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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 mindspore.common.dtype as mstype
- import mindspore.dataset as ds
- import mindspore.dataset.transforms.c_transforms as ops
-
-
- def test_random_apply():
- ds.config.set_seed(0)
-
- def test_config(arr, op_list, prob=0.5):
- try:
- data = ds.NumpySlicesDataset(arr, column_names="col", shuffle=False)
- data = data.map(operations=ops.RandomApply(op_list, prob), input_columns=["col"])
- res = []
- for i in data.create_dict_iterator(num_epochs=1, output_numpy=True):
- res.append(i["col"].tolist())
- return res
- except (TypeError, ValueError) as e:
- return str(e)
-
- res1 = test_config([[0, 1]], [ops.Duplicate(), ops.Concatenate()])
- assert res1 in [[[0, 1]], [[0, 1, 0, 1]]]
- # test single nested compose
- assert test_config([[0, 1, 2]], [ops.Compose([ops.Duplicate(), ops.Concatenate(), ops.Slice([0, 1, 2])])]) == [
- [0, 1, 2]]
- # test exception
- assert "is not of type [<class 'list'>]" in test_config([1, 0], ops.TypeCast(mstype.int32))
- assert "Input prob is not within the required interval" in test_config([0, 1], [ops.Slice([0, 1])], 1.1)
- assert "is not of type [<class 'float'>, <class 'int'>]" in test_config([1, 0], [ops.TypeCast(mstype.int32)], None)
- assert "op_list with value None is not of type [<class 'list'>]" in test_config([1, 0], None)
-
-
- if __name__ == "__main__":
- test_random_apply()
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