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/*
* Copyright (c) 2018-2020 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/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h"
#include "arm_compute/core/KernelDescriptors.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
#include "tests/CL/CLAccessor.h"
#include "tests/CL/Helper.h"
#include "tests/PaddingCalculator.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/GEMMFixture.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
using namespace arm_compute::misc::shape_calculator;
// Create function for CLGEMMReshapeLHSMatrixKernel
using CLGEMMReshapeLHSMatrix = CLSynthetizeFunction<CLGEMMReshapeLHSMatrixKernel>;
// Create function for CLGEMMReshapeRHSMatrixKernel
using CLGEMMReshapeRHSMatrix = CLSynthetizeFunction<CLGEMMReshapeRHSMatrixKernel>;
// Create function for CLGEMMMatrixMultiplyReshapedKernel
using CLGEMMMatrixMultiplyReshaped = CLSynthetizeFunction<CLGEMMMatrixMultiplyReshapedKernel>;
// Fixture for CLGEMMMatrixMultiplyReshaped
template <typename T>
using CLGEMMMatrixMultiplyReshapedFixture = GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
// Fixture for CLGEMMMatrixMultiplyReshaped mixed precision
template <typename T>
using CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture =
GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;
// Fixture for CLGEMMMatrixMultiplyReshaped3D
template <typename T>
using CLGEMMMatrixMultiplyReshaped3DFixture = GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
// Fixture for CLGEMMMatrixMultiplyReshaped3D mixed precision
template <typename T>
using CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture =
GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;
namespace
{
// *INDENT-OFF*
// clang-format off
RelativeTolerance<float> rel_tolerance_f32(0.001f);
constexpr float abs_tolerance_f32(0.0001f);
RelativeTolerance<float> rel_tolerance_f16_mixed_precision(0.001f);
constexpr float abs_tolerance_f16_mixed_precision(0.01f);
RelativeTolerance<float> rel_tolerance_f16(0.001f);
constexpr float abs_tolerance_f16(0.01f);
/** M values to test */
const auto m_values = framework::dataset::make("M", 17);
/** M_W values to test */
const auto m_w_values = framework::dataset::make("M_W", 5);
/** M_H values to test */
const auto m_h_values = framework::dataset::make("M_H", 7);
/** N values to test */
const auto n_values = framework::dataset::make("N", 21);
/** K values to test */
const auto k_values = framework::dataset::make("K", 13);
/** Batch size values to test */
const auto b_values = framework::dataset::make("batch_size", 2, 3);
/** Activation values to test */
const auto act_values = framework::dataset::make("Activation",
{
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
});
/** Alpha values to test - Precommit */
const auto a_values_precommit = framework::dataset::make("alpha", {-0.75f} );
/** Beta values to test - Precommit */
const auto beta_values_precommit = framework::dataset::make("beta", {-0.35f} );
/** M0 values to test - Precommit */
const auto m0_values_precommit = framework::dataset::make("M0", { 4 });
/** N0 values to test - Precommit */
const auto n0_values_precommit = framework::dataset::make("N0", { 4 });
/** K0 values to test - Precommit */
const auto k0_values_precommit = framework::dataset::make("K0", { 4 });
/** V0 values to test - Precommit */
const auto v0_values_precommit = framework::dataset::make("V0", 1, 3);
/** H0 values to test - Precommit */
const auto h0_values_precommit = framework::dataset::make("H0", 1, 3);
/** Alpha values to test - Nightly */
const auto a_values_nightly = framework::dataset::make("alpha", {1.0f} );
/** Beta values to test - Nightly */
const auto beta_values_nightly = framework::dataset::make("beta", {1.0f} );
/** M0 values to test - Nightly */
const auto m0_values_nightly = framework::dataset::make("M0", { 2, 3, 4, 8 });
/** N0 values to test - Nightly */
const auto n0_values_nightly = framework::dataset::make("N0", { 2, 3, 4, 8 });
/** K0 values to test - Nightly */
const auto k0_values_nightly = framework::dataset::make("K0", { 2, 3, 4, 8 });
/** V0 values to test - Nightly */
const auto v0_values_nightly = framework::dataset::make("V0", 1, 4);
/** H0 values to test - Nightly */
const auto h0_values_nightly = framework::dataset::make("H0", 1, 4);
/** Interleave values to test with LHS matrix */
const auto i_values_lhs = framework::dataset::make("interleave_lhs", { true, false });
/** Interleave values to test with RHS matrix */
const auto i_values_rhs = framework::dataset::make("interleave_rhs", { true, false });
/** Broadcast bias from vector to matrix */
const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", { false, true } );
/** LHS transposed values */
const auto lhs_transpose_values = framework::dataset::make("lhs_transpose", { false, true } );
} // namespace
TEST_SUITE(CL)
TEST_SUITE(GEMMMatrixMultiplyReshaped)
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
