




"""simple docstring"""


import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


_A													=      datasets.utils.logging.get_logger(__name__)


@dataclass
class _lowerCamelCase    (					datasets.BuilderConfig						):
   _lowerCamelCase    :Optional[datasets.Features]     				=     None
   _lowerCamelCase    :str     				=     "utf-8"
   _lowerCamelCase    :Optional[str]     				=     None
   _lowerCamelCase    :Optional[str]     				=     None
   _lowerCamelCase    :bool     				=     True  # deprecated
   _lowerCamelCase    :Optional[int]     				=     None  # deprecated
   _lowerCamelCase    :int     				=     10 << 20  # 10MB
   _lowerCamelCase    :Optional[bool]     				=     None






class _lowerCamelCase    (					datasets.ArrowBasedBuilder						):
   _lowerCamelCase    :str     				=     JsonConfig






   def 	_lowerCAmelCase   (		self       :		Tuple   )			->						Tuple:

         """simple docstring"""
         if self.config.block_size is not None:
               logger.warning("""The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead"""   )
               lowerCAmelCase__      :			str   =	self.config.block_size
         if self.config.use_threads is not True:
               logger.warning(
                   """The JSON loader parameter `use_threads` is deprecated and doesn't have any effect anymore."""   )
         if self.config.newlines_in_values is not None:
               raise ValueError("""The JSON loader parameter `newlines_in_values` is no longer supported"""   )
         return datasets.DatasetInfo(features=self.config.features   )






   def 	_lowerCAmelCase   (		self       :		int   ,     UpperCamelCase       :		Optional[Any]   )			->						str:

         """simple docstring"""
         if not self.config.data_files:
               raise ValueError(f"""At least one data file must be specified, but got data_files={self.config.data_files}"""   )
         lowerCAmelCase__      :			Optional[Any]   =	dl_manager.download_and_extract(self.config.data_files   )
         if isinstance(UpperCamelCase   ,     (str, list, tuple)   ):
               lowerCAmelCase__      :			List[Any]   =	data_files
               if isinstance(UpperCamelCase   ,     UpperCamelCase   ):
                     lowerCAmelCase__      :			Optional[Any]   =	[files]
               lowerCAmelCase__      :			Optional[int]   =	[dl_manager.iter_files(UpperCamelCase   ) for file in files]
               return [datasets.SplitGenerator(name=datasets.Split.TRAIN   ,     gen_kwargs={"""files""": files}   )]
         lowerCAmelCase__      :			Dict   =	[]
         for split_name, files in data_files.items():
               if isinstance(UpperCamelCase   ,     UpperCamelCase   ):
                     lowerCAmelCase__      :			int   =	[files]
               lowerCAmelCase__      :			Union[str, Any]   =	[dl_manager.iter_files(UpperCamelCase   ) for file in files]
               splits.append(datasets.SplitGenerator(name=UpperCamelCase   ,     gen_kwargs={"""files""": files}   )   )
         return splits






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		pa.Table   )			->						pa.Table:

         """simple docstring"""
         if self.config.features is not None:
               # adding missing columns
               for column_name in set(self.config.features   ) - set(pa_table.column_names   ):
                     lowerCAmelCase__      :			str   =	self.config.features.arrow_schema.field(UpperCamelCase   ).type
                     lowerCAmelCase__      :			Dict   =	pa_table.append_column(UpperCamelCase   ,     pa.array([None] * len(UpperCamelCase   )   ,     type=UpperCamelCase   )   )
               # more expensive cast to support nested structures with keys in a different order
               # allows str <-> int/float or str to Audio for example
               lowerCAmelCase__      :			Any   =	table_cast(UpperCamelCase   ,     self.config.features.arrow_schema   )
         return pa_table






   def 	_lowerCAmelCase   (		self       :		Tuple   ,     UpperCamelCase       :		Tuple   )			->						Tuple:

         """simple docstring"""
         for file_idx, file in enumerate(itertools.chain.from_iterable(UpperCamelCase   )   ):
               # If the file is one json object and if we need to look at the list of items in one specific field
               if self.config.field is not None:
                     with open(UpperCamelCase   ,     encoding=self.config.encoding   ,     errors=self.config.encoding_errors   ) as f:
                           lowerCAmelCase__      :			List[Any]   =	json.load(UpperCamelCase   )

                     # We keep only the field we are interested in
                     lowerCAmelCase__      :			str   =	dataset[self.config.field]

