Removing BertConfig inheritance from LayoutLMConfig (#19307)

* removing BertConfig inheritance

* fix missing arguments

src/transformers/models/layoutlm/configuration_layoutlm.py

@@ -21,7 +21,6 @@ from transformers import PretrainedConfig, PreTrainedTokenizer, TensorType
 from ... import is_torch_available
 from ...onnx import OnnxConfig, PatchingSpec
 from ...utils import logging
-from ..bert.configuration_bert import BertConfig
 
 
 logger = logging.get_logger(__name__)
@@ -36,7 +35,7 @@ LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP = {
 }
 
 
-class LayoutLMConfig(BertConfig):
+class LayoutLMConfig(PretrainedConfig):
     r"""
     This is the configuration class to store the configuration of a [`LayoutLMModel`]. It is used to instantiate a
     LayoutLM model according to the specified arguments, defining the model architecture. Instantiating a configuration
@@ -110,25 +109,28 @@ class LayoutLMConfig(BertConfig):
         initializer_range=0.02,
         layer_norm_eps=1e-12,
         pad_token_id=0,
+        position_embedding_type="absolute",
+        use_cache=True,
+        classifier_dropout=None,
         max_2d_position_embeddings=1024,
         **kwargs
     ):
-        super().__init__(
-            vocab_size=vocab_size,
-            hidden_size=hidden_size,
-            num_hidden_layers=num_hidden_layers,
-            num_attention_heads=num_attention_heads,
-            intermediate_size=intermediate_size,
-            hidden_act=hidden_act,
-            hidden_dropout_prob=hidden_dropout_prob,
-            attention_probs_dropout_prob=attention_probs_dropout_prob,
-            max_position_embeddings=max_position_embeddings,
-            type_vocab_size=type_vocab_size,
-            initializer_range=initializer_range,
-            layer_norm_eps=layer_norm_eps,
-            pad_token_id=pad_token_id,
-            **kwargs,
-        )
+        super().__init__(pad_token_id=pad_token_id, **kwargs)
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.hidden_act = hidden_act
+        self.intermediate_size = intermediate_size
+        self.hidden_dropout_prob = hidden_dropout_prob
+        self.attention_probs_dropout_prob = attention_probs_dropout_prob
+        self.max_position_embeddings = max_position_embeddings
+        self.type_vocab_size = type_vocab_size
+        self.initializer_range = initializer_range
+        self.layer_norm_eps = layer_norm_eps
+        self.position_embedding_type = position_embedding_type
+        self.use_cache = use_cache
+        self.classifier_dropout = classifier_dropout
         self.max_2d_position_embeddings = max_2d_position_embeddings