import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil




class   lowercase_    (    __snake_case		):



	"""simple docstring"""





	def      SCREAMING_SNAKE_CASE_							(				self							)		->str:
								lowerCAmelCase      						=						pa.array(TypedSequence([1, 2, 3]							)							)
								self.assertEqual(arr.type						,     pa.intaa()							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Optional[int]:







								with self.assertRaises(__lowerCamelCase							):
															lowerCAmelCase      						=						pa.array(TypedSequence([1, 2, 3]							)						,     type=pa.intaa()							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Any:







								with self.assertRaises(__lowerCamelCase							):
															lowerCAmelCase      						=						pa.array(TypedSequence([1, 2, 3]						,     try_type=Value('''bool'''							)						,     type=Value('''int64'''							)							)							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Tuple:
								lowerCAmelCase      						=						pa.array(TypedSequence([1, 2, 3]						,     type=Value('''int32'''							)							)							)
								self.assertEqual(arr.type						,     pa.intaa()							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->str:







								with self.assertRaises((TypeError, pa.lib.ArrowInvalid)							):
															lowerCAmelCase      						=						pa.array(TypedSequence(['''foo''', '''bar''']						,     type=Value('''int64'''							)							)							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->List[Any]:
								lowerCAmelCase      						=						pa.array(TypedSequence([1, 2, 3]						,     try_type=Value('''int32'''							)							)							)
								self.assertEqual(arr.type						,     pa.intaa()							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->str:
								lowerCAmelCase      						=						pa.array(TypedSequence(['''foo''', '''bar''']						,     try_type=Value('''int64'''							)							)							)
								self.assertEqual(arr.type						,     pa.string()							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->List[str]:
								lowerCAmelCase      						=						pa.array(TypedSequence([[[1, 2, 3]]]						,     type=ArrayaD((1, 3)						,     '''int64'''							)							)							)
								self.assertEqual(arr.type						,     ArrayaDExtensionType((1, 3)						,     '''int64'''							)							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->int:







								with self.assertRaises((TypeError, pa.lib.ArrowInvalid)							):
															lowerCAmelCase      						=						pa.array(TypedSequence(['''foo''', '''bar''']						,     type=ArrayaD((1, 3)						,     '''int64'''							)							)							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Dict:
								lowerCAmelCase      						=						pa.array(TypedSequence([[[1, 2, 3]]]						,     try_type=ArrayaD((1, 3)						,     '''int64'''							)							)							)
								self.assertEqual(arr.type						,     ArrayaDExtensionType((1, 3)						,     '''int64'''							)							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Union[str, Any]:
								lowerCAmelCase      						=						pa.array(TypedSequence(['''foo''', '''bar''']						,     try_type=ArrayaD((1, 3)						,     '''int64'''							)							)							)
								self.assertEqual(arr.type						,     pa.string()							)




	@require_pil
	def      SCREAMING_SNAKE_CASE_							(				self							)		->Tuple:
								import PIL.Image

								lowerCAmelCase      						=						PIL.Image.fromarray(np.arange(10						,     dtype=np.uinta							).reshape(2						,     5							)							)
								with patch(
								    '''datasets.arrow_writer.cast_to_python_objects'''						,     side_effect=__lowerCamelCase							) as mock_cast_to_python_objects:
															lowerCAmelCase      						=						pa.array(TypedSequence([{'''path''': None, '''bytes''': b'''image_bytes'''}, pil_image]						,     type=Image()							)							)
															lowerCAmelCase						, lowerCAmelCase      						=						mock_cast_to_python_objects.call_args_list[-1]
															self.assertIn('''optimize_list_casting'''						,     __lowerCamelCase							)
															self.assertFalse(kwargs['''optimize_list_casting''']							)

def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      List[Any]:
							lowerCAmelCase      						=						pa.BufferReader(lowerCAmelCase_				) if isinstance(lowerCAmelCase_  ,    pa.Buffer				) else pa.memory_map(lowerCAmelCase_				)
							lowerCAmelCase      						=						pa.ipc.open_stream(lowerCAmelCase_				)
							lowerCAmelCase      						=						f.read_all()
							assert len(pa_table.to_batches()				) == expected_num_chunks
							assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
							del pa_table

