mindspore/tests/ut/python/dataset/test_c_random_apply.py

49 lines
2.0 KiB
Python

# 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(input_columns=["col"], operations=ops.RandomApply(op_list, prob))
res = []
for i in data.create_dict_iterator(num_epochs=1):
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'>" 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()