remove RobertaConfig inheritance from MarkupLMConfig (#19404)

* remove RobertaConfig inheritance from MarkupLMConfig

* Update src/transformers/models/markuplm/configuration_markuplm.py

fixed typo in docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

src/transformers/models/markuplm/configuration_markuplm.py

@@ -14,9 +14,10 @@
 # limitations under the License.
 """ MarkupLM model configuration"""
 
-from transformers.models.roberta.configuration_roberta import RobertaConfig
 from transformers.utils import logging
 
+from ...configuration_utils import PretrainedConfig
+
 
 logger = logging.get_logger(__name__)
 
@@ -26,7 +27,7 @@ MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP = {
 }
 
 
-class MarkupLMConfig(RobertaConfig):
+class MarkupLMConfig(PretrainedConfig):
     r"""
     This is the configuration class to store the configuration of a [`MarkupLMModel`]. It is used to instantiate a
     MarkupLM model according to the specified arguments, defining the model architecture. Instantiating a configuration
@@ -116,6 +117,8 @@ class MarkupLMConfig(RobertaConfig):
         initializer_range=0.02,
         layer_norm_eps=1e-12,
         pad_token_id=0,
+        bos_token_id=0,
+        eos_token_id=2,
         gradient_checkpointing=False,
         max_xpath_tag_unit_embeddings=256,
         max_xpath_subs_unit_embeddings=1024,
@@ -123,25 +126,33 @@ class MarkupLMConfig(RobertaConfig):
         subs_pad_id=1001,
         xpath_unit_hidden_size=32,
         max_depth=50,
+        position_embedding_type="absolute",
+        use_cache=True,
+        classifier_dropout=None,
         **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,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
             gradient_checkpointing=gradient_checkpointing,
             **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
         # additional properties
         self.max_depth = max_depth
         self.max_xpath_tag_unit_embeddings = max_xpath_tag_unit_embeddings