                     # We accept two format: a list of dicts or a dict of lists
                     if isinstance(UpperCamelCase   ,     (list, tuple)   ):
                           lowerCAmelCase__      :			Tuple   =	set().union(*[row.keys() for row in dataset]   )
                           lowerCAmelCase__      :			str   =	{col: [row.get(UpperCamelCase   ) for row in dataset] for col in keys}
                     else:
                           lowerCAmelCase__      :			List[str]   =	dataset
                     lowerCAmelCase__      :			str   =	pa.Table.from_pydict(UpperCamelCase   )
                     yield file_idx, self._cast_table(UpperCamelCase   )

               # If the file has one json object per line
               else:
                     with open(UpperCamelCase   ,     """rb"""   ) as f:
                           lowerCAmelCase__      :			Dict   =	0
                           # Use block_size equal to the chunk size divided by 32 to leverage multithreading
                           # Set a default minimum value of 16kB if the chunk size is really small
                           lowerCAmelCase__      :			str   =	max(self.config.chunksize // 32   ,     16 << 10   )
                           lowerCAmelCase__      :			Any   =	(
                               self.config.encoding_errors if self.config.encoding_errors is not None else """strict"""
                           )
                           while True:
                                 lowerCAmelCase__      :			Union[str, Any]   =	f.read(self.config.chunksize   )
                                 if not batch:
                                       break
                                 # Finish current line
                                 try:
                                       batch += f.readline()
                                 except (AttributeError, io.UnsupportedOperation):
                                       batch += readline(UpperCamelCase   )
                                 # PyArrow only accepts utf-8 encoded bytes
                                 if self.config.encoding != "utf-8":
                                       lowerCAmelCase__      :			Tuple   =	batch.decode(self.config.encoding   ,     errors=UpperCamelCase   ).encode("""utf-8"""   )
                                 try:
                                       while True:
                                             try:
                                                   lowerCAmelCase__      :			Optional[Any]   =	paj.read_json(
                                                       io.BytesIO(UpperCamelCase   )   ,     read_options=paj.ReadOptions(block_size=UpperCamelCase   )   )
                                                   break
                                             except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
                                                   if (
                                                       isinstance(UpperCamelCase   ,     pa.ArrowInvalid   )
                                                       and "straddling" not in str(UpperCamelCase   )
                                                       or block_size > len(UpperCamelCase   )
                                                   ):
                                                         raise
                                                   else:
                                                         # Increase the block size in case it was too small.
                                                         # The block size will be reset for the next file.
                                                         logger.debug(
                                                             f"""Batch of {len(UpperCamelCase   )} bytes couldn't be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}."""   )
                                                         block_size *= 2
                                 except pa.ArrowInvalid as e:
                                       try:
                                             with open(
                                                 UpperCamelCase   ,     encoding=self.config.encoding   ,     errors=self.config.encoding_errors   ) as f:
                                                   lowerCAmelCase__      :			Dict   =	json.load(UpperCamelCase   )
                                       except json.JSONDecodeError:
                                             logger.error(f"""Failed to read file '{file}' with error {type(UpperCamelCase   )}: {e}"""   )
                                             raise e
                                       # If possible, parse the file as a list of json objects and exit the loop
                                       if isinstance(UpperCamelCase   ,     UpperCamelCase   ):  # list is the only sequence type supported in JSON
                                             try:
                                                   lowerCAmelCase__      :			List[str]   =	set().union(*[row.keys() for row in dataset]   )
                                                   lowerCAmelCase__      :			Union[str, Any]   =	{col: [row.get(UpperCamelCase   ) for row in dataset] for col in keys}
                                                   lowerCAmelCase__      :			Union[str, Any]   =	pa.Table.from_pydict(UpperCamelCase   )
                                             except (pa.ArrowInvalid, AttributeError) as e:
                                                   logger.error(f"""Failed to read file '{file}' with error {type(UpperCamelCase   )}: {e}"""   )
                                                   raise ValueError(f"""Not able to read records in the JSON file at {file}."""   ) from None
                                             yield file_idx, self._cast_table(UpperCamelCase   )
                                             break
                                       else:
                                             logger.error(f"""Failed to read file '{file}' with error {type(UpperCamelCase   )}: {e}"""   )
                                             raise ValueError(
                                                 f"""Not able to read records in the JSON file at {file}. """
                                                 f"""You should probably indicate the field of the JSON file containing your records. """
                                                 f"""This JSON file contain the following fields: {str(list(dataset.keys()   )   )}. """
                                                 f"""Select the correct one and provide it as `field='XXX'` to the dataset loading method. """   ) from None
                        # Uncomment for debugging (will print the Arrow table size and elements)
                        # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                        # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                                 yield (file_idx, batch_idx), self._cast_table(UpperCamelCase   )
                                 batch_idx += 1











