def testCharConvEmbedder(self):
vocab_file = os.path.join(self.get_temp_dir(), "vocab.txt")
data_file = os.path.join(self.get_temp_dir(), "data.txt")
with io.open(vocab_file, encoding="utf-8", mode="w") as vocab:
vocab.write(u"h\n" u"e\n" u"l\n" u"w\n" u"o\n")
with io.open(data_file, encoding="utf-8", mode="w") as data:
data.write(u"hello world !\n")
embedder = text_inputter.CharConvEmbedder("vocabulary_file", 10, 5)
features, transformed = self._makeDataset(
embedder,
data_file,
metadata={"vocabulary_file": vocab_file},
shapes={
"char_ids": [None, None, None],
"length": [None]
})
with self.test_session() as sess:
sess.run(tf.tables_initializer())
sess.run(tf.global_variables_initializer())
features, transformed = sess.run([features, transformed])
self.assertAllEqual([3], features["length"])
self.assertAllEqual(
[[[0, 1, 2, 2, 4], [3, 4, 5, 2, 5], [5, 5, 5, 5, 5]]],
features["char_ids"])
self.assertAllEqual([1, 3, 5], transformed.shape)
def testMixedInputter(self):
vocab_file = self._makeTextFile("vocab.txt",
["the", "world", "hello", "toto"])
vocab_alt_file = self._makeTextFile("vocab_alt.txt",
["h", "e", "l", "w", "o"])
data_file = self._makeTextFile("data.txt", ["hello world !"])
mixed_inputter = inputter.MixedInputter(
[
text_inputter.WordEmbedder(embedding_size=10),
text_inputter.CharConvEmbedder(10, 5),
],
reducer=reducer.ConcatReducer(),
)
self.assertEqual(mixed_inputter.num_outputs, 1)
features, transformed = self._makeDataset(
mixed_inputter,
data_file,
data_config={
"1_vocabulary": vocab_file,
"2_vocabulary": vocab_alt_file
},
shapes={
"char_ids": [None, None, None],
"ids": [None, None],
"length": [None],
},
)
self.assertAllEqual([1, 3, 15], transformed.shape)
def testMixedInputter(self):
vocab_file = self._makeTextFile("vocab.txt",
["the", "world", "hello", "toto"])
vocab_alt_file = self._makeTextFile("vocab_alt.txt",
["h", "e", "l", "w", "o"])
data_file = self._makeTextFile("data.txt", ["hello world !"])
mixed_inputter = inputter.MixedInputter(
[
text_inputter.WordEmbedder("vocabulary_file_1",
embedding_size=10),
text_inputter.CharConvEmbedder("vocabulary_file_2", 10, 5)
],
reducer=reducer.ConcatReducer())
self.assertEqual(mixed_inputter.num_outputs, 1)
features, transformed = self._makeDataset(mixed_inputter,
data_file,
metadata={
"vocabulary_file_1":
vocab_file,
"vocabulary_file_2":
vocab_alt_file
},
shapes={
"char_ids":
[None, None, None],
"ids": [None, None],
"length": [None]
})
with self.test_session() as sess:
sess.run(tf.tables_initializer())
sess.run(tf.global_variables_initializer())
features, transformed = sess.run([features, transformed])
self.assertAllEqual([1, 3, 15], transformed.shape)
def testCharConvEmbedder(self):
with open(vocab_file, "w") as vocab:
vocab.write("h\n"
"e\n"
"l\n"
"w\n"
"o\n")
with open(data_file, "w") as data:
data.write("hello world !\n")
embedder = text_inputter.CharConvEmbedder("vocabulary_file", 10, 5)
data, transformed = _first_element(
embedder, data_file, {"vocabulary_file": vocab_file})
input_receiver = embedder.get_serving_input_receiver()
self.assertAllEqual(
[None, None, None],
input_receiver.features["char_ids"].get_shape().as_list())
self.assertAllEqual(
[None],
input_receiver.features["length"].get_shape().as_list())
