forked from huawei/mindspore2022
133 lines
5.4 KiB
Python
133 lines
5.4 KiB
Python
# Copyright 2021 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 numpy as np
|
|
import pytest
|
|
|
|
import mindspore.dataset as ds
|
|
import mindspore.dataset.vision.c_transforms as C
|
|
|
|
|
|
DATA_DIR = "../data/dataset/testPK/data"
|
|
|
|
|
|
def test_offload():
|
|
"""
|
|
Feature: test map offload flag.
|
|
Description: Input is image dataset.
|
|
Expectation: Output should be same with activated or deactivated offload.
|
|
"""
|
|
# Dataset with offload activated.
|
|
dataset_0 = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_0 = dataset_0.map(operations=[C.Decode()], input_columns="image")
|
|
dataset_0 = dataset_0.map(operations=[C.HWC2CHW()], input_columns="image", offload=True)
|
|
dataset_0 = dataset_0.batch(8, drop_remainder=True)
|
|
|
|
# Dataset with offload not activated.
|
|
dataset_1 = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_1 = dataset_1.map(operations=[C.Decode()], input_columns="image")
|
|
dataset_1 = dataset_1.map(operations=[C.HWC2CHW()], input_columns="image")
|
|
dataset_1 = dataset_1.batch(8, drop_remainder=True)
|
|
|
|
for (img_0, _), (img_1, _) in zip(dataset_0.create_tuple_iterator(num_epochs=1, output_numpy=True),
|
|
dataset_1.create_tuple_iterator(num_epochs=1, output_numpy=True)):
|
|
np.testing.assert_array_equal(img_0, img_1)
|
|
|
|
|
|
def test_auto_offload():
|
|
"""
|
|
Feature: Test auto_offload config option.
|
|
Description: Input is image dataset.
|
|
Expectation: Output should same with auto_offload activated and deactivated.
|
|
"""
|
|
trans = [C.Decode(), C.HWC2CHW()]
|
|
|
|
# Enable automatic offload
|
|
ds.config.set_auto_offload(True)
|
|
|
|
# Dataset with offload deactivated
|
|
dataset_auto_disabled = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_auto_disabled = dataset_auto_disabled.map(operations=trans, input_columns="image", offload=False)
|
|
dataset_auto_disabled = dataset_auto_disabled.batch(8, drop_remainder=True)
|
|
|
|
# Dataset with config.auto_offload activated
|
|
dataset_auto_enabled = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_auto_enabled = dataset_auto_enabled.map(operations=trans, input_columns="image")
|
|
dataset_auto_enabled = dataset_auto_enabled.batch(8, drop_remainder=True)
|
|
|
|
for (img_0, _), (img_1, _) in zip(dataset_auto_disabled.create_tuple_iterator(num_epochs=1, output_numpy=True),
|
|
dataset_auto_enabled.create_tuple_iterator(num_epochs=1, output_numpy=True)):
|
|
np.testing.assert_array_equal(img_0, img_1)
|
|
|
|
# Need to turn off here or subsequent test cases will fail.
|
|
ds.config.set_auto_offload(False)
|
|
|
|
|
|
def test_offload_concat_dataset_1():
|
|
"""
|
|
Feature: test map offload flag for concatenated dataset.
|
|
Description: Input is image dataset.
|
|
Expectation: Should raise RuntimeError.
|
|
"""
|
|
# Dataset with offload activated.
|
|
dataset_0 = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_0 = dataset_0.map(operations=[C.Decode()], input_columns="image")
|
|
dataset_0 = dataset_0.map(operations=[C.HWC2CHW()], input_columns="image", offload=True)
|
|
dataset_0 = dataset_0.batch(8, drop_remainder=True)
|
|
|
|
# Dataset with offload not activated.
|
|
dataset_1 = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_1 = dataset_1.map(operations=[C.Decode()], input_columns="image")
|
|
dataset_1 = dataset_1.map(operations=[C.HWC2CHW()], input_columns="image")
|
|
dataset_1 = dataset_1.batch(8, drop_remainder=True)
|
|
|
|
dataset_concat = dataset_0 + dataset_1
|
|
|
|
error_msg = "Offload module currently does not support concatenated or zipped datasets."
|
|
with pytest.raises(RuntimeError, match=error_msg):
|
|
for (_, _) in dataset_concat.create_tuple_iterator(num_epochs=1, output_numpy=True):
|
|
continue
|
|
|
|
|
|
def test_offload_concat_dataset_2():
|
|
"""
|
|
Feature: test map offload flag for concatenated dataset.
|
|
Description: Input is image dataset.
|
|
Expectation: Should raise RuntimeError.
|
|
"""
|
|
# Dataset with offload activated.
|
|
dataset_0 = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_0 = dataset_0.map(operations=[C.Decode()], input_columns="image")
|
|
dataset_0 = dataset_0.map(operations=[C.HWC2CHW()], input_columns="image", offload=True)
|
|
|
|
# Dataset with offload not activated.
|
|
dataset_1 = ds.ImageFolderDataset(DATA_DIR)
|
|
dataset_1 = dataset_1.map(operations=[C.Decode()], input_columns="image")
|
|
dataset_1 = dataset_1.map(operations=[C.HWC2CHW()], input_columns="image")
|
|
|
|
dataset_concat = dataset_0 + dataset_1
|
|
dataset_concat = dataset_concat.batch(8, drop_remainder=True)
|
|
|
|
error_msg = "Offload module currently does not support concatenated or zipped datasets."
|
|
with pytest.raises(RuntimeError, match=error_msg):
|
|
for (_, _) in dataset_concat.create_tuple_iterator(num_epochs=1, output_numpy=True):
|
|
continue
|
|
|
|
|
|
if __name__ == "__main__":
|
|
test_offload()
|
|
test_auto_offload()
|
|
test_offload_concat_dataset_1()
|
|
test_offload_concat_dataset_2()
|