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>
diff --git a/tests/datasets/LargeConvolutionLayerDataset.h b/tests/datasets/LargeConvolutionLayerDataset.h
index 40a8855..20a73b8 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 @@
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 @@
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 e85978c..e426b28 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 @@
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 0d8a322..6d80bf1 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -175,75 +175,18 @@
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(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 @@
});
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 @@
// 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 @@
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 @@
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(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 364eb6e..2813d29 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 @@
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 d3772bb..19f69d12 100644
--- a/tests/validation/NEON/ConvolutionLayer.cpp
+++ b/tests/validation/NEON/ConvolutionLayer.cpp
@@ -367,63 +367,17 @@
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 @@
#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 @@
#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 @@
});
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 @@
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 @@
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 })),