"""simple docstring"""







from collections import OrderedDict
from typing import Any, List, Mapping, Optional

from ... import PretrainedConfig, PreTrainedTokenizer
from ...onnx import OnnxConfig, PatchingSpec
from ...utils import TensorType, is_torch_available, logging


UpperCamelCase_							:							Dict				 =		logging.get_logger(__name__)

UpperCamelCase_							:							List[Any]				 =		{
    """microsoft/layoutlm-base-uncased""": (
        """https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/config.json"""
    ),
    """microsoft/layoutlm-large-uncased""": (
        """https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/config.json"""
    ),
}


class       _lowercase		( lowercase_	):
				lowerCamelCase__							=							'layoutlm'

				def __init__(  self							:     Any							,     _lowercase							:     Tuple=3_0_5_2_2							,     _lowercase							:     Dict=7_6_8							,     _lowercase							:     Union[str, Any]=1_2							,     _lowercase							:     Dict=1_2							,     _lowercase							:     int=3_0_7_2							,     _lowercase							:     List[str]="gelu"							,     _lowercase							:     Any=0.1							,     _lowercase							:     Tuple=0.1							,     _lowercase							:     Optional[int]=5_1_2							,     _lowercase							:     Tuple=2							,     _lowercase							:     Optional[int]=0.02							,     _lowercase							:     List[str]=1e-12							,     _lowercase							:     Dict=0							,     _lowercase							:     List[str]="absolute"							,     _lowercase							:     Optional[int]=True							,     _lowercase							:     List[str]=1_0_2_4							,     **_lowercase							:     Tuple							,     ):


										'''simple docstring'''
										super().__init__(pad_token_id=a__							,     **a__  )
										UpperCAmelCase__       						=		vocab_size
										UpperCAmelCase__       						=		hidden_size
										UpperCAmelCase__       						=		num_hidden_layers
										UpperCAmelCase__       						=		num_attention_heads
										UpperCAmelCase__       						=		hidden_act
										UpperCAmelCase__       						=		intermediate_size
										UpperCAmelCase__       						=		hidden_dropout_prob
										UpperCAmelCase__       						=		attention_probs_dropout_prob
										UpperCAmelCase__       						=		max_position_embeddings
										UpperCAmelCase__       						=		type_vocab_size
										UpperCAmelCase__       						=		initializer_range
										UpperCAmelCase__       						=		layer_norm_eps
										UpperCAmelCase__       						=		position_embedding_type
										UpperCAmelCase__       						=		use_cache
										UpperCAmelCase__       						=		max_ad_position_embeddings


class       _lowercase		( lowercase_	):

				def __init__(  self							:     Dict							,     _lowercase							:     Union[str, Any]							,     _lowercase							:     int = "default"							,     _lowercase							:     int = None							,     ):


										'''simple docstring'''
										super().__init__(a__							,     task=a__							,     patching_specs=a__  )
										UpperCAmelCase__       						=		config.max_ad_position_embeddings - 1

				@property
				def 							A			(  self							:     str  ):


										'''simple docstring'''
										return OrderedDict(
										    [
										        ("""input_ids""", {0: """batch""", 1: """sequence"""}),
										        ("""bbox""", {0: """batch""", 1: """sequence"""}),
										        ("""attention_mask""", {0: """batch""", 1: """sequence"""}),
										        ("""token_type_ids""", {0: """batch""", 1: """sequence"""}),
										    ]  )

				def 							A			(  self							:     List[str]							,     _lowercase							:     Optional[int]							,     _lowercase							:     List[Any] = -1							,     _lowercase							:     str = -1							,     _lowercase							:     str = False							,     _lowercase							:     Optional[Any] = None							,     ):


										'''simple docstring'''
										UpperCAmelCase__       						=		super().generate_dummy_inputs(
										    a__							,     batch_size=a__							,     seq_length=a__							,     is_pair=a__							,     framework=a__  )

										# Generate a dummy bbox
										UpperCAmelCase__       						=		[4_8, 8_4, 7_3, 1_2_8]

										if not framework == TensorType.PYTORCH:
																raise NotImplementedError("""Exporting LayoutLM to ONNX is currently only supported for PyTorch."""  )

										if not is_torch_available():
																raise ValueError("""Cannot generate dummy inputs without PyTorch installed."""  )
										import torch