"""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													=      logging.getLogger(__name__)


class _lowerCamelCase    (					a_						):






   def __init__(		self       :		List[Any]   ,     UpperCamelCase       :		Dict=-1   )			->						List[Any]:

         """simple docstring"""
         # in NER datasets, the last column is usually reserved for NER label
         lowerCAmelCase__      :			Optional[int]   =	label_idx






   def 	_lowerCAmelCase   (		self       :		Optional[int]   ,     UpperCamelCase       :		Optional[int]   ,     UpperCamelCase       :		Union[Split, str]   )			->						List[InputExample]:

         """simple docstring"""
         if isinstance(UpperCamelCase   ,     UpperCamelCase   ):
               lowerCAmelCase__      :			int   =	mode.value
         lowerCAmelCase__      :			Dict   =	os.path.join(UpperCamelCase   ,     f"""{mode}.txt"""   )
         lowerCAmelCase__      :			str   =	1
         lowerCAmelCase__      :			List[Any]   =	[]
         with open(UpperCamelCase   ,     encoding="""utf-8"""   ) as f:
               lowerCAmelCase__      :			str   =	[]
               lowerCAmelCase__      :			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=UpperCamelCase   ,     labels=UpperCamelCase   )   )
                                 guid_index += 1
                                 lowerCAmelCase__      :			Optional[Any]   =	[]
                                 lowerCAmelCase__      :			Tuple   =	[]
                     else:
                           lowerCAmelCase__      :			Optional[int]   =	line.split(""" """   )
                           words.append(splits[0]   )
                           if len(UpperCamelCase   ) > 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=UpperCamelCase   ,     labels=UpperCamelCase   )   )
         return examples






   def 	_lowerCAmelCase   (		self       :		Any   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		List   )			->						List[Any]:

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






   def 	_lowerCAmelCase   (		self       :		str   ,     UpperCamelCase       :		str   )			->						List[str]:

         """simple docstring"""
         if path:
               with open(UpperCamelCase   ,     """r"""   ) as f:
                     lowerCAmelCase__      :			Any   =	f.read().splitlines()
               if "O" not in labels:
                     lowerCAmelCase__      :			List[str]   =	["""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    (					a_						):






   def __init__(		self       :		Union[str, Any]   )			->						Any:

         """simple docstring"""
         # in CONLL2003 dataset chunk column is second-to-last
         super().__init__(label_idx=-2   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   ,     UpperCamelCase       :		str   )			->						List[str]:

         """simple docstring"""
         if path:
               with open(UpperCamelCase   ,     """r"""   ) as f:
                     lowerCAmelCase__      :			Any   =	f.read().splitlines()
               if "O" not in labels:
                     lowerCAmelCase__      :			str   =	["""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    (					a_						):






   def 	_lowerCAmelCase   (		self       :		Union[str, Any]   ,     UpperCamelCase       :		Any   ,     UpperCamelCase       :		Union[Split, str]   )			->						List[InputExample]:

         """simple docstring"""
         if isinstance(UpperCamelCase   ,     UpperCamelCase   ):
               lowerCAmelCase__      :			Optional[Any]   =	mode.value
         lowerCAmelCase__      :			int   =	os.path.join(UpperCamelCase   ,     f"""{mode}.txt"""   )
         lowerCAmelCase__      :			Optional[int]   =	1
         lowerCAmelCase__      :			List[Any]   =	[]

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






   def 	_lowerCAmelCase   (		self       :		List[str]   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		TextIO   ,     UpperCamelCase       :		List   )			->						List[Any]:

         """simple docstring"""
         lowerCAmelCase__      :			Any   =	0
         for sentence in parse_incr(UpperCamelCase   ):
               lowerCAmelCase__      :			Union[str, Any]   =	preds_list[example_id]
               lowerCAmelCase__      :			List[Any]   =	""""""
               for token in sentence:
                     out += f"""{token['form']} ({token['upos']}|{s_p.pop(0   )}) """
               out += "\n"
               writer.write(UpperCamelCase   )
               example_id += 1






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		str   )			->						List[str]:

         """simple docstring"""
         if path:
               with open(UpperCamelCase   ,     """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",
               ]





