def test_text_classification_demo(self):
with patch_data_loader():
with tempfile.TemporaryDirectory() as temp_dir:
# Use cached training data if exists.
data_dir = text_classification_demo.download_demo_data(
cache_dir=get_cache_dir(),
file_hash='9f81648d4199384278b86e315dac217c')
tflite_filename = os.path.join(temp_dir, 'model.tflite')
label_filename = os.path.join(temp_dir, 'label.txt')
vocab_filename = os.path.join(temp_dir, 'vocab.txt')
# TODO(b/150597348): Bert model is out of memory when export to tflite.
# Changed to a smaller bert models like mobilebert later for unittest.
text_classification_demo.run(data_dir,
tflite_filename,
label_filename,
vocab_filename,
spec='average_word_vec',
epochs=1,
batch_size=1)
self.assertTrue(tf.io.gfile.exists(tflite_filename))
self.assertGreater(os.path.getsize(tflite_filename), 0)
self.assertTrue(tf.io.gfile.exists(label_filename))
self.assertGreater(os.path.getsize(label_filename), 0)
self.assertTrue(tf.io.gfile.exists(vocab_filename))
self.assertGreater(os.path.getsize(vocab_filename), 0)
def text_classification(self,
data_dir,
tflite_filename,
label_filename,
vocab_filename,
spec='bert',
**kwargs):
r"""Run text classification.
Args:
data_dir: str, input directory of training data. (required)
tflite_filename: str, output path to export tflite file. (required)
label_filename: str, output path to export label file. (required)
vocab_filename: str, output path to export vocab file. (required)
spec: str, model_name. Valid: {MODELS}, default: bert.
**kwargs: --epochs: int, epoch num to run. More: see `create` function.
"""
# Convert types
data_dir = str(data_dir)
tflite_filename = str(tflite_filename)
label_filename = str(label_filename)
vocab_filename = str(vocab_filename)
text_classification_demo.run(data_dir, tflite_filename, label_filename,
vocab_filename, spec, **kwargs)
def text_classification(self,
data_dir,
export_dir,
spec='mobilebert_classifier',
**kwargs):
r"""Run text classification.
Args:
data_dir: str, input directory of training data. (required)
export_dir: str, output directory to export files. (required)
spec: str, model_name. Valid: {MODELS}, default: mobilebert_classifier.
**kwargs: --epochs: int, epoch num to run. More: see `create` function.
"""
# Convert types
data_dir = str(data_dir)
export_dir = str(export_dir)
text_classification_demo.run(data_dir, export_dir, spec, **kwargs)
