"""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


a							=logging.get_logger(__name__)

a							={
    '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						(     A__     ):
				A__				:       Union[str, Any]  							=	'''layoutlm'''

				def __init__(				self     ,			_lowerCamelCase=30522     ,			_lowerCamelCase=768     ,			_lowerCamelCase=12     ,			_lowerCamelCase=12     ,			_lowerCamelCase=3072     ,			_lowerCamelCase="gelu"     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=512     ,			_lowerCamelCase=2     ,			_lowerCamelCase=0.0_2     ,			_lowerCamelCase=1E-12     ,			_lowerCamelCase=0     ,			_lowerCamelCase="absolute"     ,			_lowerCamelCase=True     ,			_lowerCamelCase=1024     ,			**_lowerCamelCase     ,			):
								super().__init__(pad_token_id=_lowerCamelCase     ,			**_lowerCamelCase				)
								lowerCamelCase__ =vocab_size
								lowerCamelCase__ =hidden_size
								lowerCamelCase__ =num_hidden_layers
								lowerCamelCase__ =num_attention_heads
								lowerCamelCase__ =hidden_act
								lowerCamelCase__ =intermediate_size
								lowerCamelCase__ =hidden_dropout_prob
								lowerCamelCase__ =attention_probs_dropout_prob
								lowerCamelCase__ =max_position_embeddings
								lowerCamelCase__ =type_vocab_size
								lowerCamelCase__ =initializer_range
								lowerCamelCase__ =layer_norm_eps
								lowerCamelCase__ =position_embedding_type
								lowerCamelCase__ =use_cache
								lowerCamelCase__ =max_ad_position_embeddings






class        __UpperCAmelCase						(     A__     ):

				def __init__(				self     ,			_lowerCamelCase     ,			_lowerCamelCase = "default"     ,			_lowerCamelCase = None     ,			):
								super().__init__(_lowerCamelCase     ,			task=_lowerCamelCase     ,			patching_specs=_lowerCamelCase				)
								lowerCamelCase__ =config.max_ad_position_embeddings - 1

				@property
				def 		_a     (				self				):
								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     ,			_lowerCamelCase     ,			_lowerCamelCase = -1     ,			_lowerCamelCase = -1     ,			_lowerCamelCase = False     ,			_lowerCamelCase = None     ,			):
								lowerCamelCase__ =super().generate_dummy_inputs(
								    _lowerCamelCase     ,			batch_size=_lowerCamelCase     ,			seq_length=_lowerCamelCase     ,			is_pair=_lowerCamelCase     ,			framework=_lowerCamelCase				)

								# Generate a dummy bbox
								lowerCamelCase__ =[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

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



"""simple docstring"""


from __future__ import annotations

from collections.abc import Generator





def       lowerCamelCase_			( __lowerCAmelCase    )							-> Generator[int, None, None]:




						'''simple docstring'''



						if not isinstance(__lowerCAmelCase       ,   __lowerCAmelCase    ) or n < 1:
												raise Exception("Sequence only defined for positive integers"    )

						yield n
						while n != 1:
												if n % 2 == 0:
																		n //= 2
												else:
																		lowerCamelCase__ =3 * n + 1
												yield n





def       lowerCamelCase_			( )							-> List[str]:




						'''simple docstring'''



						lowerCamelCase__ =43
						lowerCamelCase__ =tuple(collatz_sequence(__lowerCAmelCase    )    )
						print(__lowerCAmelCase    )
						print(F'''Collatz sequence from {n} took {len(__lowerCAmelCase    )} steps.'''    )


if __name__ == "__main__":
	main()