@pytest.mark.parametrize('''writer_batch_size'''  ,    [None, 1, 1_0]				)
@pytest.mark.parametrize(
    '''fields'''  ,    [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      int:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							lowerCAmelCase      						=						pa.schema(lowerCAmelCase_				) if fields else None
							with ArrowWriter(stream=lowerCAmelCase_  ,    schema=lowerCAmelCase_  ,    writer_batch_size=lowerCAmelCase_				) as writer:
														writer.write({'''col_1''': '''foo''', '''col_2''': 1}				)
														writer.write({'''col_1''': '''bar''', '''col_2''': 2}				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							if not fields:
														lowerCAmelCase      						=						{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
							assert writer._schema == pa.schema(lowerCAmelCase_  ,    metadata=writer._schema.metadata				)
							_check_output(output.getvalue()  ,    expected_num_chunks=num_examples if writer_batch_size == 1 else 1				)

def   SCREAMING_SNAKE_CASE_	(		)	->      Any:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							lowerCAmelCase      						=						Features({'''labels''': ClassLabel(names=['''neg''', '''pos''']				)}				)
							with ArrowWriter(stream=lowerCAmelCase_  ,    features=lowerCAmelCase_				) as writer:
														writer.write({'''labels''': 0}				)
														writer.write({'''labels''': 1}				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							assert writer._schema == features.arrow_schema
							assert writer._schema.metadata == features.arrow_schema.metadata
							lowerCAmelCase      						=						pa.BufferReader(output.getvalue()				)
							lowerCAmelCase      						=						pa.ipc.open_stream(lowerCAmelCase_				)
							lowerCAmelCase      						=						f.read_all()
							lowerCAmelCase      						=						pa_table.schema
							assert pa_table.num_rows == 2
							assert schema == features.arrow_schema
							assert schema.metadata == features.arrow_schema.metadata
							assert features == Features.from_arrow_schema(lowerCAmelCase_				)

@pytest.mark.parametrize('''writer_batch_size'''  ,    [None, 1, 1_0]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__				)	->      Union[str, Any]:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							with ArrowWriter(
							    stream=lowerCAmelCase_  ,    writer_batch_size=lowerCAmelCase_  ,    hash_salt='''split_name'''  ,    check_duplicates=lowerCAmelCase_  ,    ) as writer:
														with pytest.raises(lowerCAmelCase_				):
																					writer.write({'''col_1''': '''foo''', '''col_2''': 1}  ,    key=[1, 2]				)
																					lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()

@pytest.mark.parametrize('''writer_batch_size'''  ,    [None, 2, 1_0]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__				)	->      List[str]:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							with ArrowWriter(
							    stream=lowerCAmelCase_  ,    writer_batch_size=lowerCAmelCase_  ,    hash_salt='''split_name'''  ,    check_duplicates=lowerCAmelCase_  ,    ) as writer:
														with pytest.raises(lowerCAmelCase_				):
																					writer.write({'''col_1''': '''foo''', '''col_2''': 1}  ,    key=1_0				)
																					writer.write({'''col_1''': '''bar''', '''col_2''': 2}  ,    key=1_0				)
																					lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()

@pytest.mark.parametrize('''writer_batch_size'''  ,    [None, 2, 1_0]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__				)	->      Dict:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							with ArrowWriter(
							    stream=lowerCAmelCase_  ,    writer_batch_size=lowerCAmelCase_  ,    hash_salt='''split_name'''  ,    check_duplicates=lowerCAmelCase_  ,    ) as writer:
														writer.write({'''col_1''': '''foo''', '''col_2''': 1}  ,    key=1				)
														writer.write({'''col_1''': '''bar''', '''col_2''': 2}  ,    key=2				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							_check_output(output.getvalue()  ,    expected_num_chunks=num_examples if writer_batch_size == 1 else 1				)

