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mindspore/tests/ut/python/dataset_deprecated/test_map.py

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# Copyright 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.
# ==============================================================================
"""
Test Map op in Dataset
"""
import pytest
import mindspore.dataset as ds
import mindspore.dataset.text as text
from mindspore.dataset.transforms import c_transforms
from mindspore.dataset.transforms import py_transforms
import mindspore.dataset.transforms.transforms as data_trans
import mindspore.dataset.vision.c_transforms as c_vision
import mindspore.dataset.vision.py_transforms as py_vision
import mindspore.dataset.vision.transforms as vision
DATA_DIR_PK = "../data/dataset/testPK/data"
DATA_DIR_VOCAB = "../data/dataset/testVocab/words.txt"
def test_map_c_transform_exception():
"""
Feature: test c error op def
Description: op defined like c_vision.HWC2CHW
Expectation: success
"""
data_set = ds.ImageFolderDataset(DATA_DIR_PK, num_parallel_workers=1, shuffle=True)
train_image_size = 224
mean = [0.485 * 255, 0.456 * 255, 0.406 * 255]
std = [0.229 * 255, 0.224 * 255, 0.225 * 255]
# define map operations
random_crop_decode_resize_op = c_vision.RandomCropDecodeResize(train_image_size,
scale=(0.08, 1.0),
ratio=(0.75, 1.333))
random_horizontal_flip_op = c_vision.RandomHorizontalFlip(prob=0.5)
normalize_op = c_vision.Normalize(mean=mean, std=std)
hwc2chw_op = c_vision.HWC2CHW # exception
data_set = data_set.map(operations=random_crop_decode_resize_op, input_columns="image", num_parallel_workers=1)
data_set = data_set.map(operations=random_horizontal_flip_op, input_columns="image", num_parallel_workers=1)
data_set = data_set.map(operations=normalize_op, input_columns="image", num_parallel_workers=1)
with pytest.raises(ValueError) as info:
data_set = data_set.map(operations=hwc2chw_op, input_columns="image", num_parallel_workers=1)
assert "Parameter operations's element of method map should be a " in str(info.value)
# compose exception
with pytest.raises(ValueError) as info:
c_transforms.Compose([
c_vision.RandomCropDecodeResize(train_image_size, scale=(0.08, 1.0), ratio=(0.75, 1.333)),
c_vision.RandomHorizontalFlip,
c_vision.Normalize(mean=mean, std=std),
c_vision.HWC2CHW()])
assert " should be a " in str(info.value)
# randomapply exception
with pytest.raises(ValueError) as info:
c_transforms.RandomApply([
c_vision.RandomCropDecodeResize,
c_vision.RandomHorizontalFlip(prob=0.5),
c_vision.Normalize(mean=mean, std=std),
c_vision.HWC2CHW()])
assert " should be a " in str(info.value)
# randomchoice exception
with pytest.raises(ValueError) as info:
c_transforms.RandomChoice([
c_vision.RandomCropDecodeResize(train_image_size, scale=(0.08, 1.0), ratio=(0.75, 1.333)),
c_vision.RandomHorizontalFlip(prob=0.5),
c_vision.Normalize,
c_vision.HWC2CHW()])
assert " should be a " in str(info.value)
def test_map_py_transform_exception():
"""
Feature: test python error op def
Description: op defined like py_vision.RandomHorizontalFlip
Expectation: success
"""
data_set = ds.ImageFolderDataset(DATA_DIR_PK, num_parallel_workers=1, shuffle=True)
# define map operations
decode_op = py_vision.Decode()
random_horizontal_flip_op = py_vision.RandomHorizontalFlip # exception
to_tensor_op = py_vision.ToTensor()
trans = [decode_op, random_horizontal_flip_op, to_tensor_op]
with pytest.raises(ValueError) as info:
data_set = data_set.map(operations=trans, input_columns="image", num_parallel_workers=1)
assert "Parameter operations's element of method map should be a " in str(info.value)
# compose exception
with pytest.raises(ValueError) as info:
py_transforms.Compose([
py_vision.Decode,
py_vision.RandomHorizontalFlip(),
py_vision.ToTensor()])
assert " should be a " in str(info.value)
# randomapply exception
with pytest.raises(ValueError) as info:
py_transforms.RandomApply([
py_vision.Decode(),
py_vision.RandomHorizontalFlip,
py_vision.ToTensor()])
assert " should be a " in str(info.value)
# randomchoice exception
with pytest.raises(ValueError) as info:
py_transforms.RandomChoice([
py_vision.Decode(),
py_vision.RandomHorizontalFlip(),
py_vision.ToTensor])
assert " should be a " in str(info.value)
def test_map_text_and_data_transforms():
"""
Feature: Map op
Description: Test Map op with both Text Transforms and Data Transforms
Expectation: Dataset pipeline runs successfully and results are verified
"""
data = ds.TextFileDataset(DATA_DIR_VOCAB, shuffle=False)
vocab = text.Vocab.from_dataset(data, "text", freq_range=None, top_k=None,
special_tokens=["<pad>", "<unk>"],
special_first=True)
padend_op = c_transforms.PadEnd([100], pad_value=vocab.tokens_to_ids('<pad>'))
lookup_op = text.Lookup(vocab, "<unk>")
# Use both Text Lookup op and Data Transforms PadEnd op in operations list for Map
data = data.map(operations=[lookup_op, padend_op], input_columns=["text"])
res = []
for d in data.create_dict_iterator(num_epochs=1, output_numpy=True):
res.append(d["text"].item())
assert res == [4, 5, 3, 6, 7, 2]
def test_map_mix_vision_tranforms():
"""
Feature: Map op
Description: Test Map op with mixing of old legacy vision c/py_transforms and new unified vision transforms
Expectation: RuntimeError is detected
"""
def test_config(my_operations):
# Not valid to mix legacy c/py_transforms with new unified transforms
data_set = ds.ImageFolderDataset(DATA_DIR_PK, num_parallel_workers=1)
data_set = data_set.map(operations=my_operations, input_columns="image")
with pytest.raises(RuntimeError) as error_info:
for _ in enumerate(data_set):
pass
assert "Mixing old legacy c/py_transforms and new unified transforms is not allowed" in str(error_info.value)
# Test old legacy transform before new unified transform
test_config([c_vision.Decode(), vision.RandomHorizontalFlip()])
test_config([py_vision.Decode(), lambda x: x, vision.RandomHorizontalFlip()])
# Test old legacy transform after new unified transform
test_config([lambda x: x, vision.Decode(), c_vision.RandomHorizontalFlip(), c_vision.RandomVerticalFlip()])
test_config([vision.Decode(True), py_vision.RandomHorizontalFlip(), py_vision.ToTensor()])
def test_map_mix_data_transforms():
"""
Feature: Map op
Description: Test Map op with mixing of old legacy data c/py_transforms and new unified data transforms
Expectation: RuntimeError is detected
"""
def test_config(my_operations):
# Not valid to mix legacy c/py_transforms with new unified transforms
data_set = ds.NumpySlicesDataset([1, 2, 3], column_names="x")
data_set = data_set.map(operations=my_operations, input_columns="x")
with pytest.raises(RuntimeError) as error_info:
for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
pass
assert "Mixing old legacy c/py_transforms and new unified transforms is not allowed" in str(error_info.value)
# Test old legacy transform before new unified transform
test_config([c_transforms.Duplicate(), data_trans.Concatenate(), lambda x: x])
# Test old legacy transform after new unified transform
test_config([data_trans.Duplicate(), c_transforms.Concatenate()])
if __name__ == '__main__':
test_map_c_transform_exception()
test_map_py_transform_exception()
test_map_text_and_data_transforms()
test_map_mix_vision_transforms()
test_map_mix_data_transforms()
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