def test_TFXLMForQuestionAnsweringSimple(self):
from transformers import XLMConfig, TFXLMForQuestionAnsweringSimple
keras.backend.clear_session()
# pretrained_weights = 'xlm-mlm-enfr-1024'
tokenizer_file = 'xlm_xlm-mlm-enfr-1024.pickle'
tokenizer = self._get_tokenzier(tokenizer_file)
text, inputs, inputs_onnx = self._prepare_inputs(tokenizer)
config = XLMConfig()
model = TFXLMForQuestionAnsweringSimple(config)
predictions = model.predict(inputs)
onnx_model = keras2onnx.convert_keras(model, model.name)
self.assertTrue(run_onnx_runtime(onnx_model.graph.name, onnx_model, inputs_onnx, predictions, self.model_files))
def create_and_check_xlm_qa(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
input_mask,
):
model = TFXLMForQuestionAnsweringSimple(config)
inputs = {"input_ids": input_ids, "lengths": input_lengths}
start_logits, end_logits = model(inputs)
result = {
"start_logits": start_logits.numpy(),
"end_logits": end_logits.numpy(),
}
self.parent.assertListEqual(list(result["start_logits"].shape),
[self.batch_size, self.seq_length])
self.parent.assertListEqual(list(result["end_logits"].shape),
[self.batch_size, self.seq_length])
def test_TFXLMForQuestionAnsweringSimple(self):
from transformers import XLMTokenizer, TFXLMForQuestionAnsweringSimple
pretrained_weights = 'xlm-mlm-enfr-1024'
tokenizer = XLMTokenizer.from_pretrained(pretrained_weights)
text, inputs, inputs_onnx = self._prepare_inputs(tokenizer)
model = TFXLMForQuestionAnsweringSimple.from_pretrained(
pretrained_weights)
predictions = model.predict(inputs)
onnx_model = keras2onnx.convert_keras(model, model.name)
self.assertTrue(
run_onnx_runtime(onnx_model.graph.name, onnx_model, inputs_onnx,
predictions, self.model_files))
def create_and_check_xlm_qa(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = TFXLMForQuestionAnsweringSimple(config)
inputs = {"input_ids": input_ids, "lengths": input_lengths}
result = model(inputs)
self.parent.assertEqual(result.start_logits.shape, (self.batch_size, self.seq_length))
self.parent.assertEqual(result.end_logits.shape, (self.batch_size, self.seq_length))
