

from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType





class        lowerCAmelCase__  (					__magic_name__			):



       '''simple docstring'''







       lowercase_						=    ["""image_processor""", """tokenizer"""]
       lowercase_						=    """Pix2StructImageProcessor"""
       lowercase_						=    ("""T5Tokenizer""", """T5TokenizerFast""")

       def __init__(							self ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             __A    =False
             super().__init__(lowercase__ ,   lowercase__     )

       def __call__(							self ,   lowercase__=None ,   lowercase__ = None ,   lowercase__ = True ,   lowercase__ = False ,   lowercase__ = None ,   lowercase__ = None ,   lowercase__ = 2_0_4_8 ,   lowercase__ = 0 ,   lowercase__ = None ,   lowercase__ = None ,   lowercase__ = False ,   lowercase__ = False ,   lowercase__ = False ,   lowercase__ = False ,   lowercase__ = False ,   lowercase__ = True ,   lowercase__ = None ,   **lowercase__ ,   ):







             '''simple docstring'''



             if images is None and text is None:
                   raise ValueError('''You have to specify either images or text.'''     )

             # Get only text
             if images is None and not self.image_processor.is_vqa:
                   __A    =self.tokenizer
                   __A    =self.tokenizer(
                       text=lowercase__ ,   add_special_tokens=lowercase__ ,   padding=lowercase__ ,   truncation=lowercase__ ,   max_length=lowercase__ ,   stride=lowercase__ ,   pad_to_multiple_of=lowercase__ ,   return_attention_mask=lowercase__ ,   return_overflowing_tokens=lowercase__ ,   return_special_tokens_mask=lowercase__ ,   return_offsets_mapping=lowercase__ ,   return_token_type_ids=lowercase__ ,   return_length=lowercase__ ,   verbose=lowercase__ ,   return_tensors=lowercase__ ,   **lowercase__ ,   )
                   return text_encoding

             if not self.image_processor.is_vqa:
                   # add pixel_values
                   __A    =self.image_processor(
                       lowercase__ ,   return_tensors=lowercase__ ,   max_patches=lowercase__ ,   **lowercase__     )
             else:
                   # add pixel_values and bbox
                   __A    =self.image_processor(
                       lowercase__ ,   return_tensors=lowercase__ ,   max_patches=lowercase__ ,   header_text=lowercase__ ,   **lowercase__     )

             if text is not None and not self.image_processor.is_vqa:
                   __A    =self.tokenizer(
                       text=lowercase__ ,   add_special_tokens=lowercase__ ,   padding=lowercase__ ,   truncation=lowercase__ ,   max_length=lowercase__ ,   stride=lowercase__ ,   pad_to_multiple_of=lowercase__ ,   return_attention_mask=lowercase__ ,   return_overflowing_tokens=lowercase__ ,   return_special_tokens_mask=lowercase__ ,   return_offsets_mapping=lowercase__ ,   return_token_type_ids=lowercase__ ,   return_length=lowercase__ ,   verbose=lowercase__ ,   return_tensors=lowercase__ ,   **lowercase__ ,   )

                   if "attention_mask" in text_encoding:
                         __A    =text_encoding.pop('''attention_mask'''     )
                   if "input_ids" in text_encoding:
                         __A    =text_encoding.pop('''input_ids'''     )
             else:
                   __A    =None

             if text_encoding is not None:
                   encoding_image_processor.update(lowercase__     )

             return encoding_image_processor

       def     __UpperCamelCase     (							self ,   *lowercase__ ,   **lowercase__     ):







             '''simple docstring'''



             return self.tokenizer.batch_decode(*lowercase__ ,   **lowercase__     )

       def     __UpperCamelCase     (							self ,   *lowercase__ ,   **lowercase__     ):







             '''simple docstring'''



             return self.tokenizer.decode(*lowercase__ ,   **lowercase__     )


       @property
       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =self.tokenizer.model_input_names
             __A    =self.image_processor.model_input_names
             return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names     )     )





import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


_lowerCamelCase      :					List[Any]					    =      logging.getLogger(__name__)





class        lowerCAmelCase__  (					__magic_name__			):



       '''simple docstring'''







       def __init__(							self ,   lowercase__=-1     ):







             '''simple docstring'''



