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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # 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.
-
- import numpy as np
- from akg.utils import kernel_exec as utils
- from tests.common.test_op import cosh
- from tests.common.tensorio import compare_tensor
- from tests.common.base import get_rtol_atol
- from tests.common.gen_random import random_gaussian
-
- def cosh_execute(shape, dtype, attrs):
- exp_output, inputs, args = gen_data(dtype, shape)
- mod = cosh_compile(shape, dtype, attrs)
- # result_tvm
- acu_output = utils.mod_launch(mod, args, expect=exp_output)
-
- # compare result
- rtol, atol = get_rtol_atol("cosh", dtype)
- TestCase_Result = compare_tensor(acu_output, exp_output, rtol=rtol, atol=atol, equal_nan=True)
-
- return inputs, acu_output, exp_output, TestCase_Result
-
-
- def gen_data(dtype, shape):
- # Result_Numpy
- inputs = random_gaussian(shape, miu=0, sigma=0.3).astype(dtype)
- exp_output = np.cosh(inputs)
- # inputs and output to hold the data
- output = np.full(shape, np.nan, dtype)
- args = []
- args.append(inputs)
- args.append(output)
- return exp_output, inputs, args
-
-
- def cosh_compile(shape, dtype, attrs, kernel_name='cosh', runing=False):
- return utils.op_build_test(cosh.cosh, [shape], [dtype], kernel_name=kernel_name, attrs=attrs, tuning=runing)
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