





'''simple docstring'''






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

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


A_		:  List[str]		 =						logging.getLogger(__name__)
class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   def __init__(							self	,		__SCREAMING_SNAKE_CASE=-1       ):
    # in NER datasets, the last column is usually reserved for NER label
    snake_case__     :					List[str]    =  label_idx

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    if isinstance(__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
     snake_case__     :					Any    =  mode.value
    snake_case__     :					List[str]    =  os.path.join(__SCREAMING_SNAKE_CASE	,		f"{mode}.txt"       )
    snake_case__     :					List[str]    =  1
    snake_case__     :					str    =  []
    with open(__SCREAMING_SNAKE_CASE	,		encoding="""utf-8"""       ) as f:
     snake_case__     :					Any    =  []
     snake_case__     :					Optional[Any]    =  []
     for line in f:
      if line.startswith("""-DOCSTART-"""       ) or line == "" or line == "\n":
       if words:
        examples.append(InputExample(guid=f"{mode}-{guid_index}"	,		words=__SCREAMING_SNAKE_CASE	,		labels=__SCREAMING_SNAKE_CASE       )       )
        guid_index += 1
        snake_case__     :					Any    =  []
        snake_case__     :					int    =  []
      else:
       snake_case__     :					Any    =  line.split(""" """       )
       words.append(splits[0]       )
       if len(__SCREAMING_SNAKE_CASE       ) > 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=__SCREAMING_SNAKE_CASE	,		labels=__SCREAMING_SNAKE_CASE       )       )
    return examples

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


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    if path:
     with open(__SCREAMING_SNAKE_CASE	,		"""r"""       ) as f:
      snake_case__     :					List[Any]    =  f.read().splitlines()
     if "O" not in labels:
      snake_case__     :					Any    =  ["""O"""] + labels
     return labels
    else:
     return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   def __init__(							self       ):
    # in CONLL2003 dataset chunk column is second-to-last
    super().__init__(label_idx=-2       )


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    if path:
     with open(__SCREAMING_SNAKE_CASE	,		"""r"""       ) as f:
      snake_case__     :					Optional[int]    =  f.read().splitlines()
     if "O" not in labels:
      snake_case__     :					List[Any]    =  ["""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 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    if isinstance(__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
     snake_case__     :					Optional[Any]    =  mode.value
    snake_case__     :					int    =  os.path.join(__SCREAMING_SNAKE_CASE	,		f"{mode}.txt"       )
    snake_case__     :					Union[str, Any]    =  1
    snake_case__     :					Any    =  []

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

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__     :					Tuple    =  0
    for sentence in parse_incr(__SCREAMING_SNAKE_CASE       ):
     snake_case__     :					int    =  preds_list[example_id]
     snake_case__     :					Any    =  """"""
     for token in sentence:
      out += f"{token['form']} ({token['upos']}|{s_p.pop(0       )}) "
     out += "\n"
     writer.write(__SCREAMING_SNAKE_CASE       )
     example_id += 1


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    if path:
     with open(__SCREAMING_SNAKE_CASE	,		"""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",
     ]







"""simple docstring"""




import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin





class  lowerCamelCase    (A__      ,unittest.TestCase      ):
			lowerCamelCase__ :		List[str]       		=				PhobertTokenizer
			lowerCamelCase__ :		Union[str, Any]       		=				False

			def        SCREAMING_SNAKE_CASE					(       self					:    int							) ->     Any:
						super().setUp()

						# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
						SCREAMING_SNAKE_CASE__										=   ["""T@@""", """i""", """I""", """R@@""", """r""", """e@@"""]
						SCREAMING_SNAKE_CASE__										=   dict(zip(__UpperCAmelCase     ,					range(len(__UpperCAmelCase							)							)							)							)
						SCREAMING_SNAKE_CASE__										=   ["""#version: 0.2""", """l à</w>"""]
						SCREAMING_SNAKE_CASE__										=   {"""unk_token""": """<unk>"""}

						SCREAMING_SNAKE_CASE__										=   os.path.join(self.tmpdirname     ,					VOCAB_FILES_NAMES["""vocab_file"""]							)
						SCREAMING_SNAKE_CASE__										=   os.path.join(self.tmpdirname     ,					VOCAB_FILES_NAMES["""merges_file"""]							)

						with open(self.vocab_file     ,					"""w"""     ,					encoding="""utf-8"""							) as fp:
									for token in vocab_tokens:
												fp.write(F"""{token} {vocab_tokens[token]}\n"""							)
						with open(self.merges_file     ,					"""w"""     ,					encoding="""utf-8"""							) as fp:
									fp.write("""\n""".join(__UpperCAmelCase							)							)

			def        SCREAMING_SNAKE_CASE					(       self					:    List[Any]     ,					**__UpperCAmelCase					:    int							) ->     Optional[int]:
						kwargs.update(self.special_tokens_map							)
						return PhobertTokenizer.from_pretrained(self.tmpdirname     ,					**__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Dict     ,					__UpperCAmelCase					:    int							) ->     Optional[Any]:
						SCREAMING_SNAKE_CASE__										=   """Tôi là VinAI Research"""
						SCREAMING_SNAKE_CASE__										=   """T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
						return input_text, output_text





			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[int]							) ->     int:
						SCREAMING_SNAKE_CASE__										=   PhobertTokenizer(self.vocab_file     ,					self.merges_file     ,					**self.special_tokens_map							)
						SCREAMING_SNAKE_CASE__										=   """Tôi là VinAI Research"""
						SCREAMING_SNAKE_CASE__										=   """T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h""".split()
						SCREAMING_SNAKE_CASE__										=   tokenizer.tokenize(__UpperCAmelCase							)
						print(__UpperCAmelCase							)
						self.assertListEqual(__UpperCAmelCase     ,					__UpperCAmelCase							)

						SCREAMING_SNAKE_CASE__										=   tokens + [tokenizer.unk_token]

						SCREAMING_SNAKE_CASE__										=   [4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase							)     ,					__UpperCAmelCase							)


