consistent ignore keys + make private (#8737)

* consistent ignore keys + make private

* style

* - authorized_missing_keys    => _keys_to_ignore_on_load_missing
  - authorized_unexpected_keys => _keys_to_ignore_on_load_unexpected

* move public doc of private attributes to private comment

src/transformers/models/mbart/modeling_mbart.py

@@ -29,11 +29,11 @@ class MBartForConditionalGeneration(BartForConditionalGeneration):
     """
     model_type = "mbart"
     config_class = MBartConfig
-    authorized_missing_keys = [
+    _keys_to_ignore_on_load_missing = [
         "model.encoder.embed_positions.weight",
         "model.decoder.embed_positions.weight",
     ]
-    keys_to_never_save = [
+    _keys_to_ignore_on_save = [
         "model.encoder.embed_positions.weight",
         "model.decoder.embed_positions.weight",
     ]

src/transformers/models/mobilebert/modeling_mobilebert.py

@@ -677,7 +677,7 @@ class MobileBertPreTrainedModel(PreTrainedModel):
     pretrained_model_archive_map = MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST
     load_tf_weights = load_tf_weights_in_mobilebert
     base_model_prefix = "mobilebert"
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def _init_weights(self, module):
         """ Initialize the weights """
@@ -1054,7 +1054,7 @@ class MobileBertForPreTraining(MobileBertPreTrainedModel):
 @add_start_docstrings("""MobileBert Model with a `language modeling` head on top. """, MOBILEBERT_START_DOCSTRING)
 class MobileBertForMaskedLM(MobileBertPreTrainedModel):
 
-    authorized_unexpected_keys = [r"pooler"]
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
 
     def __init__(self, config):
         super().__init__(config)
@@ -1350,7 +1350,7 @@ class MobileBertForSequenceClassification(MobileBertPreTrainedModel):
 )
 class MobileBertForQuestionAnswering(MobileBertPreTrainedModel):
 
-    authorized_unexpected_keys = [r"pooler"]
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
 
     def __init__(self, config):
         super().__init__(config)
@@ -1545,7 +1545,7 @@ class MobileBertForMultipleChoice(MobileBertPreTrainedModel):
 )
 class MobileBertForTokenClassification(MobileBertPreTrainedModel):
 
-    authorized_unexpected_keys = [r"pooler"]
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
 
     def __init__(self, config):
         super().__init__(config)

src/transformers/models/mobilebert/modeling_tf_mobilebert.py

@@ -1030,7 +1030,7 @@ class TFMobileBertForPreTraining(TFMobileBertPreTrainedModel):
 @add_start_docstrings("""MobileBert Model with a `language modeling` head on top. """, MOBILEBERT_START_DOCSTRING)
 class TFMobileBertForMaskedLM(TFMobileBertPreTrainedModel, TFMaskedLanguageModelingLoss):
 
-    authorized_missing_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"pooler"]
 
     def __init__(self, config, *inputs, **kwargs):
         super().__init__(config, *inputs, **kwargs)
@@ -1297,7 +1297,7 @@ class TFMobileBertForSequenceClassification(TFMobileBertPreTrainedModel, TFSeque
 )
 class TFMobileBertForQuestionAnswering(TFMobileBertPreTrainedModel, TFQuestionAnsweringLoss):
 
-    authorized_missing_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"pooler"]
 
     def __init__(self, config, *inputs, **kwargs):
         super().__init__(config, *inputs, **kwargs)
@@ -1529,7 +1529,7 @@ class TFMobileBertForMultipleChoice(TFMobileBertPreTrainedModel, TFMultipleChoic
 )
 class TFMobileBertForTokenClassification(TFMobileBertPreTrainedModel, TFTokenClassificationLoss):
 
-    authorized_missing_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"pooler"]
 
     def __init__(self, config, *inputs, **kwargs):
         super().__init__(config, *inputs, **kwargs)

src/transformers/models/mt5/modeling_mt5.py

@@ -42,12 +42,12 @@ class MT5Model(T5Model):
     """
     model_type = "mt5"
     config_class = MT5Config
-    authorized_missing_keys = [
+    _keys_to_ignore_on_load_missing = [
         r"encoder\.embed_tokens\.weight",
         r"decoder\.embed_tokens\.weight",
         r"decoder\.block\.0\.layer\.1\.EncDecAttention\.relative_attention_bias\.weight",
     ]
-    keys_to_never_save = [
+    _keys_to_ignore_on_save = [
         r"encoder\.embed_tokens\.weight",
         r"decoder\.embed_tokens\.weight",
     ]
@@ -71,13 +71,13 @@ class MT5ForConditionalGeneration(T5ForConditionalGeneration):
 
