def test_lm_generate_openai_gpt(self):
model = TFOpenAIGPTLMHeadModel.from_pretrained("openai-gpt")
input_ids = tf.convert_to_tensor([[481, 4735, 544]],
dtype=tf.int32) # the president is
expected_output_ids = [
481,
4735,
544,
246,
963,
870,
762,
239,
244,
40477,
244,
249,
719,
881,
487,
544,
240,
244,
603,
481,
] # the president is a very good man. " \n " i\'m sure he is, " said the
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(),
expected_output_ids)
def create_and_check_openai_gpt_lm_head(self, config, input_ids, input_mask, head_mask, token_type_ids, *args):
model = TFOpenAIGPTLMHeadModel(config=config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask, "token_type_ids": token_type_ids}
prediction_scores = model(inputs)[0]
result = {
"prediction_scores": prediction_scores.numpy(),
}
self.parent.assertListEqual(
list(result["prediction_scores"].shape), [self.batch_size, self.seq_length, self.vocab_size]
)
def create_and_check_openai_gpt_lm_head(self, config, input_ids,
input_mask, head_mask,
token_type_ids, *args):
model = TFOpenAIGPTLMHeadModel(config=config)
inputs = {
"input_ids": input_ids,
"attention_mask": input_mask,
"token_type_ids": token_type_ids
}
result = model(inputs)
self.parent.assertEqual(
result.logits.shape,
(self.batch_size, self.seq_length, self.vocab_size))
def initialize():
global model, tokenizer
model = TFOpenAIGPTLMHeadModel.from_pretrained("openai-gpt")
tokenizer = OpenAIGPTTokenizer.from_pretrained("openai-gpt")
