* Copyright (c) 2026 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
#include <array>
#include <vector>
#include "gtest/gtest.h"
#include "math/atan/op_api/aclnn_atan.h"
#include "op_api_ut_common/inner/types.h"
#include "op_api_ut_common/op_api_ut.h"
#include "op_api_ut_common/scalar_desc.h"
#include "op_api_ut_common/tensor_desc.h"
using namespace std;
class l2_atan_test : public testing::Test {
protected:
static void SetUpTestCase()
{
cout << "l2_atan_test SetUp" << endl;
}
static void TearDownTestCase()
{
cout << "l2_atan_test TearDown" << endl;
}
};
TEST_F(l2_atan_test, ascend910B2_atan_dtype_all)
{
vector<aclDataType> input_vaild_dtype_list{ACL_INT8, ACL_INT32, ACL_UINT8, ACL_INT16, ACL_INT64,
ACL_BOOL, ACL_FLOAT, ACL_FLOAT16, ACL_DOUBLE, ACL_BF16};
vector<aclDataType> output_vaild_dtype_list{ACL_FLOAT, ACL_FLOAT16, ACL_DOUBLE};
vector<aclDataType> invaild_dtype_list{ACL_COMPLEX64, ACL_COMPLEX128};
for (auto dtype1 : input_vaild_dtype_list) {
auto self_tensor_desc = TensorDesc({3, 5}, dtype1, ACL_FORMAT_ND).ValueRange(-20, 20);
for (auto dtype2 : output_vaild_dtype_list) {
auto out_tensor_desc = TensorDesc({3, 5}, dtype2, ACL_FORMAT_ND).Precision(0.001, 0.001);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACL_SUCCESS);
}
}
for (auto dtype : invaild_dtype_list) {
auto self_tensor_desc = TensorDesc({3, 5}, dtype, ACL_FORMAT_ND).ValueRange(-20, 20);
auto out_tensor_desc = TensorDesc({3, 5}, dtype, ACL_FORMAT_ND);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACLNN_ERR_PARAM_INVALID);
}
}
TEST_F(l2_atan_test, atan_nullptr)
{
auto ut = OP_API_UT(aclnnAtan, INPUT((aclTensor*)nullptr), OUTPUT((aclTensor*)nullptr));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACLNN_ERR_PARAM_NULLPTR);
}
TEST_F(l2_atan_test, atan_precision)
{
auto self_tensor_desc = TensorDesc({13, 16, 9}, ACL_FLOAT, ACL_FORMAT_ND).ValueRange(-20, 20);
auto out_tensor_desc = TensorDesc({13, 16, 9}, ACL_FLOAT, ACL_FORMAT_ND).Precision(0.001, 0.001);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACL_SUCCESS);
}
TEST_F(l2_atan_test, ascend910B2_atan_bf16_precision)
{
auto self_tensor_desc = TensorDesc({13, 16, 9}, ACL_BF16, ACL_FORMAT_ND).ValueRange(-20, 20);
auto out_tensor_desc = TensorDesc({13, 16, 9}, ACL_BF16, ACL_FORMAT_ND).Precision(0.001, 0.001);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACL_SUCCESS);
}
TEST_F(l2_atan_test, atan_empty_tensor)
{
auto self_tensor_desc = TensorDesc({13, 0, 9}, ACL_FLOAT, ACL_FORMAT_ND).ValueRange(-20, 20);
auto out_tensor_desc = TensorDesc({13, 0, 9}, ACL_FLOAT, ACL_FORMAT_ND).Precision(0.001, 0.001);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACL_SUCCESS);
}
TEST_F(l2_atan_test, atan_non_contiguous)
{
auto self_tensor_desc = TensorDesc({5, 3}, ACL_FLOAT, ACL_FORMAT_ND, {1, 5}, 0, {3, 5}).ValueRange(-20, 20);
auto out_tensor_desc = TensorDesc({5, 3}, ACL_FLOAT, ACL_FORMAT_ND, {1, 5}, 0, {3, 5}).Precision(0.001, 0.001);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACL_SUCCESS);
}
TEST_F(l2_atan_test, atan_bigDim)
{
auto self_tensor_desc = TensorDesc({2, 2, 2, 2, 2, 2, 2, 2, 2}, ACL_FLOAT, ACL_FORMAT_ND).ValueRange(-20, 20);
auto out_tensor_desc = TensorDesc({2, 2, 2, 2, 2, 2, 2, 2, 2}, ACL_FLOAT, ACL_FORMAT_ND).Precision(0.001, 0.001);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACLNN_ERR_PARAM_INVALID);
}
TEST_F(l2_atan_test, atan_bigDim_non_contiguous)
{
auto self_tensor_desc = TensorDesc(
{2, 2, 2, 2, 2, 2, 2, 2, 2}, ACL_FLOAT, ACL_FORMAT_ND, {128, 64, 32, 16, 8, 4, 2, 1, 0},
0, {2, 2, 2, 2, 2, 2, 2, 2, 1})
.ValueRange(-20, 20);
auto out_tensor_desc = TensorDesc(
{2, 2, 2, 2, 2, 2, 2, 2, 2}, ACL_FLOAT, ACL_FORMAT_ND, {128, 64, 32, 16, 8, 4, 2, 1, 0},
0, {2, 2, 2, 2, 2, 2, 2, 2, 1})
.Precision(0.001, 0.001);
auto ut = OP_API_UT(aclnnAtan, INPUT(self_tensor_desc), OUTPUT(out_tensor_desc));
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACLNN_ERR_PARAM_INVALID);
}
TEST_F(l2_atan_test, atan_inplace)
{
auto self_tensor_desc = TensorDesc({3, 5}, ACL_FLOAT, ACL_FORMAT_ND).ValueRange(-20, 20);
auto ut = OP_API_UT(aclnnInplaceAtan, INPUT(self_tensor_desc), OUTPUT());
uint64_t workspace_size = 0;
aclnnStatus aclRet = ut.TestGetWorkspaceSize(&workspace_size);
EXPECT_EQ(aclRet, ACL_SUCCESS);
}
