
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union

import numpy as np

from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase

def a__       (			A_,	A_,	A_,	A_   ):






  '''simple docstring'''





  if isinstance(lowerCAmelCase_,	lowerCAmelCase_   ):
    __magic_name__								=			np.full((len(lowerCAmelCase_   ), sequence_length, 2),	lowerCAmelCase_   )
  else:
    __magic_name__								=			np.full((len(lowerCAmelCase_   ), sequence_length),	lowerCAmelCase_   )

  for i, tensor in enumerate(lowerCAmelCase_   ):
    if padding_side == "right":
      if isinstance(lowerCAmelCase_,	lowerCAmelCase_   ):
        __magic_name__								=			tensor[:sequence_length]
      else:
        __magic_name__								=			tensor[:sequence_length]
    else:
      if isinstance(lowerCAmelCase_,	lowerCAmelCase_   ):
        __magic_name__								=			tensor[:sequence_length]
      else:
        __magic_name__								=			tensor[:sequence_length]

  return out_tensor.tolist()

def a__       (			A_   ):






  '''simple docstring'''





  __magic_name__								=			ord(lowerCAmelCase_   )
  if (cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126):
    return True
  __magic_name__								=			unicodedata.category(lowerCAmelCase_   )
  if cat.startswith("""P"""   ):
    return True
  return False





@dataclass
class 			UpperCAmelCase_     (					_UpperCamelCase	):


  '''simple docstring'''







  a__       			=						42
  a__       			=						True
  a__       			=						None
  a__       			=						None
  a__       			=						-1_00
  a__       			=						"pt"
  def 				_lowercase				(					self     :					Union[str, Any]     ,				UpperCamelCase__     :					List[Any]       )     ->      Optional[Any]:







    """simple docstring"""






    import torch

    __magic_name__								=			'label' if 'label' in features[0].keys() else 'labels'
    __magic_name__								=			[feature[label_name] for feature in features] if label_name in features[0].keys() else None
    __magic_name__								=			self.tokenizer.pad(
        _UpperCAmelCase     ,				padding=self.padding     ,				max_length=self.max_length     ,				pad_to_multiple_of=self.pad_to_multiple_of     ,				return_tensors="""pt""" if labels is None else None     ,				)

    if labels is None:
      return batch

    __magic_name__								=			torch.tensor(batch["""entity_ids"""]       ).shape[1]
    __magic_name__								=			self.tokenizer.padding_side
    if padding_side == "right":
      __magic_name__								=			[
          list(_UpperCAmelCase       ) + [self.label_pad_token_id] * (sequence_length - len(_UpperCAmelCase       )) for label in labels
      ]
    else:
      __magic_name__								=			[
          [self.label_pad_token_id] * (sequence_length - len(_UpperCAmelCase       )) + list(_UpperCAmelCase       ) for label in labels
      ]

    __magic_name__								=			[feature['ner_tags'] for feature in features]
    __magic_name__								=			padding_tensor(_UpperCAmelCase     ,				-1     ,				_UpperCAmelCase     ,				_UpperCAmelCase       )
    __magic_name__								=			[feature['original_entity_spans'] for feature in features]
    __magic_name__								=			padding_tensor(_UpperCAmelCase     ,				(-1, -1)     ,				_UpperCAmelCase     ,				_UpperCAmelCase       )
    __magic_name__								=			{k: torch.tensor(_UpperCAmelCase     ,				dtype=torch.intaa       ) for k, v in batch.items()}

    return batch






'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


__lowerCAmelCase		     =  logging.get_logger(__name__)

class       __magic_name__		(       _UpperCamelCase  ):







							def __init__(				self   :			Optional[int]      ,*_UpperCAmelCase   :			List[Any]      ,**_UpperCAmelCase   :			Union[str, Any]						):
									warnings.warn(
									    'The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
									    ' use GLPNImageProcessor instead.'      ,_UpperCAmelCase      ,)
									super().__init__(*_UpperCAmelCase      ,**_UpperCAmelCase						)




