|
- # Copyright 2019 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.
-
- from akg.utils import kernel_exec as utils
- from tests.common.tensorio import compare_tensor
- import numpy as np
- from tests.common.test_op.assign_sub import assign_sub
- from tests.common.gen_random import random_gaussian
-
- def assign_sub_run(shape, dtype, attrs):
- if 'tuning' in attrs.keys():
- t = attrs.get("tuning", False)
- kernel_name = attrs.get("kernel_name", False)
- mod = utils.op_build_test(assign_sub, [shape, shape], [dtype, dtype], kernel_name=kernel_name, attrs=attrs,
- tuning=t)
- if t:
- expect, input1, input2, output = gen_data(dtype, shape)
- return mod, expect, (input1, input2, output)
- else:
- return mod
- else:
- mod = utils.op_build_test(assign_sub, [shape, shape], [dtype, dtype], kernel_name='assign_sub', attrs=attrs)
- expect, input1, input2, output = gen_data(dtype, shape)
- output = utils.mod_launch(mod, (input1, input2, output), expect=expect)
-
- return input1, output, expect, compare_tensor(output, expect, rtol=5e-03, equal_nan=True)
-
-
- def gen_data(dtype, shape):
- """ Generate data for testing the op """
- input1 = random_gaussian(shape, miu=1, sigma=0.1).astype(dtype)
- input2 = random_gaussian(shape, miu=1, sigma=0.1).astype(dtype)
- expect = np.subtract(input1, input2)
- output = np.full(shape, np.nan, dtype)
- return expect, input1, input2, output
|
