def prepare_config_and_inputs(self):
input_ids_1 = TransfoXLModelTest.ids_tensor(
[self.batch_size, self.seq_length], self.vocab_size)
input_ids_2 = TransfoXLModelTest.ids_tensor(
[self.batch_size, self.seq_length], self.vocab_size)
lm_labels = None
if self.use_labels:
lm_labels = TransfoXLModelTest.ids_tensor(
[self.batch_size, self.seq_length], self.vocab_size)
config = TransfoXLConfig(
vocab_size_or_config_json_file=self.vocab_size,
mem_len=self.mem_len,
clamp_len=self.clamp_len,
cutoffs=self.cutoffs,
d_model=self.d_model,
d_embed=self.d_embed,
n_head=self.n_head,
d_head=self.d_head,
d_inner=self.d_inner,
div_val=self.div_val,
n_layer=self.n_layer)
return (config, input_ids_1, input_ids_2, lm_labels)
def test_config_to_json_file(self):
config_first = TransfoXLConfig(vocab_size_or_config_json_file=96,
d_embed=37)
json_file_path = "/tmp/config.json"
config_first.to_json_file(json_file_path)
config_second = TransfoXLConfig.from_json_file(json_file_path)
os.remove(json_file_path)
self.assertEqual(config_second.to_dict(), config_first.to_dict())
def test_config_to_json_string(self):
config = TransfoXLConfig(vocab_size_or_config_json_file=96, d_embed=37)
obj = json.loads(config.to_json_string())
self.assertEqual(obj["n_token"], 96)
self.assertEqual(obj["d_embed"], 37)