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/*
* Copyright (c) 2017-2020, 2022-2024 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/NEON/functions/NESoftmaxLayer.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "src/common/cpuinfo/CpuIsaInfo.h"
#include "src/cpu/kernels/CpuSoftmaxKernel.h"
#include "tests/NEON/Accessor.h"
#include "tests/datasets/ShapeDatasets.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/SoftmaxLayerFixture.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
using framework::dataset::make;
namespace
{
/** Tolerance for float operations */
constexpr AbsoluteTolerance<float> tolerance_f32(0.000001f);
RelativeTolerance<half> tolerance_f16(half(0.2));
/** Tolerance for quantized operations */
constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1);
constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_signed(1);
/** CNN data types */
const auto CNNDataTypes = make("DataType",
{
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
DataType::F16,
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
DataType::F32,
});
} // namespace
TEST_SUITE(NEON)
TEST_SUITE(SoftmaxLayer)
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(
make("InputInfo", { TensorInfo(TensorShape(27U, 13U), 1, DataType::F32), // Mismatching data types
TensorInfo(TensorShape(27U, 13U), 1, DataType::F32), // Mismatching shapes
TensorInfo(TensorShape(27U, 13U), 1, DataType::QASYMM8, // Invalid output quantization info
QuantizationInfo(1.f/256, 12)),
TensorInfo(TensorShape(32U, 13U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8,
QuantizationInfo(1.f/256, 12)),
TensorInfo(TensorShape(32U, 13U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, //Invalid axis high
QuantizationInfo(1.f/256, 12)),
TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, //Invalid axis low
QuantizationInfo(1.f/256, 12)),
}),
make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U), 1, DataType::F16),
TensorInfo(TensorShape(27U, 11U), 1, DataType::F32),
TensorInfo(TensorShape(27U, 13U), 1, DataType::QASYMM8,
QuantizationInfo(1.f/256, 12)),
TensorInfo(TensorShape(32U, 13U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8,
QuantizationInfo(1.f/256, 0)),
TensorInfo(TensorShape(32U, 13U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8,
QuantizationInfo(1.f/256, 0)),
TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8,
QuantizationInfo(1.f/256, 0)),
}),
make("beta", { 1.0,
2.0,
1.0,
2.0,
1.0,
1.0,
2.0,
1.0,
}),
make("axis", { 0,
0,
0,
1,
0,
-1,
2,
-3,
}),
make("Expected", { false, false, false, true, true, true, false, false })),
input_info, output_info, beta, axis, expected)
{
ARM_COMPUTE_EXPECT(bool(NESoftmaxLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), beta, axis)) == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
template <typename T>
using NESoftmaxLayerFixture = SoftmaxValidationFixture<Tensor, Accessor, NESoftmaxLayer, T>;
DATA_TEST_CASE(KernelSelection, framework::DatasetMode::ALL,
concat(
combine(
make("CpuExt", std::string("neon")),
make("DataType", { DataType::F32,
DataType::F16,
DataType::QASYMM8,
DataType::QASYMM8_SIGNED})
),
combine(
make("CpuExt", std::string("sme2")),
make("DataType", { DataType::F32,
DataType::F16}))
),
cpu_ext, data_type)
{
using namespace cpu::kernels;
cpuinfo::CpuIsaInfo cpu_isa{};
cpu_isa.neon = (cpu_ext == "neon");
cpu_isa.sme2 = (cpu_ext == "sme2");
cpu_isa.fp16 = (data_type == DataType::F16);
const auto *selected_impl = CpuSoftmaxKernel::get_implementation(
SoftmaxKernelDataTypeISASelectorData{ data_type, cpu_isa, false /* is_log */, 0 /* axis */},
cpu::KernelSelectionType::Preferred);
ARM_COMPUTE_ERROR_ON_NULLPTR(selected_impl);
std::string expected = cpu_ext + "_" + cpu_impl_dt(data_type) + "_softmax";
std::string actual = selected_impl->name;
ARM_COMPUTE_EXPECT_EQUAL(expected, actual, framework::LogLevel::ERRORS);
}
TEST_SUITE(Float)
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
combine(
datasets::SoftmaxLayerSmallShapes(),
make("DataType", DataType::F16),
make("Beta", { 1.0f, 2.0f }),
make("Axis", { 0, -1 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunSmall, NESoftmaxLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
combine(
datasets::SmallShapes(),
make("DataType", DataType::F16),
make("Beta", { 1.0f, 2.0f }),
make("Axis", { 0, 1 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
combine(
datasets::Small4DShapes(),
make("DataType", DataType::F16),
make("Beta", { 1.0f }),
make("Axis", { 0, 2, -1 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunLarge, NESoftmaxLayerFixture<half>, framework::DatasetMode::NIGHTLY,
combine(
datasets::SoftmaxLayerLargeShapes(),
make("DataType", DataType::F16),
make("Beta", { 1.0f, 2.0f }),
make("Axis", { 0 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f16);
}
TEST_SUITE_END() //FP16
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
combine(
datasets::SoftmaxLayerSmallShapes(),
make("DataType", DataType::F32),
make("Beta", { 1.0f, 2.0f }),
make("Axis", { 0, -1 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
combine(datasets::Small4DShapes(),
make("DataType", DataType::F32),
make("Beta", { 1.0f, 2.0f }),
make("Axis", { 0, -2, 3 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, NESoftmaxLayerFixture<float>, framework::DatasetMode::NIGHTLY,
combine(datasets::SoftmaxLayerLargeShapes(),
make("DataType", DataType::F32),
make("Beta", { 1.0f, 2.0f }),
make("Axis", { 0 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
TEST_SUITE_END() //FP32
TEST_SUITE_END() //Float
template <typename T>
using NESoftmaxLayerQuantizedFixture = SoftmaxValidationQuantizedFixture<Tensor, Accessor, NESoftmaxLayer, T>;
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL,
combine(
datasets::SoftmaxLayerSmallShapes(),
make("DataType", DataType::QASYMM8),
combine(
make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }),
make("Beta", { 1.0f, 2.f })
),
make("Axis", { 0, -1 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8);
}
FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL,
combine(
datasets::Small4DShapes(),
make("DataType", DataType::QASYMM8),
combine(
make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }),
make("Beta", { 1.0f, 2.f })),
make("Axis", { 0, 1, -2 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8);
}
FIXTURE_DATA_TEST_CASE(RunLarge, NESoftmaxLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY,
combine(
datasets::SoftmaxLayerLargeShapes(),
make("DataType", DataType::QASYMM8),
combine(
make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }),
make("Beta", { 1.0f, 2.0f })
),
make("Axis", { 0 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8);
}
TEST_SUITE_END() //QASYMM8
TEST_SUITE(QASYMM8_SIGNED)
FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL,
combine(
datasets::SoftmaxLayerSmallShapes(),
make("DataType", DataType::QASYMM8_SIGNED),
combine(
make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }),
make("Beta", { 1.0f, 2.f })
),
make("Axis", { 0, -1 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
}
FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL,
combine(
datasets::Small4DShapes(),
make("DataType", DataType::QASYMM8_SIGNED),
combine(
make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }),
make("Beta", { 1.0f, 2.f })
),
make("Axis", { 0, 1, -1 })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
}
TEST_SUITE_END() //QASYMM8_SIGNED
TEST_SUITE_END() //Quantized
TEST_SUITE_END() //SoftmaxLayer
TEST_SUITE_END() //NEON
} // namespace validation
} // namespace test
} // namespace arm_compute