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)