Update configuration_gpt_bert.py

configuration_gpt_bert.py

@@ -1,30 +1,29 @@
-
 from transformers import PretrainedConfig
 
 class GPTBertConfig(PretrainedConfig):
     model_type = 'gpt_bert'
 
     def __init__(self, **kwargs):
-        self.attention_probs_dropout_prob = kwargs.pop('attention_probs_dropout_prob', 0.1)
-        self.hidden_dropout_prob = kwargs.pop('hidden_dropout_prob', 0.1)
-        self.hidden_size = kwargs.pop('hidden_size', 768)
-        self.intermediate_size = kwargs.pop('intermediate_size', 2560)
-        self.max_position_embeddings = kwargs.pop('max_position_embeddings', 512)
-        self.position_bucket_size = kwargs.pop('position_bucket_size', 32)
-        self.num_attention_heads = kwargs.pop('num_attention_heads', 12)
-        self.num_hidden_layers = kwargs.pop('num_hidden_layers', 12)
-        self.vocab_size = kwargs.pop('vocab_size', 16384)
-        self.layer_norm_eps = kwargs.pop('layer_norm_eps', 1e-5)
-        self.force_causal_mask = kwargs.pop('force_causal_mask', True)
-        self.classifier_dropout = kwargs.pop('classifier_dropout', 0.1)
-        self.classifier_layer_norm_eps = kwargs.pop('classifier_layer_norm_eps', 1e-05)
-        self.num_labels = kwargs.pop('num_labels', 2)
-        self.problem_type = kwargs.pop('problem_type', None)
-        self.auto_map = {
-    'AutoConfig': 'configuration_gpt_bert.GPTBertConfig',
-    'AutoModel': 'modeling_gpt_bert.GPTBertForMaskedLM',
-    'AutoModelForCausalLM': 'modeling_gpt_bert.GPTBertForCausalLM',
-    'AutoModelForMaskedLM': 'modeling_gpt_bert.GPTBertForMaskedLM',
-    'AutoModelForSequenceClassification': 'modeling_gpt_bert.GPTBertForSequenceClassification',
-        }
-        super().__init__(**kwargs)
+        kwargs.setdefault('attention_probs_dropout_prob', 0.1)
+        kwargs.setdefault('hidden_dropout_prob', 0.1)
+        kwargs.setdefault('hidden_size', 768)
+        kwargs.setdefault('intermediate_size', 2560)
+        kwargs.setdefault('max_position_embeddings', 512)
+        kwargs.setdefault('position_bucket_size', 32)
+        kwargs.setdefault('num_attention_heads', 12)
+        kwargs.setdefault('num_hidden_layers', 12)
+        kwargs.setdefault('vocab_size', 16384)
+        kwargs.setdefault('layer_norm_eps', 1e-5)
+        kwargs.setdefault('force_causal_mask', True)
+        kwargs.setdefault('classifier_dropout', 0.1)
+        kwargs.setdefault('classifier_layer_norm_eps', 1e-5)
+        kwargs.setdefault('num_labels', 2)
+        kwargs.setdefault('problem_type', None)
+        kwargs.setdefault('auto_map', {
+            'AutoConfig': 'configuration_gpt_bert.GPTBertConfig',
+            'AutoModel': 'modeling_gpt_bert.GPTBertForMaskedLM',
+            'AutoModelForCausalLM': 'modeling_gpt_bert.GPTBertForCausalLM',
+            'AutoModelForMaskedLM': 'modeling_gpt_bert.GPTBertForMaskedLM',
+            'AutoModelForSequenceClassification': 'modeling_gpt_bert.GPTBertForSequenceClassification',
+        })
+        super().__init__(**kwargs)