


"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase				=						logging.get_logger(__name__)

UpperCAmelCase				=						{
    """microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
    """microsoft/markuplm-large""": """https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json""",
}




class 	lowercase__				(					A_				):
   __UpperCAmelCase							       =					'''markuplm'''





   def __init__(							self      ,   SCREAMING_SNAKE_CASE=3_0522      ,   SCREAMING_SNAKE_CASE=768      ,   SCREAMING_SNAKE_CASE=12      ,   SCREAMING_SNAKE_CASE=12      ,   SCREAMING_SNAKE_CASE=3072      ,   SCREAMING_SNAKE_CASE="gelu"      ,   SCREAMING_SNAKE_CASE=0.1      ,   SCREAMING_SNAKE_CASE=0.1      ,   SCREAMING_SNAKE_CASE=512      ,   SCREAMING_SNAKE_CASE=2      ,   SCREAMING_SNAKE_CASE=0.02      ,   SCREAMING_SNAKE_CASE=1e-1_2      ,   SCREAMING_SNAKE_CASE=0      ,   SCREAMING_SNAKE_CASE=0      ,   SCREAMING_SNAKE_CASE=2      ,   SCREAMING_SNAKE_CASE=256      ,   SCREAMING_SNAKE_CASE=1024      ,   SCREAMING_SNAKE_CASE=216      ,   SCREAMING_SNAKE_CASE=1001      ,   SCREAMING_SNAKE_CASE=32      ,   SCREAMING_SNAKE_CASE=50      ,   SCREAMING_SNAKE_CASE="absolute"      ,   SCREAMING_SNAKE_CASE=True      ,   SCREAMING_SNAKE_CASE=None      ,   **SCREAMING_SNAKE_CASE      ,   )  ->  int:
      super().__init__(
          pad_token_id=SCREAMING_SNAKE_CASE      ,   bos_token_id=SCREAMING_SNAKE_CASE      ,   eos_token_id=SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE      ,   )
      _lowerCamelCase	:					str   =		vocab_size
      _lowerCamelCase	:					Union[str, Any]   =		hidden_size
      _lowerCamelCase	:					List[Any]   =		num_hidden_layers
      _lowerCamelCase	:					Any   =		num_attention_heads
      _lowerCamelCase	:					Union[str, Any]   =		hidden_act
      _lowerCamelCase	:					Optional[int]   =		intermediate_size
      _lowerCamelCase	:					Optional[int]   =		hidden_dropout_prob
      _lowerCamelCase	:					Union[str, Any]   =		attention_probs_dropout_prob
      _lowerCamelCase	:					List[Any]   =		max_position_embeddings
      _lowerCamelCase	:					Optional[int]   =		type_vocab_size
      _lowerCamelCase	:					int   =		initializer_range
      _lowerCamelCase	:					Tuple   =		layer_norm_eps
      _lowerCamelCase	:					str   =		position_embedding_type
      _lowerCamelCase	:					List[Any]   =		use_cache
      _lowerCamelCase	:					Tuple   =		classifier_dropout
      # additional properties
      _lowerCamelCase	:					Tuple   =		max_depth
      _lowerCamelCase	:					List[Any]   =		max_xpath_tag_unit_embeddings
      _lowerCamelCase	:					Optional[int]   =		max_xpath_subs_unit_embeddings
      _lowerCamelCase	:					Tuple   =		tag_pad_id
      _lowerCamelCase	:					int   =		subs_pad_id
      _lowerCamelCase	:					Optional[int]   =		xpath_unit_hidden_size




"""simple docstring"""




A_				:      Any           =			"0.21.0"

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
						from .utils import rich