@pytest.mark.parametrize('''writer_batch_size'''  ,    [None, 1, 1_0]				)
@pytest.mark.parametrize(
    '''fields'''  ,    [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      str:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							lowerCAmelCase      						=						pa.schema(lowerCAmelCase_				) if fields else None
							with ArrowWriter(stream=lowerCAmelCase_  ,    schema=lowerCAmelCase_  ,    writer_batch_size=lowerCAmelCase_				) as writer:
														writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}				)
														writer.write_batch({'''col_1''': [], '''col_2''': []}				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							if not fields:
														lowerCAmelCase      						=						{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
							assert writer._schema == pa.schema(lowerCAmelCase_  ,    metadata=writer._schema.metadata				)
							_check_output(output.getvalue()  ,    expected_num_chunks=num_examples if writer_batch_size == 1 else 1				)

@pytest.mark.parametrize('''writer_batch_size'''  ,    [None, 1, 1_0]				)
@pytest.mark.parametrize(
    '''fields'''  ,    [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      Dict:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							lowerCAmelCase      						=						pa.schema(lowerCAmelCase_				) if fields else None
							with ArrowWriter(stream=lowerCAmelCase_  ,    schema=lowerCAmelCase_  ,    writer_batch_size=lowerCAmelCase_				) as writer:
														writer.write_table(pa.Table.from_pydict({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}				)				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							if not fields:
														lowerCAmelCase      						=						{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
							assert writer._schema == pa.schema(lowerCAmelCase_  ,    metadata=writer._schema.metadata				)
							_check_output(output.getvalue()  ,    expected_num_chunks=num_examples if writer_batch_size == 1 else 1				)

@pytest.mark.parametrize('''writer_batch_size'''  ,    [None, 1, 1_0]				)
@pytest.mark.parametrize(
    '''fields'''  ,    [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      int:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							lowerCAmelCase      						=						pa.schema(lowerCAmelCase_				) if fields else None
							with ArrowWriter(stream=lowerCAmelCase_  ,    schema=lowerCAmelCase_  ,    writer_batch_size=lowerCAmelCase_				) as writer:
														writer.write_row(pa.Table.from_pydict({'''col_1''': ['''foo'''], '''col_2''': [1]}				)				)
														writer.write_row(pa.Table.from_pydict({'''col_1''': ['''bar'''], '''col_2''': [2]}				)				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							if not fields:
														lowerCAmelCase      						=						{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
							assert writer._schema == pa.schema(lowerCAmelCase_  ,    metadata=writer._schema.metadata				)
							_check_output(output.getvalue()  ,    expected_num_chunks=num_examples if writer_batch_size == 1 else 1				)

def   SCREAMING_SNAKE_CASE_	(		)	->      Union[str, Any]:
							with tempfile.TemporaryDirectory() as tmp_dir:
														lowerCAmelCase      						=						{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
														lowerCAmelCase      						=						os.path.join(lowerCAmelCase_  ,    '''test.arrow'''				)
														with ArrowWriter(path=lowerCAmelCase_  ,    schema=pa.schema(lowerCAmelCase_				)				) as writer:
																					writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}				)
																					lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
														assert num_examples == 2
														assert num_bytes > 0
														assert writer._schema == pa.schema(lowerCAmelCase_  ,    metadata=writer._schema.metadata				)
														_check_output(lowerCAmelCase_  ,    1				)

def   SCREAMING_SNAKE_CASE_	(		snake_case__				)	->      str:
							if pa.types.is_list(lowerCAmelCase_				):
														return get_base_dtype(arr_type.value_type				)
							else:
														return arr_type

def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      int:
							if isinstance(lst[0]  ,    lowerCAmelCase_				):
														change_first_primitive_element_in_list(lst[0]  ,    lowerCAmelCase_				)
							else:
														lowerCAmelCase      						=						value

@pytest.mark.parametrize('''optimized_int_type, expected_dtype'''  ,    [(None, pa.intaa()), (Value('''int32'''				), pa.intaa())]				)
@pytest.mark.parametrize('''sequence'''  ,    [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__  ,    snake_case__				)	->      List[str]:
							lowerCAmelCase      						=						pa.array(TypedSequence(lowerCAmelCase_  ,    optimized_int_type=lowerCAmelCase_				)				)
							assert get_base_dtype(arr.type				) == expected_dtype

