188 lines
14 KiB
C++
188 lines
14 KiB
C++
/*
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* Copyright (c) 2018-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "arm_compute/runtime/NEON/functions/NELSTMLayer.h"
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#include "tests/NEON/Accessor.h"
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#include "tests/PaddingCalculator.h"
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#include "tests/datasets/LSTMLayerDataset.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Macros.h"
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#include "tests/framework/datasets/Datasets.h"
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#include "tests/validation/Validation.h"
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#include "tests/validation/fixtures/LSTMLayerFixture.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace
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{
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RelativeTolerance<float> tolerance_f32(0.00001f);
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RelativeTolerance<half> tolerance_f16(half(0.1));
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} // namespace
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TEST_SUITE(NEON)
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TEST_SUITE(LSTMLayer)
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// *INDENT-OFF*
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// clang-format off
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DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(zip(zip(
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framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 2U), 1, DataType::U8), // Wrong data type
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TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Wrong input size
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TensorInfo(TensorShape(8U, 2U), 1, DataType::F32), // Wrong input weights size
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TensorInfo(TensorShape(8U, 2U), 1, DataType::F32), // Wrong recurrent weights size
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TensorInfo(TensorShape(8U, 2U), 1, DataType::F32), // Wrong cell bias size
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TensorInfo(TensorShape(8U, 2U), 1, DataType::F32), // Wrong cell state size
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TensorInfo(TensorShape(8U, 2U), 1, DataType::F32), // Wrong output size
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TensorInfo(TensorShape(8U, 2U), 1, DataType::F32), // Wrong scratch size
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}),
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framework::dataset::make("InputWeightsInfo", { TensorInfo(TensorShape(8U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(8U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(27U, 11U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(8U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(8U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(8U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(8U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(8U, 16U), 1, DataType::F32),
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})),
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framework::dataset::make("RecurrentWeightsInfo", { TensorInfo(TensorShape(16U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U), 1, DataType::F32),
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})),
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framework::dataset::make("CellBiasInfo", { TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(30U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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})),
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framework::dataset::make("ProjectionBiasInfo", { TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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TensorInfo(TensorShape(16U), 1, DataType::F32),
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})),
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framework::dataset::make("CellStateInfo", { TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(11U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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})),
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framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(11U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
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})),
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framework::dataset::make("ScratchInfo", { TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(12U, 2U), 1, DataType::F32),
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})),
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framework::dataset::make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
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})),
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framework::dataset::make("Expected", { false, false, false, false, false, false, false, false })),
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input_info, input_weights_info, recurrent_weights_info, cell_bias_info, projection_bias_info, cell_state_info, output_info, scratch_info, info, expected)
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{
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LSTMParams<ITensorInfo> lstm_params_info;
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auto cell_bias_clone = cell_bias_info.clone();
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lstm_params_info.set_peephole_params(cell_bias_clone.get(), cell_bias_clone.get())
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.set_projection_params(&recurrent_weights_info, &projection_bias_info)
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.set_cifg_params(&input_weights_info, &recurrent_weights_info, cell_bias_clone.get(), cell_bias_clone.get());
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ARM_COMPUTE_EXPECT(bool(NELSTMLayer::validate(&input_info.clone()->set_is_resizable(false), &input_weights_info.clone()->set_is_resizable(false), &input_weights_info.clone()->set_is_resizable(false),
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&input_weights_info.clone()->set_is_resizable(false), &recurrent_weights_info.clone()->set_is_resizable(false), &recurrent_weights_info.clone()->set_is_resizable(false),
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&recurrent_weights_info.clone()->set_is_resizable(false), &cell_bias_info.clone()->set_is_resizable(false), &cell_bias_info.clone()->set_is_resizable(false),
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&cell_bias_info.clone()->set_is_resizable(false),
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&output_info.clone()->set_is_resizable(false), &cell_state_info.clone()->set_is_resizable(false),
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&scratch_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), &cell_state_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false),
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lstm_params_info, info, 0.05, 0.9)) == expected, framework::LogLevel::ERRORS);
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}
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// clang-format on
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// *INDENT-ON*
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template <typename T>
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using NELSTMLayerFixture = LSTMLayerValidationFixture<Tensor, Accessor, NELSTMLayer, LSTMParams<ITensor>, T>;
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSmall, NELSTMLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallLSTMLayerDataset(), framework::dataset::make("DataType",
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DataType::F32)),
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framework::dataset::make("ProjectionOpt", { true, false })),
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framework::dataset::make("PeepholeOpt", { true, false })),
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framework::dataset::make("UseLayerNorm", { true, false })))
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{
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// Validate output
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validate(Accessor(_target), _reference, tolerance_f32);
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validate(Accessor(_target_scratch), _reference_scratch, tolerance_f32);
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}
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TEST_SUITE_END() // FP32
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#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
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TEST_SUITE(FP16)
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FIXTURE_DATA_TEST_CASE(RunSmall, NELSTMLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallLSTMLayerDataset(), framework::dataset::make("DataType",
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DataType::F16)),
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framework::dataset::make("ProjectionOpt", { true, false })),
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framework::dataset::make("PeepholeOpt", { true, false })),
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framework::dataset::make("UseLayerNorm", { true, false })))
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{
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// Validate output
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validate(Accessor(_target), _reference, tolerance_f16);
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validate(Accessor(_target_scratch), _reference_scratch, tolerance_f16);
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}
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TEST_SUITE_END() // FP16
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#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
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TEST_SUITE_END() // LSTMLayer
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TEST_SUITE_END() // NEON
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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