refactoring generation

transformers/configuration_utils.py

@@ -57,8 +57,19 @@ class PretrainedConfig(object):
         self.torchscript = kwargs.pop('torchscript', False)  # Only used by PyTorch models
         self.use_bfloat16 = kwargs.pop('use_bfloat16', False)
         self.pruned_heads = kwargs.pop('pruned_heads', {})
+
+        # Is decoder is used in encoder-decoder models to differentiate encoder from decoder
         self.is_decoder = kwargs.pop('is_decoder', False)
 
+        # Parameters for sequence generation
+        self.generate_length = kwargs.pop('generate_length', 10)
+        self.generate_do_sample = kwargs.pop('generate_do_sample', False)
+        self.generate_num_beams = kwargs.pop('generate_num_beams', 1)
+        self.generate_temperature = kwargs.pop('generate_temperature', 1.0)
+        self.generate_top_k = kwargs.pop('generate_top_k', 50)
+        self.generate_top_p = kwargs.pop('generate_top_p', 0.0)
+        self.generate_repetition_penalty = kwargs.pop('generate_repetition_penalty', 1.0)
+
     def save_pretrained(self, save_directory):
         """ Save a configuration object to the directory `save_directory`, so that it
             can be re-loaded using the :func:`~transformers.PretrainedConfig.from_pretrained` class method.