@pytest.mark.parametrize(
    '''col, expected_dtype'''  ,    [
        ('''attention_mask''', pa.inta()),
        ('''special_tokens_mask''', pa.inta()),
        ('''token_type_ids''', pa.inta()),
        ('''input_ids''', pa.intaa()),
        ('''other''', pa.intaa()),
    ]  ,    )
@pytest.mark.parametrize('''sequence'''  ,    [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__  ,    snake_case__				)	->      str:
							# in range
							lowerCAmelCase      						=						pa.array(OptimizedTypedSequence(lowerCAmelCase_  ,    col=lowerCAmelCase_				)				)
							assert get_base_dtype(arr.type				) == expected_dtype

							# not in range
							if col != "other":
														# avoids errors due to in-place modifications
														lowerCAmelCase      						=						copy.deepcopy(lowerCAmelCase_				)
														lowerCAmelCase      						=						np.iinfo(expected_dtype.to_pandas_dtype()				).max + 1
														change_first_primitive_element_in_list(lowerCAmelCase_  ,    lowerCAmelCase_				)
														lowerCAmelCase      						=						pa.array(OptimizedTypedSequence(lowerCAmelCase_  ,    col=lowerCAmelCase_				)				)
														assert get_base_dtype(arr.type				) == pa.intaa()

@pytest.mark.parametrize('''raise_exception'''  ,    [False, True]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      Optional[Any]:
							lowerCAmelCase      						=						str(tmp_path / '''dataset-train.arrow'''				)
							try:
														with ArrowWriter(path=lowerCAmelCase_				) as writer:
																					if raise_exception:
																												raise pa.lib.ArrowInvalid()
																					else:
																												writer.stream.close()
							except pa.lib.ArrowInvalid:
														pass
							finally:
														assert writer.stream.closed

def   SCREAMING_SNAKE_CASE_	(		snake_case__				)	->      Dict:
							lowerCAmelCase      						=						'''mock://dataset-train.arrow'''
							with ArrowWriter(path=lowerCAmelCase_  ,    storage_options=mockfs.storage_options				) as writer:
														assert isinstance(writer._fs  ,    type(lowerCAmelCase_				)				)
														assert writer._fs.storage_options == mockfs.storage_options
														writer.write({'''col_1''': '''foo''', '''col_2''': 1}				)
														writer.write({'''col_1''': '''bar''', '''col_2''': 2}				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							assert mockfs.exists(lowerCAmelCase_				)

def   SCREAMING_SNAKE_CASE_	(		)	->      List[str]:
							lowerCAmelCase      						=						pa.BufferOutputStream()
							with ParquetWriter(stream=lowerCAmelCase_				) as writer:
														writer.write({'''col_1''': '''foo''', '''col_2''': 1}				)
														writer.write({'''col_1''': '''bar''', '''col_2''': 2}				)
														lowerCAmelCase						, lowerCAmelCase      						=						writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							lowerCAmelCase      						=						pa.BufferReader(output.getvalue()				)
							lowerCAmelCase      						=						pq.read_table(lowerCAmelCase_				)
							assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}

@require_pil
@pytest.mark.parametrize('''embed_local_files'''  ,    [False, True]				)
def   SCREAMING_SNAKE_CASE_	(		snake_case__  ,    snake_case__				)	->      Any:
							import PIL.Image

							lowerCAmelCase      						=						str(tmp_path / '''test_image_rgb.jpg'''				)
							PIL.Image.fromarray(np.zeros((5, 5)  ,    dtype=np.uinta				)				).save(lowerCAmelCase_  ,    format='''png'''				)
							lowerCAmelCase      						=						pa.BufferOutputStream()
							with ParquetWriter(
							    stream=lowerCAmelCase_  ,    features=Features({'''image''': Image()}				)  ,    embed_local_files=lowerCAmelCase_				) as writer:
														writer.write({'''image''': image_path}				)
														writer.finalize()
							lowerCAmelCase      						=						pa.BufferReader(output.getvalue()				)
							lowerCAmelCase      						=						pq.read_table(lowerCAmelCase_				)
							lowerCAmelCase      						=						pa_table.to_pydict()
							if embed_local_files:
														assert isinstance(out['''image'''][0]['''path''']  ,    lowerCAmelCase_				)
														with open(lowerCAmelCase_  ,    '''rb'''				) as f:
																					assert out["image"][0]["bytes"] == f.read()
							else:
														assert out["image"][0]["path"] == image_path
														assert out["image"][0]["bytes"] is None






