tests/validation/CL/GEMMLowp.cpp - platform/external/ComputeLibrary - Git at Google

 /*
  * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to
  * deal in the Software without restriction, including without limitation the
  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
  * sell copies of the Software, and to permit persons to whom the Software is
  * furnished to do so, subject to the following conditions:
  *
  * The above copyright notice and this permission notice shall be included in all
  * copies or substantial portions of the Software.
  *
  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
 #include "arm_compute/core/Types.h"
 #include "arm_compute/runtime/CL/CLTensor.h"
 #include "arm_compute/runtime/CL/CLTensorAllocator.h"
 #include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
 #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
 #include "tests/CL/CLAccessor.h"
 #include "tests/PaddingCalculator.h"
 #include "tests/datasets/GEMMLowpFusedOffsetOutputDataset.h"
 #include "tests/datasets/LargeGEMMLowpDataset.h"
 #include "tests/datasets/ShapeDatasets.h"
 #include "tests/datasets/SmallGEMMLowpDataset.h"
 #include "tests/framework/Asserts.h"
 #include "tests/framework/Macros.h"
 #include "tests/framework/datasets/Datasets.h"
 #include "tests/validation/Validation.h"
 #include "tests/validation/fixtures/GEMMLowpFixture.h"

 namespace arm_compute
 {
 namespace test
 {
 namespace validation
 {
 TEST_SUITE(CL)
 TEST_SUITE(GEMMLowp)

 TEST_SUITE(MatrixMultiplyCore)

 using CLGEMMLowpMatrixMultiplyCoreFixture = GEMMLowpMatrixMultiplyCoreValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;

 DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, datasets::SmallGEMMLowpDataset(),
                shape_a, shape_b, shape_c, a_offset, b_offset)
 {
     // Create tensors
     CLTensor a = create_tensor<CLTensor>(shape_a, DataType::QASYMM8);
     CLTensor b = create_tensor<CLTensor>(shape_b, DataType::QASYMM8);
     CLTensor c = create_tensor<CLTensor>(shape_c, DataType::S32);

     a.info()->set_quantization_info(QuantizationInfo(1.0f / 255, a_offset));
     b.info()->set_quantization_info(QuantizationInfo(1.0f / 255, b_offset));

     ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS);

     // Create and configure function
     CLGEMMLowpMatrixMultiplyCore gemmlowp_mm;
     // TODO (giaiod01) COMPMID-1672 - Extending the test to validate add bias in offset contribution
     gemmlowp_mm.configure(&a, &b, nullptr, &c);
 }

 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFixture, framework::DatasetMode::ALL, datasets::SmallGEMMLowpDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;
 TEST_SUITE(FusedOffsetOutput)
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::ALL, datasets::SmallGEMMLowpFusedOffsetOutputDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpFusedOffsetOutputDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 TEST_SUITE_END() // FusedOffsetOutput

 TEST_SUITE(Output3D)
 using CLGEMMLowpMatrixMultiplyCoreOutput3DFixture = GEMMLowpMatrixMultiplyCoreValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore, false, true>;
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreOutput3DFixture, framework::DatasetMode::PRECOMMIT, datasets::SmallGEMMLowpOutput3DDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreOutput3DFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpOutput3DDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 TEST_SUITE_END() // Output3D

 TEST_SUITE(InputOutput3D)
 using CLGEMMLowpMatrixMultiplyCoreInputOutput3DFixture = GEMMLowpMatrixMultiplyCoreValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore, true, true>;
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreInputOutput3DFixture, framework::DatasetMode::PRECOMMIT, datasets::SmallGEMMLowpInputOutput3DDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreInputOutput3DFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpInputOutput3DDataset())
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 TEST_SUITE_END() // InputOutput3D
 TEST_SUITE_END() // MatrixMultiplyCore

 TEST_SUITE(OutputStage)
 TEST_SUITE(QuantizeDownInt32ToUint8Scale)

 const auto quantize_down_int32_to_uint8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_shift", 2,
                                                       3)
                                                       * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });

 const auto quantize_down_int32_to_uint8_scale_relu_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1,
                                                            2)
                                                            * framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 173) * framework::dataset::make("addBias", { false, true });

 using CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToUint8Scale>;

 DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases),
                shape, result_offset, result_mult_int, result_shift, min, max, add_bias)
 {
     TensorShape shape_bias(shape[0]);

     // Create tensors
     CLTensor in   = create_tensor<CLTensor>(shape, DataType::S32);
     CLTensor bias = create_tensor<CLTensor>(shape_bias, DataType::S32);
     CLTensor out  = create_tensor<CLTensor>(shape, DataType::QASYMM8);

     ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS);

     // Create and configure function
     CLGEMMLowpQuantizeDownInt32ToUint8Scale output_stage;
     output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_offset, result_mult_int, result_shift, min, max);