framework::dataset::make("Input0Info", { TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32), // OK
TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK
TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8), // Data type not supported
TensorInfo(TensorShape(10U, 5U, 2U), 1, DataType::F32), // Incorrect dimension bias
TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32), // Mismatching shapes
TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, do not broadcast bias
TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, wider accummulation
TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, RHS 4,4,2
}),
framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(128U, 3U, 2U), 1, DataType::F16),
})),
framework::dataset::make("Input2Info", { TensorInfo(TensorShape(21U), 1, DataType::F32),
TensorInfo(TensorShape(21U), 1, DataType::F16),
TensorInfo(TensorShape(21U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(21U), 1, DataType::F32),
TensorInfo(TensorShape(21U), 1, DataType::F32),
TensorInfo(TensorShape(21U,17U), 1, DataType::F16),
TensorInfo(TensorShape(21U,17U), 1, DataType::F16),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
})),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
})),
framework::dataset::make("LHSMInfo",{
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMLHSMatrixInfo(4,2,4,false,false),
GEMMLHSMatrixInfo(4,2,4,false,false),
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMLHSMatrixInfo(4,4,1,false,true),
})),
framework::dataset::make("RHSMInfo",{
GEMMRHSMatrixInfo(4,4,1,true,true),
GEMMRHSMatrixInfo(4,4,1, true,true),
GEMMRHSMatrixInfo(4,4,1,true,true),
GEMMRHSMatrixInfo(2,2,1,true,false),
GEMMRHSMatrixInfo(2,2,1,true,false),
GEMMRHSMatrixInfo(4,4,1,true,true),
GEMMRHSMatrixInfo(4,4,1,true,true),
GEMMRHSMatrixInfo(4,4,2,true,false),
})),
framework::dataset::make("GEMMInfo",{
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
21 /**<N Number of RHS columns*/,
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
false /**< reinterpret the input as 3D */,
true /**< Flag used to broadcast the bias addition */,
false /**< wider accumm */,
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
1 /**< Multiplication factor for the width of the 1xW transposed block */,
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMRHSMatrixInfo(4,4,1,true,true),
0 /**< Offset to be added to each element of the matrix A */,
0 /**< Offset to be added to each element of the matrix B */),
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
21 /**<N Number of RHS columns*/,
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
false /**< reinterpret the input as 3D */,
true /**< Flag used to broadcast the bias addition */,
false /**< wider accumm */,
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
1 /**< Multiplication factor for the width of the 1xW transposed block */,
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMRHSMatrixInfo(4,4,1,true,true),
0 /**< Offset to be added to each element of the matrix A */,
0 /**< Offset to be added to each element of the matrix B */),
GEMMKernelInfo(),
GEMMKernelInfo(),
GEMMKernelInfo(),
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
21 /**<N Number of RHS columns*/,
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
false /**< reinterpret the input as 3D */,
false /**< Flag used to broadcast the bias addition */,
false /**< wider accumm */,
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
1 /**< Multiplication factor for the width of the 1xW transposed block */,
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMRHSMatrixInfo(4,4,1,true,true),
0 /**< Offset to be added to each element of the matrix A */,
0 /**< Offset to be added to each element of the matrix B */),
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
21 /**<N Number of RHS columns*/,
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
false /**< reinterpret the input as 3D */,
false /**< Flag used to broadcast the bias addition */,
true /**< wider accumm */,
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
1 /**< Multiplication factor for the width of the 1xW transposed block */,
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMRHSMatrixInfo(4,4,1,true,true),
0 /**< Offset to be added to each element of the matrix A */,
0 /**< Offset to be added to each element of the matrix B */),
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
21 /**<N Number of RHS columns*/,
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
false /**< reinterpret the input as 3D */,
false /**< Flag used to broadcast the bias addition */,
false /**< wider accumm */,
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
1 /**< Multiplication factor for the width of the 1xW transposed block */,
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
GEMMLHSMatrixInfo(4,4,1,false,true),
GEMMRHSMatrixInfo(4,4,2,true,false),
0 /**< Offset to be added to each element of the matrix A */,
0 /**< Offset to be added to each element of the matrix B */),
})),
