forked from huawei/mindspore2022
248 lines
8.3 KiB
Python
248 lines
8.3 KiB
Python
# Copyright 2021 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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import os
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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.c_transforms as c_vision
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DATA_DIR_SEMEION = "../data/dataset/testSemeionData"
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def load_semeion(path):
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"""
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load Semeion data
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"""
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fp = os.path.realpath(os.path.join(path, "semeion.data"))
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data = np.loadtxt(fp)
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images = (data[:, :256]).astype('uint8')
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images = images.reshape(-1, 16, 16)
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labels = np.nonzero(data[:, 256:])[1]
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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])
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plt.title(labels[i])
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plt.show()
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def test_semeion_content_check():
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"""
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Feature: SemeionDataset
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Description: Check content of each sample
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Expectation: correct content
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"""
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data1 = ds.SemeionDataset(DATA_DIR_SEMEION, num_samples=10, shuffle=False)
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images, labels = load_semeion(DATA_DIR_SEMEION)
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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, d in enumerate(data1.create_dict_iterator(num_epochs=1, output_numpy=True)):
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np.testing.assert_array_equal(d["image"], images[i])
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np.testing.assert_array_equal(d["label"], labels[i])
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num_iter += 1
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assert num_iter == 10
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def test_semeion_basic():
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"""
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Feature: SemeionDataset
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Description: use different data to test the functions of different versions
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Expectation: all samples(10)
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num_samples
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set 5
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get 5
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num_parallel_workers
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set 1(num_samples=6)
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get 6
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num repeat
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set 3(num_samples=3)
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get 9
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"""
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# case 0: test loading all samples
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data0 = ds.SemeionDataset(DATA_DIR_SEMEION)
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num_iter0 = 0
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for _ in data0.create_dict_iterator(num_epochs=1):
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num_iter0 += 1
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assert num_iter0 == 10
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# case 1: test num_samples
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data1 = ds.SemeionDataset(DATA_DIR_SEMEION, num_samples=5)
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num_iter1 = 0
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for _ in data1.create_dict_iterator(num_epochs=1):
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num_iter1 += 1
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assert num_iter1 == 5
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# case 2: test num_parallel_workers
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data2 = ds.SemeionDataset(DATA_DIR_SEMEION, num_samples=6, num_parallel_workers=1)
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num_iter2 = 0
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for _ in data2.create_dict_iterator(num_epochs=1):
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num_iter2 += 1
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assert num_iter2 == 6
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# case 3: test repeat
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data3 = ds.SemeionDataset(DATA_DIR_SEMEION, num_samples=3)
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data3 = data3.repeat(3)
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num_iter3 = 0
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for _ in data3.create_dict_iterator(num_epochs=1):
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num_iter3 += 1
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assert num_iter3 == 9
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def test_semeion_sequential_sampler():
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"""
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Feature: SemeionDataset
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Description: test semeion sequential sampler
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Expectation: correct data
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"""
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num_samples = 4
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sampler = ds.SequentialSampler(num_samples=num_samples)
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data1 = ds.SemeionDataset(DATA_DIR_SEMEION, sampler=sampler)
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data2 = ds.SemeionDataset(DATA_DIR_SEMEION, shuffle=False, num_samples=num_samples)
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num_iter = 0
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for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True),
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data2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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np.testing.assert_equal(item1["label"], item2["label"])
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np.testing.assert_equal(item1["image"], item2["image"])
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num_iter += 1
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assert num_iter == num_samples
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def test_semeion_exceptions():
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"""
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Feature: SemeionDataset
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Description: error test
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Expectation: throw error
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"""
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error_msg_1 = "sampler and shuffle cannot be specified at the same time"
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with pytest.raises(RuntimeError, match=error_msg_1):
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ds.SemeionDataset(DATA_DIR_SEMEION, shuffle=False, sampler=ds.PKSampler(3))
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error_msg_2 = "sampler and sharding cannot be specified at the same time"
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with pytest.raises(RuntimeError, match=error_msg_2):
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ds.SemeionDataset(DATA_DIR_SEMEION, sampler=ds.PKSampler(3), num_shards=2, shard_id=0)
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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.SemeionDataset(DATA_DIR_SEMEION, 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.SemeionDataset(DATA_DIR_SEMEION, 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.SemeionDataset(DATA_DIR_SEMEION, num_shards=2, shard_id=-1)
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with pytest.raises(ValueError, match=error_msg_5):
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ds.SemeionDataset(DATA_DIR_SEMEION, 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.SemeionDataset(DATA_DIR_SEMEION, shuffle=False, num_parallel_workers=0)
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with pytest.raises(ValueError, match=error_msg_6):
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ds.SemeionDataset(DATA_DIR_SEMEION, shuffle=False, num_parallel_workers=256)
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def test_semeion_visualize(plot=False):
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"""
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Feature: SemeionDataset
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Description: visualize SemeionDataset results
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Expectation: visualization
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"""
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data1 = ds.SemeionDataset(DATA_DIR_SEMEION, num_samples=10, shuffle=False)
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num_iter = 0
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image_list, label_list = [], []
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for item in data1.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)
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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 == 10
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if plot:
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visualize_dataset(image_list, label_list)
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def test_semeion_exception_file_path():
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"""
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Feature: SemeionDataset
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Description: error test
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Expectation: throw error
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"""
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def exception_func(item):
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raise Exception("Error occur!")
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try:
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data = ds.SemeionDataset(DATA_DIR_SEMEION)
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data = data.map(operations=exception_func, input_columns=["image"], num_parallel_workers=1)
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num_rows = 0
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for _ in data.create_dict_iterator():
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num_rows += 1
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assert False
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except RuntimeError as e:
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assert "map operation: [PyFunc] failed. The corresponding data files" in str(e)
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try:
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data = ds.SemeionDataset(DATA_DIR_SEMEION)
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data = data.map(operations=exception_func, input_columns=["label"], num_parallel_workers=1)
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num_rows = 0
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for _ in data.create_dict_iterator():
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num_rows += 1
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assert False
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except RuntimeError as e:
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assert "map operation: [PyFunc] failed. The corresponding data files" in str(e)
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def test_semeion_pipeline():
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"""
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Feature: SemeionDataset
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Description: Read a sample
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Expectation: The amount of each function are equal
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"""
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# Original image
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dataset = ds.SemeionDataset(DATA_DIR_SEMEION, num_samples=1)
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resize_op = c_vision.Resize((100, 100))
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# Filtered image by Resize
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dataset = dataset.map(operations=resize_op, input_columns=["image"], num_parallel_workers=1)
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i = 0
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for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
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i += 1
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assert i == 1
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if __name__ == '__main__':
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test_semeion_content_check()
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test_semeion_basic()
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test_semeion_sequential_sampler()
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test_semeion_exceptions()
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test_semeion_visualize(plot=False)
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test_semeion_exception_file_path()
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test_semeion_pipeline()
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