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


lowerCamelCase__	    =				logging.get_logger(__name__)

lowerCamelCase__	    =				{
    "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 					UpperCamelCase	(     UpperCamelCase_      ):
					__UpperCamelCase						=   """layoutlm"""




					def __init__( self :					Union[str, Any]      ,_lowerCAmelCase :					Optional[int]=30_522      ,_lowerCAmelCase :					str=768      ,_lowerCAmelCase :					Dict=12      ,_lowerCAmelCase :					int=12      ,_lowerCAmelCase :					Dict=3_072      ,_lowerCAmelCase :					Optional[int]="gelu"      ,_lowerCAmelCase :					Any=0.1      ,_lowerCAmelCase :					str=0.1      ,_lowerCAmelCase :					List[str]=512      ,_lowerCAmelCase :					Dict=2      ,_lowerCAmelCase :					Dict=0.0_2      ,_lowerCAmelCase :					Union[str, Any]=1E-12      ,_lowerCAmelCase :					Tuple=0      ,_lowerCAmelCase :					Dict="absolute"      ,_lowerCAmelCase :					Optional[Any]=True      ,_lowerCAmelCase :					Tuple=1_024      ,**_lowerCAmelCase :					Tuple      ,):


							"""simple docstring"""




							super().__init__(pad_token_id=__UpperCamelCase      ,**__UpperCamelCase						)
							__snake_case		       =     vocab_size
							__snake_case		       =     hidden_size
							__snake_case		       =     num_hidden_layers
							__snake_case		       =     num_attention_heads
							__snake_case		       =     hidden_act
							__snake_case		       =     intermediate_size
							__snake_case		       =     hidden_dropout_prob
							__snake_case		       =     attention_probs_dropout_prob
							__snake_case		       =     max_position_embeddings
							__snake_case		       =     type_vocab_size
							__snake_case		       =     initializer_range
							__snake_case		       =     layer_norm_eps
							__snake_case		       =     position_embedding_type
							__snake_case		       =     use_cache
							__snake_case		       =     max_ad_position_embeddings




class 					UpperCamelCase	(     UpperCamelCase_      ):




					def __init__( self :					Optional[int]      ,_lowerCAmelCase :					Dict      ,_lowerCAmelCase :					Optional[int] = "default"      ,_lowerCAmelCase :					int = None      ,):


							"""simple docstring"""




							super().__init__(__UpperCamelCase      ,task=__UpperCamelCase      ,patching_specs=__UpperCamelCase						)
							__snake_case		       =     config.max_ad_position_embeddings - 1




					@property
					def 							UpperCamelCase_						( self :					List[Any]						):


							"""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 							UpperCamelCase_						( self :					Union[str, Any]      ,_lowerCAmelCase :					Optional[int]      ,_lowerCAmelCase :					Optional[Any] = -1      ,_lowerCAmelCase :					Any = -1      ,_lowerCAmelCase :					Optional[int] = False      ,_lowerCAmelCase :					Tuple = None      ,):


							"""simple docstring"""




							__snake_case		       =     super().generate_dummy_inputs(
							    __UpperCamelCase      ,batch_size=__UpperCamelCase      ,seq_length=__UpperCamelCase      ,is_pair=__UpperCamelCase      ,framework=__UpperCamelCase						)

							# Generate a dummy bbox
							__snake_case		       =     [48, 84, 73, 128]

							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

							__snake_case		       =     input_dict['''input_ids'''].shape
							__snake_case		       =     torch.tensor([*[box] * seq_length]						).tile(__UpperCamelCase      ,1      ,1						)
							return input_dict






from __future__ import annotations

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




class 					UpperCamelCase	:
					__UpperCamelCase						=   ("""_front""", """_back""", """_len""")




					@dataclass
					class 					UpperCamelCase	:
										__UpperCamelCase						=   None
										__UpperCamelCase						=   None
										__UpperCamelCase						=   None




					class 					UpperCamelCase	:
										__UpperCamelCase						=   ("""_cur""",)




										def __init__( self :					Dict      ,_lowerCAmelCase :					Deque._Node | None						):


												"""simple docstring"""




												__snake_case		       =     cur




										def __iter__( self :					Dict						):


												"""simple docstring"""




												return self







										def 							UpperCamelCase_						( self :					Optional[Any]						):


												"""simple docstring"""




												if self._cur is None:
														# finished iterating
														raise StopIteration
												__snake_case		       =     self._cur.val
												__snake_case		       =     self._cur.next_node

												return val




					def __init__( self :					Optional[int]      ,_lowerCAmelCase :					Iterable[Any] | None = None						):


							"""simple docstring"""




							__snake_case		       =     None
							__snake_case		       =     None
							__snake_case		       =     0

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




					def 							UpperCamelCase_						( self :					int      ,_lowerCAmelCase :					Any						):


							"""simple docstring"""




							__snake_case		       =     self._Node(_lowerCAmelCase      ,_lowerCAmelCase      ,_lowerCAmelCase						)
							if self.is_empty():
									# front = back
									__snake_case		       =     __snake_case		       =     node
									__snake_case		       =     1
							else:
									# connect nodes
									__snake_case		       =     node
									__snake_case		       =     self._back
									__snake_case		       =     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 :					Any      ,_lowerCAmelCase :					Any						):


							"""simple docstring"""




							__snake_case		       =     self._Node(_lowerCAmelCase      ,_lowerCAmelCase      ,_lowerCAmelCase						)
							if self.is_empty():
									# front = back
									__snake_case		       =     __snake_case		       =     node
									__snake_case		       =     1
							else:
									# connect nodes
									__snake_case		       =     self._front
									__snake_case		       =     node
									__snake_case		       =     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 :					int      ,_lowerCAmelCase :					Iterable[Any]						):


							"""simple docstring"""




							for val in iterable:
									self.append(_lowerCAmelCase						)




					def 							UpperCamelCase_						( self :					Optional[int]      ,_lowerCAmelCase :					Iterable[Any]						):


							"""simple docstring"""




							for val in iterable:
									self.appendleft(_lowerCAmelCase						)




					def 							UpperCamelCase_						( self :					List[Any]						):


							"""simple docstring"""




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

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

							self._len -= 1

							return topop.val




					def 							UpperCamelCase_						( self :					List[str]						):


							"""simple docstring"""




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

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

							self._len -= 1

							return topop.val




					def 							UpperCamelCase_						( self :					int						):


							"""simple docstring"""




							return self._front is None




					def __len__( self :					Tuple						):


							"""simple docstring"""




							return self._len




					def __eq__( self :					Union[str, Any]      ,_lowerCAmelCase :					object						):


							"""simple docstring"""




							if not isinstance(_lowerCAmelCase      ,_lowerCAmelCase						):
									return NotImplemented

							__snake_case		       =     self._front
							__snake_case		       =     other._front

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

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

							return True




					def __iter__( self :					Tuple						):


							"""simple docstring"""




							return Deque._Iterator(self._front						)







					def __repr__( self :					List[Any]						):


							"""simple docstring"""




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

							return F"""[{", ".join(repr(_lowerCAmelCase						) for val in values_list						)}]"""


if __name__ == "__main__":
		import doctest

		doctest.testmod()





