mindspore2022/tests/ut/python/dataset/test_map.py

# 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.
# ==============================================================================
import pytest
import mindspore.dataset as ds
from mindspore.dataset.transforms import c_transforms
from mindspore.dataset.transforms import py_transforms
import mindspore.dataset.vision.c_transforms as c_vision
import mindspore.dataset.vision.py_transforms as py_vision

DATA_DIR = "../data/dataset/testPK/data"


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, 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, 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)


if __name__ == '__main__':
    test_map_c_transform_exception()
    test_map_py_transform_exception()