     model_type = "mt5"
     config_class = MT5Config
-    authorized_missing_keys = [
+    _keys_to_ignore_on_load_missing = [
         r"encoder\.embed_tokens\.weight",
         r"decoder\.embed_tokens\.weight",
         r"lm_head\.weight",
         r"decoder\.block\.0\.layer\.1\.EncDecAttention\.relative_attention_bias\.weight",
     ]
-    keys_to_never_save = [
+    _keys_to_ignore_on_save = [
         r"encoder\.embed_tokens\.weight",
         r"decoder\.embed_tokens\.weight",
     ]

src/transformers/models/openai/modeling_openai.py

@@ -279,7 +279,7 @@ class OpenAIGPTPreTrainedModel(PreTrainedModel):
     config_class = OpenAIGPTConfig
     load_tf_weights = load_tf_weights_in_openai_gpt
     base_model_prefix = "transformer"
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def _init_weights(self, module):
         """Initialize the weights."""

src/transformers/models/pegasus/modeling_pegasus.py

@@ -46,14 +46,14 @@ class PegasusForConditionalGeneration(BartForConditionalGeneration):
     """
     # All the code is in src/transformers/models/bart/modeling_bart.py
     config_class = PegasusConfig
-    authorized_missing_keys = [
+    _keys_to_ignore_on_load_missing = [
         r"final_logits_bias",
         r"encoder\.version",
         r"decoder\.version",
         "model.encoder.embed_positions",
         "model.decoder.embed_positions",
     ]
-    keys_to_never_save = [
+    _keys_to_ignore_on_save = [
         "model.encoder.embed_positions.weight",
         "model.decoder.embed_positions.weight",
     ]

src/transformers/models/pegasus/modeling_tf_pegasus.py

@@ -32,7 +32,7 @@ logger = logging.get_logger(__name__)
 
 @add_start_docstrings("Pegasus model for summarization", START_DOCSTRING)
 class TFPegasusForConditionalGeneration(TFBartForConditionalGeneration):
-    authorized_missing_keys = [
+    _keys_to_ignore_on_load_missing = [
         r"final_logits_bias",
         r"model.encoder.embed_positions.weight",
         r"model.decoder.embed_positions.weight",

src/transformers/models/rag/modeling_rag.py

@@ -216,7 +216,7 @@ class RagPreTrainedModel(PreTrainedModel):
     """
     config_class = RagConfig
     base_model_prefix = "rag"
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     @classmethod
     def from_pretrained_question_encoder_generator(

src/transformers/models/roberta/modeling_roberta.py

@@ -576,7 +576,7 @@ class RobertaModel(RobertaPreTrainedModel):
 
     """
 
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     # Copied from transformers.models.bert.modeling_bert.BertModel.__init__ with Bert->Roberta
     def __init__(self, config, add_pooling_layer=True):
@@ -711,8 +711,8 @@ class RobertaModel(RobertaPreTrainedModel):
     """RoBERTa Model with a `language modeling` head on top for CLM fine-tuning. """, ROBERTA_START_DOCSTRING
 )
 class RobertaForCausalLM(RobertaPreTrainedModel):
-    authorized_missing_keys = [r"position_ids", r"predictions.decoder.bias"]
-    authorized_unexpected_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"position_ids", r"predictions.decoder.bias"]
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
 
     def __init__(self, config):
         super().__init__(config)
@@ -829,8 +829,8 @@ class RobertaForCausalLM(RobertaPreTrainedModel):
 
