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/*
* Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <gtest/gtest.h>
#include <OperationsUtils.h>
#include <kernel/acl/nnfw_kernel_acl.h>
#include <arm_compute/core/Types.h>
#include <kernel/acl/Softmax.h>
#include "../util.h"
using namespace nnfw::kernel::acl;
TEST(KernelACL_TC, softmaxFloat32_1xn)
{
float inputData[4];
const nnfw::rt::Shape inputShape = { OperandType::FLOAT32, {1,4}, 1.0, 0 };
float outputData[4];
const nnfw::rt::Shape outputShape = { OperandType::FLOAT32, {1,4}, 1.0, 0 };
const float beta = 1.0f;
bool bret;
util::initData(inputData, sizeof(inputData) / sizeof(inputData[0]), 1.0);
util::initData(outputData, sizeof(outputData) / sizeof(outputData[0]), 0.0);
bret = softmaxFloat32(inputData, inputShape, beta, outputData, outputShape);
EXPECT_EQ(bret, true);
float expectData[] = { 0.25f, 0.25f, 0.25f, 0.25f };
bret = util::compareData(outputData, expectData, outputShape);
EXPECT_EQ(bret, true);
}
TEST(KernelACL_TC, softmaxFloat32_4d)
{
float inputData[4];
const nnfw::rt::Shape inputShape = { OperandType::FLOAT32, {1,1,4,1}, 1.0, 0 };
float outputData[4];
const nnfw::rt::Shape outputShape = { OperandType::FLOAT32, {1,1,4,1}, 1.0, 0 };
const float beta = 1.0f;
bool bret;
util::initData(inputData, sizeof(inputData) / sizeof(inputData[0]), 1.0);
util::initData(outputData, sizeof(outputData) / sizeof(outputData[0]), 0.0);
bret = softmaxFloat32(inputData, inputShape, beta, outputData, outputShape);
EXPECT_EQ(bret, true);
float expectData[] = { 0.25f, 0.25f, 0.25f, 0.25f };
bret = util::compareData(outputData, expectData, outputShape);
EXPECT_EQ(bret, true);
}
TEST(KernelACL_TC, softmaxFloat32_1xn_seq)
{
float inputData[4];
const nnfw::rt::Shape inputShape = { OperandType::FLOAT32, {1,4}, 1.0, 0 };
float outputData[4];
const nnfw::rt::Shape outputShape = { OperandType::FLOAT32, {1,4}, 1.0, 0 };
const float beta = 1.0f;
bool bret;
util::initData_Increasing(inputData, sizeof(inputData) / sizeof(inputData[0]), 1.0);
util::initData(outputData, sizeof(outputData) / sizeof(outputData[0]), 0.0);
bret = softmaxFloat32(inputData, inputShape, beta, outputData, outputShape);
EXPECT_EQ(bret, true);
float expectData[] = {0.032058603280085, 0.0871443187420326, 0.23688281808991, 0.643914259887972};
bret = util::compareData(outputData, expectData, outputShape);
EXPECT_EQ(bret, true);
}
TEST(KernelACL_TC, softmaxFloat32_4d_seq)
{
float inputData[4];
const nnfw::rt::Shape inputShape = { OperandType::FLOAT32, {1,1,4,1}, 1.0, 0 };
float outputData[4];
const nnfw::rt::Shape outputShape = { OperandType::FLOAT32, {1,1,4,1}, 1.0, 0 };
const float beta = 1.0f;
bool bret;
util::initData_Increasing(inputData, sizeof(inputData) / sizeof(inputData[0]), 1.0);
util::initData(outputData, sizeof(outputData) / sizeof(outputData[0]), 0.0);
bret = softmaxFloat32(inputData, inputShape, beta, outputData, outputShape);
EXPECT_EQ(bret, true);
float expectData[] = {0.032058603280085, 0.0871443187420326, 0.23688281808991, 0.643914259887972};
bret = util::compareData(outputData, expectData, outputShape);
EXPECT_EQ(bret, true);
}
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