You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
94 lines
4.3 KiB
94 lines
4.3 KiB
# 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.dataset as ds
|
|
from mindspore import log as logger
|
|
|
|
|
|
# test5trainimgs.json contains 5 images whose un-decoded shape is [83554, 54214, 65512, 54214, 64631]
|
|
# the label of each image is [0,0,0,1,1] each image can be uniquely identified
|
|
# via the following lookup table (dict){(83554, 0): 0, (54214, 0): 1, (54214, 1): 2, (65512, 0): 3, (64631, 1): 4}
|
|
|
|
def test_sequential_sampler(print_res=False):
|
|
manifest_file = "../data/dataset/testManifestData/test5trainimgs.json"
|
|
map = {(172876, 0): 0, (54214, 0): 1, (54214, 1): 2, (173673, 0): 3, (64631, 1): 4}
|
|
|
|
def test_config(num_samples, num_repeats=None):
|
|
sampler = ds.SequentialSampler()
|
|
data1 = ds.ManifestDataset(manifest_file, num_samples=num_samples, sampler=sampler)
|
|
if num_repeats is not None:
|
|
data1 = data1.repeat(num_repeats)
|
|
res = []
|
|
for item in data1.create_dict_iterator():
|
|
logger.info("item[image].shape[0]: {}, item[label].item(): {}"
|
|
.format(item["image"].shape[0], item["label"].item()))
|
|
res.append(map[(item["image"].shape[0], item["label"].item())])
|
|
if print_res:
|
|
logger.info("image.shapes and labels: {}".format(res))
|
|
return res
|
|
|
|
assert test_config(num_samples=3, num_repeats=None) == [0, 1, 2]
|
|
assert test_config(num_samples=None, num_repeats=2) == [0, 1, 2, 3, 4] * 2
|
|
assert test_config(num_samples=4, num_repeats=2) == [0, 1, 2, 3] * 2
|
|
|
|
|
|
def test_random_sampler(print_res=False):
|
|
manifest_file = "../data/dataset/testManifestData/test5trainimgs.json"
|
|
map = {(172876, 0): 0, (54214, 0): 1, (54214, 1): 2, (173673, 0): 3, (64631, 1): 4}
|
|
|
|
def test_config(replacement, num_samples, num_repeats):
|
|
sampler = ds.RandomSampler(replacement=replacement, num_samples=num_samples)
|
|
data1 = ds.ManifestDataset(manifest_file, sampler=sampler)
|
|
data1 = data1.repeat(num_repeats)
|
|
res = []
|
|
for item in data1.create_dict_iterator():
|
|
res.append(map[(item["image"].shape[0], item["label"].item())])
|
|
if print_res:
|
|
logger.info("image.shapes and labels: {}".format(res))
|
|
return res
|
|
|
|
# this tests that each epoch COULD return different samples than the previous epoch
|
|
assert len(set(test_config(replacement=False, num_samples=2, num_repeats=6))) > 2
|
|
# the following two tests test replacement works
|
|
ordered_res = [0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]
|
|
assert sorted(test_config(replacement=False, num_samples=None, num_repeats=4)) == ordered_res
|
|
assert sorted(test_config(replacement=True, num_samples=None, num_repeats=4)) != ordered_res
|
|
|
|
|
|
def test_random_sampler_multi_iter(print_res=False):
|
|
manifest_file = "../data/dataset/testManifestData/test5trainimgs.json"
|
|
map = {(172876, 0): 0, (54214, 0): 1, (54214, 1): 2, (173673, 0): 3, (64631, 1): 4}
|
|
|
|
def test_config(replacement, num_samples, num_repeats, validate):
|
|
sampler = ds.RandomSampler(replacement=replacement, num_samples=num_samples)
|
|
data1 = ds.ManifestDataset(manifest_file, sampler=sampler)
|
|
while num_repeats > 0:
|
|
res = []
|
|
for item in data1.create_dict_iterator():
|
|
res.append(map[(item["image"].shape[0], item["label"].item())])
|
|
if print_res:
|
|
logger.info("image.shapes and labels: {}".format(res))
|
|
if validate != sorted(res):
|
|
break
|
|
num_repeats -= 1
|
|
assert num_repeats > 0
|
|
|
|
test_config(replacement=True, num_samples=5, num_repeats=5, validate=[0, 1, 2, 3, 4, 5])
|
|
|
|
|
|
if __name__ == '__main__':
|
|
test_sequential_sampler(True)
|
|
test_random_sampler(True)
|
|
test_random_sampler_multi_iter(True)
|