 @add_start_docstrings("""RoBERTa Model with a `language modeling` head on top. """, ROBERTA_START_DOCSTRING)
 class RobertaForMaskedLM(RobertaPreTrainedModel):
-    authorized_missing_keys = [r"position_ids", r"predictions.decoder.bias"]
-    authorized_unexpected_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"position_ids", r"predictions.decoder.bias"]
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
 
     def __init__(self, config):
         super().__init__(config)
@@ -948,7 +948,7 @@ class RobertaLMHead(nn.Module):
     ROBERTA_START_DOCSTRING,
 )
 class RobertaForSequenceClassification(RobertaPreTrainedModel):
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def __init__(self, config):
         super().__init__(config)
@@ -1031,7 +1031,7 @@ class RobertaForSequenceClassification(RobertaPreTrainedModel):
     ROBERTA_START_DOCSTRING,
 )
 class RobertaForMultipleChoice(RobertaPreTrainedModel):
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def __init__(self, config):
         super().__init__(config)
@@ -1123,8 +1123,8 @@ class RobertaForMultipleChoice(RobertaPreTrainedModel):
     ROBERTA_START_DOCSTRING,
 )
 class RobertaForTokenClassification(RobertaPreTrainedModel):
-    authorized_unexpected_keys = [r"pooler"]
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def __init__(self, config):
         super().__init__(config)
@@ -1233,8 +1233,8 @@ class RobertaClassificationHead(nn.Module):
     ROBERTA_START_DOCSTRING,
 )
 class RobertaForQuestionAnswering(RobertaPreTrainedModel):
-    authorized_unexpected_keys = [r"pooler"]
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def __init__(self, config):
         super().__init__(config)

src/transformers/models/roberta/modeling_tf_roberta.py

@@ -765,7 +765,7 @@ class TFRobertaLMHead(tf.keras.layers.Layer):
 @add_start_docstrings("""RoBERTa Model with a `language modeling` head on top. """, ROBERTA_START_DOCSTRING)
 class TFRobertaForMaskedLM(TFRobertaPreTrainedModel, TFMaskedLanguageModelingLoss):
 
-    authorized_missing_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"pooler"]
 
     def __init__(self, config, *inputs, **kwargs):
         super().__init__(config, *inputs, **kwargs)
@@ -877,7 +877,7 @@ class TFRobertaClassificationHead(tf.keras.layers.Layer):
 )
 class TFRobertaForSequenceClassification(TFRobertaPreTrainedModel, TFSequenceClassificationLoss):
 
-    authorized_missing_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"pooler"]
 
     def __init__(self, config, *inputs, **kwargs):
         super().__init__(config, *inputs, **kwargs)
@@ -1084,7 +1084,7 @@ class TFRobertaForMultipleChoice(TFRobertaPreTrainedModel, TFMultipleChoiceLoss)
 )
 class TFRobertaForTokenClassification(TFRobertaPreTrainedModel, TFTokenClassificationLoss):
 
-    authorized_missing_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"pooler"]
 
     def __init__(self, config, *inputs, **kwargs):
         super().__init__(config, *inputs, **kwargs)
@@ -1171,7 +1171,7 @@ class TFRobertaForTokenClassification(TFRobertaPreTrainedModel, TFTokenClassific
 )
 class TFRobertaForQuestionAnswering(TFRobertaPreTrainedModel, TFQuestionAnsweringLoss):
 
-    authorized_missing_keys = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"pooler"]
 
     def __init__(self, config, *inputs, **kwargs):
         super().__init__(config, *inputs, **kwargs)

src/transformers/models/squeezebert/modeling_squeezebert.py

@@ -428,7 +428,7 @@ class SqueezeBertPreTrainedModel(PreTrainedModel):
 
     config_class = SqueezeBertConfig
     base_model_prefix = "transformer"
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def _init_weights(self, module):
         """ Initialize the weights """
@@ -642,7 +642,7 @@ class SqueezeBertModel(SqueezeBertPreTrainedModel):
 @add_start_docstrings("""SqueezeBERT Model with a `language modeling` head on top. """, SQUEEZEBERT_START_DOCSTRING)
 class SqueezeBertForMaskedLM(SqueezeBertPreTrainedModel):
 
-    authorized_missing_keys = [r"predictions.decoder.bias"]
+    _keys_to_ignore_on_load_missing = [r"predictions.decoder.bias"]
 
     def __init__(self, config):
         super().__init__(config)

src/transformers/models/t5/modeling_t5.py

@@ -1086,7 +1086,7 @@ T5_INPUTS_DOCSTRING = r"""
     T5_START_DOCSTRING,
 )
 class T5Model(T5PreTrainedModel):
-    authorized_missing_keys = [
+    _keys_to_ignore_on_load_missing = [
         r"encoder\.embed_tokens\.weight",
         r"decoder\.embed_tokens\.weight",
         r"decoder\.block\.0\.layer\.1\.EncDecAttention\.relative_attention_bias\.weight",
@@ -1258,7 +1258,7 @@ class T5Model(T5PreTrainedModel):
 
