedFixture<uint8_t> TEST_SUITE_END() // QASYMM8 TEST_SUITE(QASYMM8_SIGNED) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), - QuantizedActivationFunctionsDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.01f, -10) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); @@ -526,19 +452,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedFixture<int8_t>, TEST_SUITE_END() // QASYMM8_SIGNED TEST_SUITE(QSYMM8_PER_CHANNEL) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, - combine(combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", { DataType::QASYMM8 })), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), - QuantizationData), - QuantizedActivationFunctionsDataset), - framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL }))) -{ - // Validate output - validate(Accessor(_target), _reference, tolerance_qasymm8); -} -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::NIGHTLY, +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", { DataType::QASYMM8 })), |