def test_run_detext_cnn_ranking(self):
"""
This method test run_detext with CNN models
"""
output = os.path.join(DataSetup.out_dir, "cnn_model")
self._cleanUp(output)
args = self.ranking_args + ["--out_dir", output]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def test_run_detext_multitask_ranking(self):
"""
This method test run_detext with multitasking models
"""
output = os.path.join(DataSetup.out_dir, "multitask_model")
args = self.multitask_args + [
"--task_ids", "0", "1", "--task_weights", "0.2", "0.8",
"--out_dir", output
]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def test_run_detext_lstm(self):
"""
This method test run_detext with LSTM models
"""
output = os.path.join(out_dir, "lstm")
args = self.args + \
["--filter_window_size", "0",
"--ftr_ext", "lstm",
"--num_hidden", "10",
"--out_dir", output]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def test_run_detext_cnn(self):
"""
This method test run_detext with CNN models
"""
output = os.path.join(out_dir, "cnn_model")
args = self.args + \
["--filter_window_size", "1", "2", "3",
"--ftr_ext", "cnn",
"--num_hidden", "10", "10", "5",
"--out_dir", output]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def test_run_detext_bert(self):
"""
This method test run_detext with BERT models
"""
output = os.path.join(out_dir, "bert")
args = self.args + \
["--ftr_ext", "bert",
"--bert_config_file", bert_config,
"--use_bert_dropout", "True",
"--out_dir", output]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def test_run_detext_multitask(self):
"""
This method test run_detext with multitasking models
"""
output = os.path.join(out_dir, "multitask_model")
args = self.multitask_args + \
["--filter_window_size", "3",
"--ftr_ext", "cnn",
"--num_hidden", "10",
"--task_ids", "0,1",
"--task_weights", "0.2,0.8",
"--out_dir", output]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def test_run_detext_libert_space_ranking(self):
"""
This method test run_detext with LiBERT space tokenization models
"""
output = os.path.join(DataSetup.out_dir, "libert_space_model")
self._cleanUp(output)
args = self.bert_args + [
"--bert_hub_url",
DataSetup.libert_space_hub_url, # pretrained bert hidden size: 16
"--out_dir",
output
]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def test_run_detext_libert_classification(self):
"""
This method tests run_detext for libert classification fine-tuning
"""
output = os.path.join(DataSetup.out_dir, "cls_libert_model")
args = self.base_args + [
"--task_type", "classification", "--ftr_ext", "bert", "--lr_bert",
"0.00001", "--bert_hub_url", DataSetup.libert_sp_hub_url,
"--num_units", "16", f"--{InputFtrType.LABEL_COLUMN_NAME}",
"label", f"--{InputFtrType.DOC_TEXT_COLUMN_NAMES}", "query_text",
f"--{InputFtrType.USER_TEXT_COLUMN_NAMES}", "user_headline",
f"--{InputFtrType.DENSE_FTRS_COLUMN_NAMES}", "dense_ftrs",
f"--{InputFtrType.SHALLOW_TOWER_SPARSE_FTRS_COLUMN_NAMES}",
"sparse_ftrs", "--nums_shallow_tower_sparse_ftrs", "30",
"--nums_dense_ftrs", "8", "--num_classes", "6", "--pmetric",
"accuracy", "--all_metrics", "accuracy", "confusion_matrix",
"--test_file", DataSetup.cls_data_dir, "--dev_file",
DataSetup.cls_data_dir, "--train_file", DataSetup.cls_data_dir,
"--out_dir", output
]
sys.argv[1:] = args
main(sys.argv)
self._cleanUp(output)
def train(self, training_data_path, validation_data_path, metadata_file,
checkpoint_path, execution_context, schema_params):
# Delegate to super class
detext_driver.main(None)
