# Copyright 2021, The Microsoft Research Asia MarkupLM Team authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """MarkupLM model configuration""" from huggingface_hub.dataclasses import strict from ...configuration_utils import PreTrainedConfig from ...utils import auto_docstring @auto_docstring(checkpoint="microsoft/markuplm-base") @strict class MarkupLMConfig(PreTrainedConfig): r""" max_xpath_tag_unit_embeddings (`int`, *optional*, defaults to 256): The maximum value that the xpath tag unit embedding might ever use. Typically set this to something large just in case (e.g., 256). max_xpath_subs_unit_embeddings (`int`, *optional*, defaults to 1024): The maximum value that the xpath subscript unit embedding might ever use. Typically set this to something large just in case (e.g., 1024). tag_pad_id (`int`, *optional*, defaults to 216): The id of the padding token in the xpath tags. subs_pad_id (`int`, *optional*, defaults to 1001): The id of the padding token in the xpath subscripts. xpath_unit_hidden_size (`int`, *optional*, defaults to 32): The hidden size of each unit in xpath. max_depth (`int`, *optional*, defaults to 50): The maximum depth in xpath. Examples: ```python >>> from transformers import MarkupLMModel, MarkupLMConfig >>> # Initializing a MarkupLM microsoft/markuplm-base style configuration >>> configuration = MarkupLMConfig() >>> # Initializing a model from the microsoft/markuplm-base style configuration >>> model = MarkupLMModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" model_type = "markuplm" vocab_size: int = 30522 hidden_size: int = 768 num_hidden_layers: int = 12 num_attention_heads: int = 12 intermediate_size: int = 3072 hidden_act: str = "gelu" hidden_dropout_prob: float | int = 0.1 attention_probs_dropout_prob: float | int = 0.1 max_position_embeddings: int = 512 type_vocab_size: int = 2 initializer_range: float = 0.02 layer_norm_eps: float = 1e-12 pad_token_id: int | None = 0 bos_token_id: int | None = 0 eos_token_id: int | list[int] | None = 2 max_xpath_tag_unit_embeddings: int = 256 max_xpath_subs_unit_embeddings: int = 1024 tag_pad_id: int = 216 subs_pad_id: int = 1001 xpath_unit_hidden_size: int = 32 max_depth: int = 50 use_cache: bool = True classifier_dropout: float | int | None = None __all__ = ["MarkupLMConfig"]