



'''simple docstring'''

import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						Optional[int]							)      ->						Optional[int]:







	"""simple docstring"""
	# 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 >= 0X4E00 and cp <= 0X9FFF)
	    or (cp >= 0X3400 and cp <= 0X4DBF)  #
	    or (cp >= 0X20000 and cp <= 0X2A6DF)  #
	    or (cp >= 0X2A700 and cp <= 0X2B73F)  #
	    or (cp >= 0X2B740 and cp <= 0X2B81F)  #
	    or (cp >= 0X2B820 and cp <= 0X2CEAF)  #
	    or (cp >= 0XF900 and cp <= 0XFAFF)
	    or (cp >= 0X2F800 and cp <= 0X2FA1F)  #
	):  #
		return True

	return False






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							)      ->						str:







	"""simple docstring"""
	# word like '180' or '身高' or '神'
	for char in word:
		lowerCAmelCase   =     ord(_a							)
		if not _is_chinese_char(_a							):
			return 0
	return 1






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						List[str]							)      ->						List[Any]:







	"""simple docstring"""
	lowerCAmelCase   =     set()

	for token in tokens:
		lowerCAmelCase   =     len(_a							) > 1 and is_chinese(_a							)
		if chinese_word:
			word_set.add(_a							)
	lowerCAmelCase   =     list(_a							)
	return word_list






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						List[str]							,		_SCREAMING_SNAKE_CASE					:						set()							)      ->						Tuple:







	"""simple docstring"""
	if not chinese_word_set:
		return bert_tokens
	lowerCAmelCase   =     max([len(_a							) for w in chinese_word_set]							)

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






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						List[str]							,		_SCREAMING_SNAKE_CASE					:						LTP							,		_SCREAMING_SNAKE_CASE					:						BertTokenizer							)      ->						Any:







	"""simple docstring"""
	lowerCAmelCase   =     []

	for i in range(0							,		len(_a							)							,		100							):
		lowerCAmelCase   =     ltp_tokenizer.seg(lines[i : i + 100]							)[0]
		lowerCAmelCase   =     [get_chinese_word(_a							) for r in res]
		ltp_res.extend(_a							)
	assert len(_a							) == len(_a							)

	lowerCAmelCase   =     []
	for i in range(0							,		len(_a							)							,		100							):
		lowerCAmelCase   =     bert_tokenizer(lines[i : i + 100]							,		add_special_tokens=_a							,		truncation=_a							,		max_length=512							)
		bert_res.extend(res["""input_ids"""]							)
	assert len(_a							) == len(_a							)

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

	assert len(_a							) == len(_a							)

	return ref_ids






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						int							)      ->						int:







	"""simple docstring"""
	# 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:
		lowerCAmelCase   =     f.readlines()
	lowerCAmelCase   =     [line.strip() for line in data if len(_a							) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
	lowerCAmelCase   =     LTP(args.ltp							)  # faster in GPU device
	lowerCAmelCase   =     BertTokenizer.from_pretrained(args.bert							)

	lowerCAmelCase   =     prepare_ref(_a							,		_a							,		_a							)

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


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

						UpperCAmelCase     		=   parser.parse_args()
						main(args)




'''simple docstring'''

import cmath
import math






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						float							,		_SCREAMING_SNAKE_CASE					:						float							,		_SCREAMING_SNAKE_CASE					:						float							,		_SCREAMING_SNAKE_CASE					:						float							)      ->						complex:







	"""simple docstring"""
	lowerCAmelCase   =     math.radians(_SCREAMING_SNAKE_CASE							)
	lowerCAmelCase   =     math.radians(_SCREAMING_SNAKE_CASE							)

	# Convert voltage and current to rectangular form
	lowerCAmelCase   =     cmath.rect(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)
	lowerCAmelCase   =     cmath.rect(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)

	# Calculate apparent power
	return voltage_rect * current_rect


if __name__ == "__main__":
				import doctest

				doctest.testmod()