def   SCREAMING_SNAKE_CASE_	(		)	->      Dict:
							lowerCAmelCase      						=						pa.schema([pa.field('''col_1'''  ,    pa.string()  ,    nullable=lowerCAmelCase_				)]				)
							lowerCAmelCase      						=						pa.BufferOutputStream()
							with ArrowWriter(stream=lowerCAmelCase_				) as writer:
														writer._build_writer(inferred_schema=lowerCAmelCase_				)
														assert writer._schema == pa.schema([pa.field('''col_1'''  ,    pa.string()				)]				)







import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->Optional[Any]:
   # This defines a "chinese character" as anything in the CJK Unicode block:
   #   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
   #
   # Note that the CJK Unicode block is NOT all Japanese and Korean characters,
   # despite its name. The modern Korean Hangul alphabet is a different block,
   # as is Japanese Hiragana and Katakana. Those alphabets are used to write
   # space-separated words, so they are not treated specially and handled
   # like the all of the other languages.
   if (
       (cp >= 0x4_E_0_0 and cp <= 0x9_F_F_F)
       or (cp >= 0x3_4_0_0 and cp <= 0x4_D_B_F)  #
       or (cp >= 0x2_0_0_0_0 and cp <= 0x2_A_6_D_F)  #
       or (cp >= 0x2_A_7_0_0 and cp <= 0x2_B_7_3_F)  #
       or (cp >= 0x2_B_7_4_0 and cp <= 0x2_B_8_1_F)  #
       or (cp >= 0x2_B_8_2_0 and cp <= 0x2_C_E_A_F)  #
       or (cp >= 0xF_9_0_0 and cp <= 0xF_A_F_F)
       or (cp >= 0x2_F_8_0_0 and cp <= 0x2_F_A_1_F)  #
   ):  #
      return True

   return False
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->List[str]:
   # word like '180' or '身高' or '神'
   for char in word:
      UpperCAmelCase      					=  ord(lowerCAmelCase_ )
      if not _is_chinese_char(lowerCAmelCase_ ):
         return 0
   return 1
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->Optional[int]:
   UpperCAmelCase      					=  set()

   for token in tokens:
      UpperCAmelCase      					=  len(lowerCAmelCase_ ) > 1 and is_chinese(lowerCAmelCase_ )
      if chinese_word:
         word_set.add(lowerCAmelCase_ )
   UpperCAmelCase      					=  list(lowerCAmelCase_ )
   return word_list
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_ )    ->Union[str, Any]:
   if not chinese_word_set:
      return bert_tokens
   UpperCAmelCase      					=  max([len(lowerCAmelCase_ ) for w in chinese_word_set] )

   UpperCAmelCase      					=  bert_tokens
   UpperCAmelCase					,	UpperCAmelCase      					=  0, len(lowerCAmelCase_ )
   while start < end:
      UpperCAmelCase      					=  True
      if is_chinese(bert_word[start] ):
         UpperCAmelCase      					=  min(end - start	,    lowerCAmelCase_ )
         for i in range(lowerCAmelCase_	,    1	,    -1 ):
            UpperCAmelCase      					=  """""".join(bert_word[start : start + i] )
            if whole_word in chinese_word_set:
               for j in range(start + 1	,    start + i ):
                  UpperCAmelCase      					=  """##""" + bert_word[j]
               UpperCAmelCase      					=  start + i
               UpperCAmelCase      					=  False
               break
      if single_word:
         start += 1
   return bert_word
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_	,    lowerCAmelCase_ )    ->Dict:
   UpperCAmelCase      					=  []

   for i in range(0	,    len(lowerCAmelCase_ )	,    1_0_0 ):
      UpperCAmelCase      					=  ltp_tokenizer.pipeline(lines[i : i + 1_0_0]	,    tasks=["""cws"""] ).cws
      UpperCAmelCase      					=  [get_chinese_word(lowerCAmelCase_ ) for r in res]
      ltp_res.extend(lowerCAmelCase_ )
   assert len(lowerCAmelCase_ ) == len(lowerCAmelCase_ )