     // Validate valid region input and output
     const ValidRegion valid_region = shape_to_valid_region(shape);
     validate(in.info()->valid_region(), valid_region);
     validate(out.info()->valid_region(), valid_region);

     // Validate valid region bias
     if(add_bias)
     {
         const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias);
         validate(bias.info()->valid_region(), valid_region_bias);
     }

     // Validate padding
     const PaddingSize padding = PaddingCalculator(shape.x(), 4).required_padding();
     validate(in.info()->padding(), padding);
     validate(out.info()->padding(), padding);

     if(add_bias)
     {
         validate(bias.info()->padding(), padding);
     }
 }

 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 TEST_SUITE(BoundedReLu)
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
                        quantize_down_int32_to_uint8_scale_relu_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 TEST_SUITE_END() // BoundedReLu
 TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale

 TEST_SUITE(QuantizeDownInt32ToUint8ScaleByFixedPoint)

 const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
                                                                     2)
                                                                     * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });

 const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
                                                                          2)
                                                                          * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 174) * framework::dataset::make("addBias", { false, true });

 using CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture =
     GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint>;

 DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
                                                                    quantize_down_int32_to_uint8_scale_by_fixedpoint_cases),
                shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias)
 {
     TensorShape shape_bias(shape[0]);

     // Create tensors
     CLTensor in   = create_tensor<CLTensor>(shape, DataType::S32);
     CLTensor bias = create_tensor<CLTensor>(shape_bias, DataType::S32);
     CLTensor out  = create_tensor<CLTensor>(shape, DataType::QASYMM8);

     ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS);

     // Create and configure function
     CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint output_stage;
     output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);

     // Validate valid region input and output
     const ValidRegion valid_region = shape_to_valid_region(shape);
     validate(in.info()->valid_region(), valid_region);
     validate(out.info()->valid_region(), valid_region);

     // Validate valid region bias
     if(add_bias)
     {
         const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias);
         validate(bias.info()->valid_region(), valid_region_bias);
     }

     // Validate padding
     const PaddingSize padding = PaddingCalculator(shape.x(), 4).required_padding();
     validate(in.info()->padding(), padding);
     validate(out.info()->padding(), padding);

     if(add_bias)
     {
         validate(bias.info()->padding(), padding);
     }
 }

 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
                        quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
                        quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 TEST_SUITE(BoundedReLu)
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
                        quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }

 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
                        quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 TEST_SUITE_END() // BoundedReLu
 TEST_SUITE_END() // QuantizeDownInt32ToUint8ScaleByFixedPoint
 TEST_SUITE(QuantizeDownInt32ToInt16ScaleByFixedPoint)

 const auto quantize_down_int32_to_int16_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
                                                                     2)
                                                                     * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });

 const auto quantize_down_int32_to_int16_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
                                                                          2)
                                                                          * framework::dataset::make("min", -2, 0) * framework::dataset::make("max", 1, 3) * framework::dataset::make("addBias", { false, true });

 using CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture =
     GEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint>;

 // *INDENT-OFF*
 // clang-format off
 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
     framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::S32),
                                              TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max
                                              TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Wrong output data type
                                           }),
     framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32),
                                             TensorInfo(TensorShape(21U), 1, DataType::S32),
                                             TensorInfo(TensorShape(21U), 1, DataType::S32),
                                           })),
     framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16),
                                             TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16),
                                             TensorInfo(TensorShape(20U, 13U), 1, DataType::S32),
                                            })),
     framework::dataset::make("Min",{        -205,
                                             -60000,
                                             -180,
                                            })),
     framework::dataset::make("Max",{        205,
                                             60000,
                                             180,
                                            })),
     framework::dataset::make("Expected", { true, false, false })),
     a_info, b_info, output_info, min, max, expected)
 {
     // Lock tensors
     Status status =  CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(&a_info.clone()->set_is_resizable(true),
                                                                                  &b_info.clone()->set_is_resizable(true),
                                                                                  &output_info.clone()->set_is_resizable(true),
                                                                                  min,
                                                                                  max);
     ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on
 // *INDENT-ON*
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
                        quantize_down_int32_to_int16_scale_by_fixedpoint_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 TEST_SUITE(BoundedReLu)
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
                        quantize_down_int32_to_int16_scale_by_fixedpoint_relu_cases))
 {
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
 TEST_SUITE_END() // BoundedReLu
 TEST_SUITE_END() // QuantizeDownInt32ToInt16ScaleByFixedPoint
 TEST_SUITE_END() // OutputStage
 TEST_SUITE_END() // GEMMLowp
 TEST_SUITE_END() // CL
 } // namespace validation
 } // namespace test
 } // namespace arm_compute
	/*
	* Copyright (c) 2017-2019 ARM Limited.
	*
	* SPDX-License-Identifier: MIT
	*
	* Permission is hereby granted, free of charge, to any person obtaining a copy
	* of this software and associated documentation files (the "Software"), to
	* deal in the Software without restriction, including without limitation the
	* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
	* sell copies of the Software, and to permit persons to whom the Software is
	* furnished to do so, subject to the following conditions:
	*
	* The above copyright notice and this permission notice shall be included in all
	* copies or substantial portions of the Software.
	*
	* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
	* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
	* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
	* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
	* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
	* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
	* SOFTWARE.
	*/
	#include "arm_compute/core/Types.h"
	#include "arm_compute/runtime/CL/CLTensor.h"
	#include "arm_compute/runtime/CL/CLTensorAllocator.h"
	#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
	#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
	#include "tests/CL/CLAccessor.h"
	#include "tests/PaddingCalculator.h"
	#include "tests/datasets/GEMMLowpFusedOffsetOutputDataset.h"
	#include "tests/datasets/LargeGEMMLowpDataset.h"
	#include "tests/datasets/ShapeDatasets.h"
	#include "tests/datasets/SmallGEMMLowpDataset.h"
	#include "tests/framework/Asserts.h"
	#include "tests/framework/Macros.h"
	#include "tests/framework/datasets/Datasets.h"
	#include "tests/validation/Validation.h"
	#include "tests/validation/fixtures/GEMMLowpFixture.h"

