forked from mindspore-Ecosystem/mindspore
309 lines
12 KiB
Python
309 lines
12 KiB
Python
# Copyright 2021-2022 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""
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Test USPS dataset operators
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"""
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import os
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from typing import cast
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import matplotlib.pyplot as plt
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import numpy as np
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import pytest
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import mindspore.dataset as ds
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import mindspore.dataset.vision.transforms as vision
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from mindspore import log as logger
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DATA_DIR = "../data/dataset/testUSPSDataset"
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WRONG_DIR = "../data/dataset/testMnistData"
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def load_usps(path, usage):
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"""
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load USPS data
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"""
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assert usage in ["train", "test"]
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if usage == "train":
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data_path = os.path.realpath(os.path.join(path, "usps"))
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elif usage == "test":
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data_path = os.path.realpath(os.path.join(path, "usps.t"))
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with open(data_path, 'r') as f:
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raw_data = [line.split() for line in f.readlines()]
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tmp_list = [[x.split(':')[-1] for x in data[1:]] for data in raw_data]
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images = np.asarray(tmp_list, dtype=np.float32).reshape((-1, 16, 16, 1))
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images = ((cast(np.ndarray, images) + 1) / 2 * 255).astype(dtype=np.uint8)
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labels = [int(d[0]) - 1 for d in raw_data]
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return images, labels
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def visualize_dataset(images, labels):
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"""
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Helper function to visualize the dataset samples
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"""
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num_samples = len(images)
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for i in range(num_samples):
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plt.subplot(1, num_samples, i + 1)
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plt.imshow(images[i].squeeze(), cmap=plt.cm.gray)
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plt.title(labels[i])
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plt.show()
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def test_usps_content_check():
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"""
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Validate USPSDataset image readings
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"""
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logger.info("Test USPSDataset Op with content check")
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train_data = ds.USPSDataset(DATA_DIR, "train", num_samples=10, shuffle=False)
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images, labels = load_usps(DATA_DIR, "train")
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num_iter = 0
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# in this example, each dictionary has keys "image" and "label"
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for i, data in enumerate(train_data.create_dict_iterator(num_epochs=1, output_numpy=True)):
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for m in range(16):
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for n in range(16):
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assert (data["image"][m, n, 0] != 0 or images[i][m, n, 0] != 255) and \
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(data["image"][m, n, 0] != 255 or images[i][m, n, 0] != 0)
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assert (data["image"][m, n, 0] == images[i][m, n, 0]) or\
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(data["image"][m, n, 0] == images[i][m, n, 0] + 1) or\
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(data["image"][m, n, 0] + 1 == images[i][m, n, 0])
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np.testing.assert_array_equal(data["label"], labels[i])
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num_iter += 1
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assert num_iter == 3
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test_data = ds.USPSDataset(DATA_DIR, "test", num_samples=3, shuffle=False)
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images, labels = load_usps(DATA_DIR, "test")
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num_iter = 0
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# in this example, each dictionary has keys "image" and "label"
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for i, data in enumerate(test_data.create_dict_iterator(num_epochs=1, output_numpy=True)):
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for m in range(16):
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for n in range(16):
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if (data["image"][m, n, 0] == 0 and images[i][m, n, 0] == 255) or\
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(data["image"][m, n, 0] == 255 and images[i][m, n, 0] == 0):
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assert False
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if (data["image"][m, n, 0] != images[i][m, n, 0]) and\
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(data["image"][m, n, 0] != images[i][m, n, 0] + 1) and\
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(data["image"][m, n, 0] + 1 != images[i][m, n, 0]):
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assert False
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np.testing.assert_array_equal(data["label"], labels[i])
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num_iter += 1
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assert num_iter == 3
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def test_usps_basic():
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"""
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Validate USPSDataset
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"""
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logger.info("Test USPSDataset Op")
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# case 1: test loading whole dataset
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train_data = ds.USPSDataset(DATA_DIR, "train")
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num_iter = 0