   UpperCAmelCase      					=  []
   for i in range(0	,    len(lowerCAmelCase_ )	,    1_0_0 ):
      UpperCAmelCase      					=  bert_tokenizer(lines[i : i + 1_0_0]	,    add_special_tokens=lowerCAmelCase_	,    truncation=lowerCAmelCase_	,    max_length=5_1_2 )
      bert_res.extend(res["""input_ids"""] )
   assert len(lowerCAmelCase_ ) == len(lowerCAmelCase_ )

   UpperCAmelCase      					=  []
   for input_ids, chinese_word in zip(lowerCAmelCase_	,    lowerCAmelCase_ ):
      UpperCAmelCase      					=  []
      for id in input_ids:
         UpperCAmelCase      					=  bert_tokenizer._convert_id_to_token(lowerCAmelCase_ )
         input_tokens.append(lowerCAmelCase_ )
      UpperCAmelCase      					=  add_sub_symbol(lowerCAmelCase_	,    lowerCAmelCase_ )
      UpperCAmelCase      					=  []
      # We only save pos of chinese subwords start with ##, which mean is part of a whole word.
      for i, token in enumerate(lowerCAmelCase_ ):
         if token[:2] == "##":
            UpperCAmelCase      					=  token[2:]
            # save chinese tokens' pos
            if len(lowerCAmelCase_ ) == 1 and _is_chinese_char(ord(lowerCAmelCase_ ) ):
               ref_id.append(lowerCAmelCase_ )
      ref_ids.append(lowerCAmelCase_ )

   assert len(lowerCAmelCase_ ) == len(lowerCAmelCase_ )

   return ref_ids
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   # For Chinese (Ro)Bert, the best result is from : RoBERTa-wwm-ext (https://github.com/ymcui/Chinese-BERT-wwm)
   # If we want to fine-tune these model, we have to use same tokenizer : LTP (https://github.com/HIT-SCIR/ltp)
   with open(args.file_name	,    """r"""	,    encoding="""utf-8""" ) as f:
      UpperCAmelCase      					=  f.readlines()
   UpperCAmelCase      					=  [line.strip() for line in data if len(lowerCAmelCase_ ) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
   UpperCAmelCase      					=  LTP(args.ltp )  # faster in GPU device
   UpperCAmelCase      					=  BertTokenizer.from_pretrained(args.bert )

   UpperCAmelCase      					=  prepare_ref(lowerCAmelCase_	,    lowerCAmelCase_	,    lowerCAmelCase_ )

   with open(args.save_path	,    """w"""	,    encoding="""utf-8""" ) as f:
      UpperCAmelCase      					=  [json.dumps(lowerCAmelCase_ ) + """\n""" for ref in ref_ids]
      f.writelines(lowerCAmelCase_ )


if __name__ == "__main__":
 __a	 =      argparse.ArgumentParser(description="""prepare_chinese_ref""")
 parser.add_argument(
     """--file_name""",
     required=False,
     type=str,
     default="""./resources/chinese-demo.txt""",
     help="""file need process, same as training data in lm""",
 )
 parser.add_argument(
     """--ltp""",
     required=False,
     type=str,
     default="""./resources/ltp""",
     help="""resources for LTP tokenizer, usually a path""",
 )
 parser.add_argument(
     """--bert""",
     required=False,
     type=str,
     default="""./resources/robert""",
     help="""resources for Bert tokenizer""",
 )
 parser.add_argument(
     """--save_path""",
     required=False,
     type=str,
     default="""./resources/ref.txt""",
     help="""path to save res""",
 )

 __a	 =      parser.parse_args()
 main(args)