             __A    =label_idx

       def     __UpperCamelCase     (							self ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             if isinstance(lowercase__ ,   lowercase__     ):
                   __A    =mode.value
             __A    =os.path.join(lowercase__ ,   f'''{mode}.txt'''     )
             __A    =1
             __A    =[]
             with open(lowercase__ ,   encoding='''utf-8'''     ) as f:
                   __A    =[]
                   __A    =[]
                   for line in f:
                         if line.startswith('''-DOCSTART-'''     ) or line == "" or line == "\n":
                               if words:
                                     examples.append(InputExample(guid=f'''{mode}-{guid_index}''' ,   words=lowercase__ ,   labels=lowercase__     )     )
                                     guid_index += 1
                                     __A    =[]
                                     __A    =[]
                         else:
                               __A    =line.split(''' '''     )
                               words.append(splits[0]     )
                               if len(lowercase__     ) > 1:
                                     labels.append(splits[self.label_idx].replace('''\n''' ,   ''''''     )     )
                               else:
                                     # Examples could have no label for mode = "test"
                                     labels.append('''O'''     )
                   if words:
                         examples.append(InputExample(guid=f'''{mode}-{guid_index}''' ,   words=lowercase__ ,   labels=lowercase__     )     )
             return examples

       def     __UpperCamelCase     (							self ,   lowercase__ ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             __A    =0
             for line in test_input_reader:
                   if line.startswith('''-DOCSTART-'''     ) or line == "" or line == "\n":
                         writer.write(lowercase__     )
                         if not preds_list[example_id]:
                               example_id += 1
                   elif preds_list[example_id]:
                         __A    =line.split()[0] + ''' ''' + preds_list[example_id].pop(0     ) + '''\n'''
                         writer.write(lowercase__     )
                   else:
                         logger.warning('''Maximum sequence length exceeded: No prediction for \'%s\'.''' ,   line.split()[0]     )


       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             if path:
                   with open(lowercase__ ,   '''r'''     ) as f:
                         __A    =f.read().splitlines()
                   if "O" not in labels:
                         __A    =['''O'''] + labels
                   return labels
             else:
                   return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]





class        lowerCAmelCase__  (					__magic_name__			):



       '''simple docstring'''







       def __init__(							self     ):







             '''simple docstring'''



             super().__init__(label_idx=-2     )


       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             if path:
                   with open(lowercase__ ,   '''r'''     ) as f:
                         __A    =f.read().splitlines()
                   if "O" not in labels:
                         __A    =['''O'''] + labels
                   return labels
             else:
                   return [
                       "O",
                       "B-ADVP",
                       "B-INTJ",
                       "B-LST",
                       "B-PRT",
                       "B-NP",
                       "B-SBAR",
                       "B-VP",
                       "B-ADJP",
                       "B-CONJP",
                       "B-PP",
                       "I-ADVP",
                       "I-INTJ",
                       "I-LST",
                       "I-PRT",
                       "I-NP",
                       "I-SBAR",
                       "I-VP",
                       "I-ADJP",
                       "I-CONJP",
                       "I-PP",
                   ]





class        lowerCAmelCase__  (					__magic_name__			):



       '''simple docstring'''







       def     __UpperCamelCase     (							self ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             if isinstance(lowercase__ ,   lowercase__     ):
                   __A    =mode.value
             __A    =os.path.join(lowercase__ ,   f'''{mode}.txt'''     )
             __A    =1
             __A    =[]

             with open(lowercase__ ,   encoding='''utf-8'''     ) as f:
                   for sentence in parse_incr(lowercase__     ):
                         __A    =[]
                         __A    =[]
                         for token in sentence:
                               words.append(token['''form''']     )
                               labels.append(token['''upos''']     )
                         assert len(lowercase__     ) == len(lowercase__     )
                         if words:
                               examples.append(InputExample(guid=f'''{mode}-{guid_index}''' ,   words=lowercase__ ,   labels=lowercase__     )     )
                               guid_index += 1
             return examples

       def     __UpperCamelCase     (							self ,   lowercase__ ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             __A    =0
             for sentence in parse_incr(lowercase__     ):
                   __A    =preds_list[example_id]
                   __A    =''''''
                   for token in sentence:
                         out += f'''{token['form']} ({token['upos']}|{s_p.pop(0     )}) '''
                   out += "\n"
                   writer.write(lowercase__     )
                   example_id += 1


       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             if path:
                   with open(lowercase__ ,   '''r'''     ) as f:
                         return f.read().splitlines()
             else:
                   return [
                       "ADJ",
                       "ADP",
                       "ADV",
                       "AUX",
                       "CCONJ",
                       "DET",
                       "INTJ",
                       "NOUN",
                       "NUM",
                       "PART",
                       "PRON",
                       "PROPN",
                       "PUNCT",
                       "SCONJ",
                       "SYM",
                       "VERB",
                       "X",
                   ]