framework::dataset::make("Expected", { true, true, false, false, false, true, true,true})),
input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
{
ARM_COMPUTE_EXPECT(bool(CLGEMMMatrixMultiplyReshapedKernel::validate(&input0_info.clone()->set_is_resizable(true),
&input1_info.clone()->set_is_resizable(true),
&input2_info.clone()->set_is_resizable(true),
&output_info.clone()->set_is_resizable(true),1.f,1.f,
lhs_info,
rhs_info,
gemm_info)) == expected, framework::LogLevel::ERRORS);
}
TEST_SUITE(Float)
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_values,
n_values),
k_values),
b_values),
m0_values_precommit),
n0_values_precommit),
k0_values_precommit),
v0_values_precommit),
h0_values_precommit),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F32)),
a_values_precommit),
beta_values_precommit),
broadcast_bias_values),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::DISABLED,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_values,
n_values),
k_values),
b_values),
m0_values_nightly),
n0_values_nightly),
k0_values_nightly),
v0_values_nightly),
h0_values_nightly),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F32)),
a_values_nightly),
beta_values_nightly),
broadcast_bias_values),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_w_values,
m_h_values),
n_values),
k_values),
b_values),
m0_values_precommit),
n0_values_precommit),
k0_values_precommit),
v0_values_precommit),
h0_values_precommit),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F32)),
a_values_precommit),
beta_values_precommit),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::DISABLED,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_w_values,
m_h_values),
n_values),
k_values),
b_values),
m0_values_nightly),
n0_values_nightly),
k0_values_nightly),
v0_values_nightly),
h0_values_nightly),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F32)),
a_values_nightly),
beta_values_nightly),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}
TEST_SUITE_END() // FP32
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_values,
n_values),
k_values),
b_values),
m0_values_precommit),
n0_values_precommit),
k0_values_precommit),
v0_values_precommit),
h0_values_precommit),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_precommit),
beta_values_precommit),
broadcast_bias_values),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::DISABLED,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_values,
n_values),
k_values),
b_values),
m0_values_nightly),
n0_values_nightly),
k0_values_nightly),
v0_values_nightly),
h0_values_nightly),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_nightly),
beta_values_nightly),
broadcast_bias_values),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_w_values,
m_h_values),
n_values),
k_values),
b_values),
m0_values_precommit),
n0_values_precommit),
k0_values_precommit),
v0_values_precommit),
h0_values_precommit),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_precommit),
beta_values_precommit),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::DISABLED,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_w_values,
m_h_values),
n_values),
k_values),
b_values),
m0_values_nightly),
n0_values_nightly),
k0_values_nightly),
v0_values_nightly),
h0_values_nightly),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_nightly),
beta_values_nightly),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}
TEST_SUITE_END() // FP16
TEST_SUITE(MixedPrecision)
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_values,
n_values),
k_values),
b_values),
m0_values_precommit),
n0_values_precommit),
k0_values_precommit),
v0_values_precommit),
h0_values_precommit),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_precommit),
beta_values_precommit),
broadcast_bias_values),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_values,
n_values),
k_values),
b_values),
m0_values_nightly),
n0_values_nightly),
k0_values_nightly),
v0_values_nightly),
h0_values_nightly),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_nightly),
beta_values_nightly),
broadcast_bias_values),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_w_values,
m_h_values),
n_values),
k_values),
b_values),
m0_values_precommit),
n0_values_precommit),
k0_values_precommit),
v0_values_precommit),
h0_values_precommit),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_precommit),
beta_values_precommit),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED,
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
m_w_values,
m_h_values),
n_values),
k_values),
b_values),
m0_values_nightly),
n0_values_nightly),
k0_values_nightly),
v0_values_nightly),
h0_values_nightly),
i_values_lhs),
i_values_rhs),
framework::dataset::make("DataType", DataType::F16)),
a_values_nightly),
beta_values_nightly),
lhs_transpose_values),
act_values))
{
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}
TEST_SUITE_END() // MixedPrecision
TEST_SUITE_END() // Float
TEST_SUITE_END() // GEMMMatrixMultiplyReshaped
TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute