def create_and_check_transfo_xl_model(self, config, input_ids_1,
input_ids_2, lm_labels):
model = TFTransfoXLModel(config)
hidden_states_1, mems_1 = model(input_ids_1)
inputs = {'input_ids': input_ids_2, 'mems': mems_1}
hidden_states_2, mems_2 = model(inputs)
result = {
"hidden_states_1": hidden_states_1.numpy(),
"mems_1": [mem.numpy() for mem in mems_1],
"hidden_states_2": hidden_states_2.numpy(),
"mems_2": [mem.numpy() for mem in mems_2],
}
self.parent.assertListEqual(
list(result["hidden_states_1"].shape),
[self.batch_size, self.seq_length, self.hidden_size])
self.parent.assertListEqual(
list(result["hidden_states_2"].shape),
[self.batch_size, self.seq_length, self.hidden_size])
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems_1"]),
[[self.mem_len, self.batch_size, self.hidden_size]] *
self.num_hidden_layers)
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems_2"]),
[[self.mem_len, self.batch_size, self.hidden_size]] *
self.num_hidden_layers)
def test_model_from_pretrained(self):
cache_dir = "/tmp/transformers_test/"
for model_name in list(
TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFTransfoXLModel.from_pretrained(model_name,
cache_dir=cache_dir)
shutil.rmtree(cache_dir)
self.assertIsNotNone(model)
def test_model_from_pretrained(self):
for model_name in list(
TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFTransfoXLModel.from_pretrained(model_name,
cache_dir=CACHE_DIR)
self.assertIsNotNone(model)