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for _ in train_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 3
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test_data = ds.USPSDataset(DATA_DIR, "test")
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num_iter = 0
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for _ in test_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 3
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# case 2: test num_samples
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train_data = ds.USPSDataset(DATA_DIR, "train", num_samples=2)
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num_iter = 0
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for _ in train_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 2
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# case 3: test repeat
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train_data = ds.USPSDataset(DATA_DIR, "train", num_samples=2)
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train_data = train_data.repeat(5)
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num_iter = 0
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for _ in train_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 10
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# case 4: test batch with drop_remainder=False
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train_data = ds.USPSDataset(DATA_DIR, "train", num_samples=3)
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assert train_data.get_dataset_size() == 3
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assert train_data.get_batch_size() == 1
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train_data = train_data.batch(batch_size=2) # drop_remainder is default to be False
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assert train_data.get_batch_size() == 2
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assert train_data.get_dataset_size() == 2
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num_iter = 0
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for _ in train_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 2
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# case 5: test batch with drop_remainder=True
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train_data = ds.USPSDataset(DATA_DIR, "train", num_samples=3)
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assert train_data.get_dataset_size() == 3
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assert train_data.get_batch_size() == 1
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train_data = train_data.batch(batch_size=2, drop_remainder=True) # the rest of incomplete batch will be dropped
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assert train_data.get_dataset_size() == 1
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assert train_data.get_batch_size() == 2
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num_iter = 0
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for _ in train_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 1
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def test_usps_exception():
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"""
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Test error cases for USPSDataset
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"""
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error_msg_3 = "num_shards is specified and currently requires shard_id as well"
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with pytest.raises(RuntimeError, match=error_msg_3):
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ds.USPSDataset(DATA_DIR, "train", num_shards=10)
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ds.USPSDataset(DATA_DIR, "test", num_shards=10)
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error_msg_4 = "shard_id is specified but num_shards is not"
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with pytest.raises(RuntimeError, match=error_msg_4):
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ds.USPSDataset(DATA_DIR, "train", shard_id=0)
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ds.USPSDataset(DATA_DIR, "test", shard_id=0)
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error_msg_5 = "Input shard_id is not within the required interval"
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with pytest.raises(ValueError, match=error_msg_5):
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ds.USPSDataset(DATA_DIR, "train", num_shards=5, shard_id=-1)
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ds.USPSDataset(DATA_DIR, "test", num_shards=5, shard_id=-1)
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with pytest.raises(ValueError, match=error_msg_5):
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ds.USPSDataset(DATA_DIR, "train", num_shards=5, shard_id=5)
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ds.USPSDataset(DATA_DIR, "test", num_shards=5, shard_id=5)
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with pytest.raises(ValueError, match=error_msg_5):
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ds.USPSDataset(DATA_DIR, "train", num_shards=2, shard_id=5)
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ds.USPSDataset(DATA_DIR, "test", num_shards=2, shard_id=5)
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error_msg_6 = "num_parallel_workers exceeds"
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with pytest.raises(ValueError, match=error_msg_6):
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ds.USPSDataset(DATA_DIR, "train", shuffle=False, num_parallel_workers=0)
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ds.USPSDataset(DATA_DIR, "test", shuffle=False, num_parallel_workers=0)
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with pytest.raises(ValueError, match=error_msg_6):
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ds.USPSDataset(DATA_DIR, "train", shuffle=False, num_parallel_workers=256)
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ds.USPSDataset(DATA_DIR, "test", shuffle=False, num_parallel_workers=256)
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with pytest.raises(ValueError, match=error_msg_6):
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ds.USPSDataset(DATA_DIR, "train", shuffle=False, num_parallel_workers=-2)
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ds.USPSDataset(DATA_DIR, "test", shuffle=False, num_parallel_workers=-2)
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error_msg_7 = "Argument shard_id"
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with pytest.raises(TypeError, match=error_msg_7):
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ds.USPSDataset(DATA_DIR, "train", num_shards=2, shard_id="0")
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ds.USPSDataset(DATA_DIR, "test", num_shards=2, shard_id="0")
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error_msg_8 = "invalid input shape"
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with pytest.raises(RuntimeError, match=error_msg_8):
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train_data = ds.USPSDataset(DATA_DIR, "train")
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train_data = train_data.map(operations=vision.Decode(), input_columns=["image"], num_parallel_workers=1)
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for _ in train_data.__iter__():