										UpperCAmelCase__						,   UpperCAmelCase__       						=		input_dict["""input_ids"""].shape
										UpperCAmelCase__       						=		torch.tensor([*[box] * seq_length]  ).tile(a__							,     1							,     1  )
										return input_dict



from __future__ import annotations

from collections.abc import Iterable
from dataclasses import dataclass
from typing import Any

class 		__magic_name__				:


  """simple docstring"""





  _UpperCamelCase						 = ("_front", "_back", "_len")

  @dataclass
  class 		__magic_name__				:


    """simple docstring"""





    _UpperCamelCase						 = None
    _UpperCamelCase						 = None
    _UpperCamelCase						 = None







  class 		__magic_name__				:


    """simple docstring"""





    _UpperCamelCase						 = ("_cur",)


    def __init__(					self	,		a__		):
      _lowerCamelCase      =						cur


    def __iter__(					self		):
      return self


    def     _UpperCAmelCase  (					self		):
      if self._cur is None:
        # finished iterating
        raise StopIteration
      _lowerCamelCase      =						self._cur.val
      _lowerCamelCase      =						self._cur.next_node

      return val







  def __init__(					self	,		a__ = None		):
    _lowerCamelCase      =						None
    _lowerCamelCase      =						None
    _lowerCamelCase      =						0

    if iterable is not None:
      # append every value to the deque
      for val in iterable:
        self.append(a__		)


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						self._Node(a__	,		a__	,		a__		)
    if self.is_empty():
      # front = back
      _lowerCamelCase      =						_lowerCamelCase      =						node
      _lowerCamelCase      =						1
    else:
      # connect nodes
      _lowerCamelCase      =						node
      _lowerCamelCase      =						self._back
      _lowerCamelCase      =						node  # assign new back to the new node

      self._len += 1

      # make sure there were no errors
      assert not self.is_empty(), "Error on appending value."


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						self._Node(a__	,		a__	,		a__		)
    if self.is_empty():
      # front = back
      _lowerCamelCase      =						_lowerCamelCase      =						node
      _lowerCamelCase      =						1
    else:
      # connect nodes
      _lowerCamelCase      =						self._front
      _lowerCamelCase      =						node
      _lowerCamelCase      =						node  # assign new front to the new node

      self._len += 1

      # make sure there were no errors
      assert not self.is_empty(), "Error on appending value."


  def     _UpperCAmelCase  (					self	,		a__		):
    for val in iterable:
      self.append(a__		)


  def     _UpperCAmelCase  (					self	,		a__		):
    for val in iterable:
      self.appendleft(a__		)


  def     _UpperCAmelCase  (					self		):
    assert not self.is_empty(), "Deque is empty."

    _lowerCamelCase      =						self._back
    _lowerCamelCase      =						self._back.prev_node  # set new back
    # drop the last node - python will deallocate memory automatically
    _lowerCamelCase      =						None

    self._len -= 1

    return topop.val


  def     _UpperCAmelCase  (					self		):
    assert not self.is_empty(), "Deque is empty."

    _lowerCamelCase      =						self._front
    _lowerCamelCase      =						self._front.next_node  # set new front and drop the first node
    _lowerCamelCase      =						None

    self._len -= 1

    return topop.val


  def     _UpperCAmelCase  (					self		):
    return self._front is None


  def __len__(					self		):
    return self._len


  def __eq__(					self	,		a__		):

    if not isinstance(a__	,		a__		):
      return NotImplemented

    _lowerCamelCase      =						self._front
    _lowerCamelCase      =						other._front

    # if the length of the dequeues are not the same, they are not equal
    if len(self		) != len(a__		):
      return False

    while me is not None and oth is not None:
      # compare every value
      if me.val != oth.val:
        return False
      _lowerCamelCase      =						me.next_node
      _lowerCamelCase      =						oth.next_node

    return True


  def __iter__(					self		):
    return Deque._Iterator(self._front		)


  def __repr__(					self		):
    _lowerCamelCase      =						[]
    _lowerCamelCase      =						self._front
    while aux is not None:
      # append the values in a list to display
      values_list.append(aux.val		)
      _lowerCamelCase      =						aux.next_node

    return f'''[{', '.join(repr(a__		) for val in values_list		)}]'''


if __name__ == "__main__":
  import doctest

  doctest.testmod()




