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input_pipeline_test.py
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input_pipeline_test.py
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# Copyright 2020 The Flax Authors.
#
# 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.
"""Tests for flax.examples.nlp.input_pipeline."""
import os
from absl.testing import absltest
import input_pipeline
import jax
import tensorflow.compat.v2 as tf
# Enable direct iteration over a tf-datasets.
tf.enable_v2_behavior()
# Parse absl flags test_srcdir and test_tmpdir.
jax.config.parse_flags_with_absl()
CONLL_DATA = u"""1\tThey\tthey\tPRON\tPRP\tCase=Nom|Number=Plur\t2\tnsubj
2\tbuy\tbuy\t VERB\tVBP\tNumber=Plur|PTense=Pres\t0\troot
3\tbooks\tbook\tNOUN\tNNS\tNumber=Plur\t2\tobj
4\t.\t.\tPUNCT\t.\t_\t2\tpunct
1\tThey\tthey\tPRON\tPRP\tCase=Nom|Number=Plur\t2\tnsubj
2\tbuy\tbuy\t VERB\tVBP\tNumber=Plur|PTense=Pres\t0\troot
3\tbooks\tbook\tNOUN\tNNS\tNumber=Plur\t2\tobj
4\t.\t.\tPUNCT\t.\t_\t2\tpunct
1\tNY\tNY\tNOUN\tNNS\tNumber=Singular\t0\troot
"""
class InputPipelineTest(absltest.TestCase):
def setUp(self):
super(InputPipelineTest, self).setUp()
self.test_tmpdir = self.create_tempdir()
# Write a sample corpus.
self._filename = os.path.join(self.test_tmpdir.full_path, 'data.conll')
with tf.io.gfile.GFile(self._filename, 'w') as f:
# The CoNLL data has to end with an empty line.
f.write(CONLL_DATA)
f.write('\n')
def test_vocab_creation(self):
"""Tests the creation of the vocab."""
vocabs = input_pipeline.create_vocabs(self._filename)
self.assertEqual(
vocabs['forms'], {
'<p>': 0,
'<u>': 1,
'<r>': 2,
'They': 3,
'buy': 4,
'books': 5,
'.': 6,
'NY': 7,
})
def testInputBatch(self):
"""Test the batching of the dataset."""
vocabs = input_pipeline.create_vocabs(self._filename)
attributes_input = [input_pipeline.CoNLLAttributes.FORM]
attributes_target = [] # empty target for tagging of unlabeled data.
sentence_dataset = input_pipeline.sentence_dataset_dict(
self._filename, vocabs, attributes_input, attributes_target,
batch_size=2, bucket_size=10, repeat=1)
sentence_dataset_iter = iter(sentence_dataset)
batch = next(sentence_dataset_iter)
inputs = batch['inputs'].numpy().tolist()
self.assertSameStructure(inputs, [[2., 3., 4., 5., 6., 0., 0., 0., 0., 0.],
[2., 3., 4., 5., 6., 0., 0., 0., 0., 0.]])
self.assertLen(batch, 1) # make sure target is not included.
def testInputTargetBatch(self):
"""Test the batching of the dataset."""
vocabs = input_pipeline.create_vocabs(self._filename)
attributes_input = [input_pipeline.CoNLLAttributes.FORM]
attributes_target = [input_pipeline.CoNLLAttributes.XPOS]
sentence_dataset = input_pipeline.sentence_dataset_dict(
self._filename, vocabs, attributes_input, attributes_target,
batch_size=2, bucket_size=10, repeat=1)
sentence_dataset_iter = iter(sentence_dataset)
batch = next(sentence_dataset_iter)
inputs = batch['inputs'].numpy().tolist()
self.assertSameStructure(inputs, [[2., 3., 4., 5., 6., 0., 0., 0., 0., 0.],
[2., 3., 4., 5., 6., 0., 0., 0., 0., 0.]])
targets = batch['targets'].numpy().tolist()
self.assertSameStructure(targets,
[[2., 4., 5., 3., 6., 0., 0., 0., 0., 0.],
[2., 4., 5., 3., 6., 0., 0., 0., 0., 0.]])
if __name__ == '__main__':
absltest.main()