with self.test_session() as sess:
sess.run(tf.tables_initializer())
sess.run(tf.global_variables_initializer())
data, transformed = sess.run([data, transformed])
self.assertNotIn("raw", data)
self.assertNotIn("tokens", data)
self.assertAllEqual([3], data["length"])
self.assertAllEqual(
[[[0, 1, 2, 2, 4], [3, 4, 5, 2, 5], [5, 5, 5, 5, 5]]],
data["char_ids"])
self.assertAllEqual([1, 3, 5], transformed.shape)
def testMixedInputter(self):
with open(vocab_file, "w") as vocab:
vocab.write("the\n" "world\n" "hello\n" "toto\n")
with open(vocab_alt_file, "w") as vocab_alt:
vocab_alt.write("h\n" "e\n" "l\n" "w\n" "o\n")
with open(data_file, "w") as data:
data.write("hello world !\n")
mixed_inputter = inputter.MixedInputter(
[
text_inputter.WordEmbedder("vocabulary_file_1",
embedding_size=10),
text_inputter.CharConvEmbedder("vocabulary_file_2", 10, 5)
],
reducer=reducer.ConcatReducer())
data, transformed = _first_element(mixed_inputter, data_file, {
"vocabulary_file_1": vocab_file,
"vocabulary_file_2": vocab_alt_file
})
input_receiver = mixed_inputter.get_serving_input_receiver()
self.assertIn("ids", input_receiver.features)
self.assertIn("char_ids", input_receiver.features)
with self.test_session() as sess:
sess.run(tf.tables_initializer())
sess.run(tf.global_variables_initializer())
data, transformed = sess.run([data, transformed])
self.assertNotIn("raw", data)
self.assertNotIn("tokens", data)
self.assertIn("ids", data)
self.assertIn("char_ids", data)
self.assertAllEqual([1, 3, 15], transformed.shape)
def testCharConvEmbedder(self):
vocab_file = self._makeTextFile("vocab.txt", ["h", "e", "l", "w", "o"])
data_file = self._makeTextFile("data.txt", ["hello world !"])
embedder = text_inputter.CharConvEmbedder("vocabulary_file", 10, 5)
features, transformed = self._makeDataset(
embedder,
data_file,
metadata={"vocabulary_file": vocab_file},
shapes={"char_ids": [None, None, None], "length": [None]})
self.assertAllEqual([3], features["length"])
self.assertAllEqual(
[[[0, 1, 2, 2, 4], [3, 4, 5, 2, 5], [5, 5, 5, 5, 5]]],
features["char_ids"])
self.assertAllEqual([1, 3, 5], transformed.shape)
def testMixedInputter(self):
vocab_file = os.path.join(self.get_temp_dir(), "vocab.txt")
vocab_alt_file = os.path.join(self.get_temp_dir(), "vocab_alt.txt")
data_file = os.path.join(self.get_temp_dir(), "data.txt")
with open(vocab_file, "w") as vocab:
vocab.write("the\n" "world\n" "hello\n" "toto\n")
with open(vocab_alt_file, "w") as vocab_alt:
vocab_alt.write("h\n" "e\n" "l\n" "w\n" "o\n")
with open(data_file, "w") as data:
data.write("hello world !\n")
mixed_inputter = inputter.MixedInputter(
[
text_inputter.WordEmbedder("vocabulary_file_1",
embedding_size=10),
text_inputter.CharConvEmbedder("vocabulary_file_2", 10, 5)
],
reducer=reducer.ConcatReducer())
features, transformed = self._makeDataset(mixed_inputter,
data_file,
metadata={
"vocabulary_file_1":
vocab_file,
"vocabulary_file_2":
vocab_alt_file
},
shapes={
"char_ids":
[None, None, None],
"ids": [None, None],
"length": [None]
})
self.assertNotIn("tokens", features)
with self.test_session() as sess:
sess.run(tf.tables_initializer())
sess.run(tf.global_variables_initializer())
features, transformed = sess.run([features, transformed])
self.assertAllEqual([1, 3, 15], transformed.shape)