 @add_start_docstrings("""T5 Model with a `language modeling` head on top. """, T5_START_DOCSTRING)
 class T5ForConditionalGeneration(T5PreTrainedModel):
-    authorized_missing_keys = [
+    _keys_to_ignore_on_load_missing = [
         r"encoder\.embed_tokens\.weight",
         r"decoder\.embed_tokens\.weight",
         r"lm_head\.weight",

src/transformers/models/xlm/modeling_xlm.py

@@ -399,7 +399,7 @@ XLM_INPUTS_DOCSTRING = r"""
     XLM_START_DOCSTRING,
 )
 class XLMModel(XLMPreTrainedModel):
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def __init__(self, config):
         super().__init__(config)

templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_{{cookiecutter.lowercase_modelname}}.py

@@ -540,7 +540,7 @@ class {{cookiecutter.camelcase_modelname}}PreTrainedModel(PreTrainedModel):
     config_class = {{cookiecutter.camelcase_modelname}}Config
     load_tf_weights = load_tf_weights_in_{{cookiecutter.lowercase_modelname}}
     base_model_prefix = "{{cookiecutter.lowercase_modelname}}"
-    authorized_missing_keys = [r"position_ids"]
+    _keys_to_ignore_on_load_missing = [r"position_ids"]
 
     def _init_weights(self, module):
         """ Initialize the weights """

tests/test_modeling_common.py

@@ -135,17 +135,17 @@ class ModelTesterMixin:
                 max_diff = np.amax(np.abs(out_1 - out_2))
                 self.assertLessEqual(max_diff, 1e-5)
 
-    def test_save_load_keys_to_never_save(self):
+    def test_save_load__keys_to_ignore_on_save(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
 
         for model_class in self.all_model_classes:
             model = model_class(config)
-            keys_to_never_save = getattr(model, "keys_to_never_save", None)
-            if keys_to_never_save is None:
+            _keys_to_ignore_on_save = getattr(model, "_keys_to_ignore_on_save", None)
+            if _keys_to_ignore_on_save is None:
                 continue
 
             # check the keys are in the original state_dict
-            for k in keys_to_never_save:
+            for k in _keys_to_ignore_on_save:
                 self.assertIn(k, model.state_dict())
 
             # check that certain keys didn't get saved with the model
@@ -153,7 +153,7 @@ class ModelTesterMixin:
                 model.save_pretrained(tmpdirname)
                 output_model_file = os.path.join(tmpdirname, WEIGHTS_NAME)
                 state_dict_saved = torch.load(output_model_file)
-                for k in keys_to_never_save:
+                for k in _keys_to_ignore_on_save:
                     self.assertNotIn(k, state_dict_saved)
 
     def test_initialization(self):

tests/test_modeling_marian.py

@@ -60,7 +60,7 @@ class ModelTester:
 class SelectiveCommonTest(unittest.TestCase):
     all_model_classes = (MarianMTModel,) if is_torch_available() else ()
 
-    test_save_load_keys_to_never_save = ModelTesterMixin.test_save_load_keys_to_never_save
+    test_save_load__keys_to_ignore_on_save = ModelTesterMixin.test_save_load__keys_to_ignore_on_save
 
     def setUp(self):
         self.model_tester = ModelTester(self)

tests/test_modeling_mbart.py

@@ -47,7 +47,7 @@ class ModelTester:
 class SelectiveCommonTest(unittest.TestCase):
     all_model_classes = (MBartForConditionalGeneration,) if is_torch_available() else ()
 
-    test_save_load_keys_to_never_save = ModelTesterMixin.test_save_load_keys_to_never_save
+    test_save_load__keys_to_ignore_on_save = ModelTesterMixin.test_save_load__keys_to_ignore_on_save
 
     def setUp(self):
         self.model_tester = ModelTester(self)

tests/test_modeling_pegasus.py

@@ -43,7 +43,7 @@ class ModelTester:
 class SelectiveCommonTest(unittest.TestCase):
     all_model_classes = (PegasusForConditionalGeneration,) if is_torch_available() else ()
 
-    test_save_load_keys_to_never_save = ModelTesterMixin.test_save_load_keys_to_never_save
+    test_save_load__keys_to_ignore_on_save = ModelTesterMixin.test_save_load__keys_to_ignore_on_save
 
     def setUp(self):
         self.model_tester = ModelTester(self)