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pass
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test_data = ds.USPSDataset(DATA_DIR, "test")
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test_data = test_data.map(operations=vision.Decode(), input_columns=["image"], num_parallel_workers=1)
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for _ in test_data.__iter__():
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pass
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error_msg_9 = "usps does not exist or is a directory"
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with pytest.raises(RuntimeError, match=error_msg_9):
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train_data = ds.USPSDataset(WRONG_DIR, "train")
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for _ in train_data.__iter__():
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pass
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error_msg_10 = "usps.t does not exist or is a directory"
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with pytest.raises(RuntimeError, match=error_msg_10):
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test_data = ds.USPSDataset(WRONG_DIR, "test")
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for _ in test_data.__iter__():
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pass
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def test_usps_visualize(plot=False):
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"""
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Visualize USPSDataset results
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"""
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logger.info("Test USPSDataset visualization")
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train_data = ds.USPSDataset(DATA_DIR, "train", num_samples=3, shuffle=False)
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num_iter = 0
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image_list, label_list = [], []
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for item in train_data.create_dict_iterator(num_epochs=1, output_numpy=True):
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image = item["image"]
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label = item["label"]
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image_list.append(image)
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label_list.append("label {}".format(label))
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assert isinstance(image, np.ndarray)
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assert image.shape == (16, 16, 1)
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assert image.dtype == np.uint8
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assert label.dtype == np.uint32
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num_iter += 1
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assert num_iter == 3
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if plot:
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visualize_dataset(image_list, label_list)
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test_data = ds.USPSDataset(DATA_DIR, "test", num_samples=3, shuffle=False)
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num_iter = 0
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image_list, label_list = [], []
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for item in test_data.create_dict_iterator(num_epochs=1, output_numpy=True):
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image = item["image"]
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label = item["label"]
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image_list.append(image)
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label_list.append("label {}".format(label))
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assert isinstance(image, np.ndarray)
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assert image.shape == (16, 16, 1)
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assert image.dtype == np.uint8
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assert label.dtype == np.uint32
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num_iter += 1
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assert num_iter == 3
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if plot:
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visualize_dataset(image_list, label_list)
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def test_usps_usage():
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"""
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Validate USPSDataset image readings
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"""
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logger.info("Test USPSDataset usage flag")
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def test_config(usage, path=None):
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path = DATA_DIR if path is None else path
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try:
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data = ds.USPSDataset(path, usage=usage, shuffle=False)
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num_rows = 0
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for _ in data.create_dict_iterator(num_epochs=1, output_numpy=True):
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num_rows += 1
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except (ValueError, TypeError, RuntimeError) as e:
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return str(e)
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return num_rows
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assert test_config("train") == 3
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assert test_config("test") == 3
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assert "usage is not within the valid set of ['train', 'test', 'all']" in test_config("invalid")
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assert "Argument usage with value ['list'] is not of type [<class 'str'>]" in test_config(["list"])
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# change this directory to the folder that contains all USPS files
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all_files_path = None
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# the following tests on the entire datasets
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if all_files_path is not None:
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assert test_config("train", all_files_path) == 3
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assert test_config("test", all_files_path) == 3
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assert ds.USPSDataset(all_files_path, usage="train").get_dataset_size() == 3
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assert ds.USPSDataset(all_files_path, usage="test").get_dataset_size() == 3
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if __name__ == '__main__':
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test_usps_content_check()
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test_usps_basic()
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test_usps_exception()
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test_usps_visualize(plot=True)
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test_usps_usage()
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