	namespace arm_compute
	{
	namespace test
	{
	namespace validation
	{
	TEST_SUITE(CL)
	TEST_SUITE(GEMMLowp)

	TEST_SUITE(MatrixMultiplyCore)

	using CLGEMMLowpMatrixMultiplyCoreFixture = GEMMLowpMatrixMultiplyCoreValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;

	DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, datasets::SmallGEMMLowpDataset(),
	shape_a, shape_b, shape_c, a_offset, b_offset)
	{
	// Create tensors
	CLTensor a = create_tensor<CLTensor>(shape_a, DataType::QASYMM8);
	CLTensor b = create_tensor<CLTensor>(shape_b, DataType::QASYMM8);
	CLTensor c = create_tensor<CLTensor>(shape_c, DataType::S32);

	a.info()->set_quantization_info(QuantizationInfo(1.0f / 255, a_offset));
	b.info()->set_quantization_info(QuantizationInfo(1.0f / 255, b_offset));

	ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS);

	// Create and configure function
	CLGEMMLowpMatrixMultiplyCore gemmlowp_mm;
	// TODO (giaiod01) COMPMID-1672 - Extending the test to validate add bias in offset contribution
	gemmlowp_mm.configure(&a, &b, nullptr, &c);
	}

	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFixture, framework::DatasetMode::ALL, datasets::SmallGEMMLowpDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;
	TEST_SUITE(FusedOffsetOutput)
	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::ALL, datasets::SmallGEMMLowpFusedOffsetOutputDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpFusedOffsetOutputDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	TEST_SUITE_END() // FusedOffsetOutput

	TEST_SUITE(Output3D)
	using CLGEMMLowpMatrixMultiplyCoreOutput3DFixture = GEMMLowpMatrixMultiplyCoreValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore, false, true>;
	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreOutput3DFixture, framework::DatasetMode::PRECOMMIT, datasets::SmallGEMMLowpOutput3DDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreOutput3DFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpOutput3DDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	TEST_SUITE_END() // Output3D

	TEST_SUITE(InputOutput3D)
	using CLGEMMLowpMatrixMultiplyCoreInputOutput3DFixture = GEMMLowpMatrixMultiplyCoreValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore, true, true>;
	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreInputOutput3DFixture, framework::DatasetMode::PRECOMMIT, datasets::SmallGEMMLowpInputOutput3DDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreInputOutput3DFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpInputOutput3DDataset())
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	TEST_SUITE_END() // InputOutput3D
	TEST_SUITE_END() // MatrixMultiplyCore

	TEST_SUITE(OutputStage)
	TEST_SUITE(QuantizeDownInt32ToUint8Scale)

	const auto quantize_down_int32_to_uint8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_shift", 2,
	3)
	* framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });

	const auto quantize_down_int32_to_uint8_scale_relu_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1,
	2)
	* framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 173) * framework::dataset::make("addBias", { false, true });

	using CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToUint8Scale>;

	DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases),
	shape, result_offset, result_mult_int, result_shift, min, max, add_bias)
	{
	TensorShape shape_bias(shape[0]);

	// Create tensors
	CLTensor in = create_tensor<CLTensor>(shape, DataType::S32);
	CLTensor bias = create_tensor<CLTensor>(shape_bias, DataType::S32);
	CLTensor out = create_tensor<CLTensor>(shape, DataType::QASYMM8);

	ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS);

	// Create and configure function
	CLGEMMLowpQuantizeDownInt32ToUint8Scale output_stage;
	output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_offset, result_mult_int, result_shift, min, max);

	// Validate valid region input and output
	const ValidRegion valid_region = shape_to_valid_region(shape);
	validate(in.info()->valid_region(), valid_region);
	validate(out.info()->valid_region(), valid_region);

	// Validate valid region bias
	if(add_bias)
	{
	const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias);
	validate(bias.info()->valid_region(), valid_region_bias);
	}

	// Validate padding
	const PaddingSize padding = PaddingCalculator(shape.x(), 4).required_padding();
	validate(in.info()->padding(), padding);
	validate(out.info()->padding(), padding);

	if(add_bias)
	{
	validate(bias.info()->padding(), padding);
	}
	}

	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	TEST_SUITE(BoundedReLu)
	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
	quantize_down_int32_to_uint8_scale_relu_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	TEST_SUITE_END() // BoundedReLu
	TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale

	TEST_SUITE(QuantizeDownInt32ToUint8ScaleByFixedPoint)

	const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
	2)
	* framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });

	const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
	2)
	* framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 174) * framework::dataset::make("addBias", { false, true });

	using CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture =
	GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint>;

	DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
	quantize_down_int32_to_uint8_scale_by_fixedpoint_cases),
	shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias)
	{
	TensorShape shape_bias(shape[0]);

	// Create tensors
	CLTensor in = create_tensor<CLTensor>(shape, DataType::S32);
	CLTensor bias = create_tensor<CLTensor>(shape_bias, DataType::S32);
	CLTensor out = create_tensor<CLTensor>(shape, DataType::QASYMM8);

	ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS);

	// Create and configure function
	CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint output_stage;
	output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);

	// Validate valid region input and output
	const ValidRegion valid_region = shape_to_valid_region(shape);
	validate(in.info()->valid_region(), valid_region);
	validate(out.info()->valid_region(), valid_region);

	// Validate valid region bias
	if(add_bias)
	{
	const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias);
	validate(bias.info()->valid_region(), valid_region_bias);
	}

	// Validate padding
	const PaddingSize padding = PaddingCalculator(shape.x(), 4).required_padding();
	validate(in.info()->padding(), padding);
	validate(out.info()->padding(), padding);

	if(add_bias)
	{
	validate(bias.info()->padding(), padding);
	}
	}

	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
	quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
	quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	TEST_SUITE(BoundedReLu)
	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
	quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}

	FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
	quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	TEST_SUITE_END() // BoundedReLu
	TEST_SUITE_END() // QuantizeDownInt32ToUint8ScaleByFixedPoint
	TEST_SUITE(QuantizeDownInt32ToInt16ScaleByFixedPoint)

	const auto quantize_down_int32_to_int16_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
	2)
	* framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });

	const auto quantize_down_int32_to_int16_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
	2)
	* framework::dataset::make("min", -2, 0) * framework::dataset::make("max", 1, 3) * framework::dataset::make("addBias", { false, true });

	using CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture =
	GEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint>;

	// INDENT-OFF
	// clang-format off
	DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
	framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::S32),
	TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max
	TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Wrong output data type
	}),
	framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32),
	TensorInfo(TensorShape(21U), 1, DataType::S32),
	TensorInfo(TensorShape(21U), 1, DataType::S32),
	})),
	framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16),
	TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16),
	TensorInfo(TensorShape(20U, 13U), 1, DataType::S32),
	})),
	framework::dataset::make("Min",{ -205,
	-60000,
	-180,
	})),
	framework::dataset::make("Max",{ 205,
	60000,
	180,
	})),
	framework::dataset::make("Expected", { true, false, false })),
	a_info, b_info, output_info, min, max, expected)
	{
	// Lock tensors
	Status status = CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(&a_info.clone()->set_is_resizable(true),
	&b_info.clone()->set_is_resizable(true),
	&output_info.clone()->set_is_resizable(true),
	min,
	max);
	ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
	}
	// clang-format on
	// INDENT-ON
	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
	quantize_down_int32_to_int16_scale_by_fixedpoint_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	TEST_SUITE(BoundedReLu)
	FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
	quantize_down_int32_to_int16_scale_by_fixedpoint_relu_cases))
	{
	// Validate output
	validate(CLAccessor(_target), _reference);
	}
	TEST_SUITE_END() // BoundedReLu
	TEST_SUITE_END() // QuantizeDownInt32ToInt16ScaleByFixedPoint
	TEST_SUITE_END() // OutputStage
	TEST_SUITE_END() // GEMMLowp
	TEST_SUITE_END() // CL
	} // namespace validation
	} // namespace test
	} // namespace arm_compute