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

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# Copyright 2019-2022 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 pytest
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import mindspore.dataset as ds
import mindspore.dataset.vision as vision
from mindspore import log as logger
DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
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SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
def test_exception_01():
"""
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Feature: Exception
Description: Test single Exception with invalid input
Expectation: Correct error and message are thrown as expected (here TypeError)
"""
logger.info("test_exception_01")
data = ds.TFRecordDataset(DATA_DIR, columns_list=["image"])
with pytest.raises(TypeError) as info:
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data.map(operations=vision.Resize(100, 100), input_columns=["image"])
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assert "Argument interpolation with value 100 is not of type [<enum 'Inter'>]" in str(
info.value)
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def test_exception_02():
"""
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Feature: Exception
Description: Test Exception with invalid input and test valid input
Expectation: Correct error and message are thrown for invalid input and runs successfully for valid input
"""
logger.info("test_exception_02")
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num_samples = -1
with pytest.raises(ValueError) as info:
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ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=[
"image"], num_samples=num_samples)
assert 'num_samples exceeds the boundary between 0 and 9223372036854775807(INT64_MAX)' in str(
info.value)
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num_samples = 1
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data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=[
"image"], num_samples=num_samples)
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data = data.map(operations=vision.Decode(), input_columns=["image"])
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data = data.map(operations=vision.Resize(
(100, 100)), input_columns=["image"])
# Confirm 1 sample in dataset
assert sum([1 for _ in data]) == 1
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num_iters = 0
for _ in data.create_dict_iterator(num_epochs=1):
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num_iters += 1
assert num_iters == 1
if __name__ == '__main__':
test_exception_01()
test_exception_02()