
"""simple docstring"""


import argparse
import datetime






def   lowerCAmelCase_  (						snake_case_						:     Optional[Any]     )  ->str:
			lowerCamelCase__      :	Tuple						={
			    "0": "Sunday",
			    "1": "Monday",
			    "2": "Tuesday",
			    "3": "Wednesday",
			    "4": "Thursday",
			    "5": "Friday",
			    "6": "Saturday",
			}

			lowerCamelCase__      :	List[str]						={0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 6, 6: 0}

			# Validate
			if not 0 < len(snake_case_     ) < 1_1:
						raise ValueError('Must be 10 characters long'     )

			# Get month
			lowerCamelCase__      :	int						=int(date_input[0] + date_input[1]     )
			# Validate
			if not 0 < m < 1_3:
						raise ValueError('Month must be between 1 - 12'     )

			lowerCamelCase__      :	str						=date_input[2]
			# Validate
			if sep_a not in ["-", "/"]:
						raise ValueError('Date separator must be \'-\' or \'/\''     )

			# Get day
			lowerCamelCase__      :	int						=int(date_input[3] + date_input[4]     )
			# Validate
			if not 0 < d < 3_2:
						raise ValueError('Date must be between 1 - 31'     )

			# Get second separator
			lowerCamelCase__      :	str						=date_input[5]
			# Validate
			if sep_a not in ["-", "/"]:
						raise ValueError('Date separator must be \'-\' or \'/\''     )

			# Get year
			lowerCamelCase__      :	int						=int(date_input[6] + date_input[7] + date_input[8] + date_input[9]     )
			# Arbitrary year range
			if not 4_5 < y < 8_5_0_0:
						raise ValueError(
						    'Year out of range. There has to be some sort of limit...right?'     )

			# Get datetime obj for validation
			lowerCamelCase__      :	str						=datetime.date(int(snake_case_     )				,       int(snake_case_     )				,       int(snake_case_     )     )

			# Start math
			if m <= 2:
						lowerCamelCase__      :	Optional[int]						=y - 1
						lowerCamelCase__      :	Any						=m + 1_2
			# maths var
			lowerCamelCase__      :	int						=int(str(snake_case_     )[:2]     )
			lowerCamelCase__      :	int						=int(str(snake_case_     )[2:]     )
			lowerCamelCase__      :	int						=int(2.6 * m - 5.39     )
			lowerCamelCase__      :	int						=int(c / 4     )
			lowerCamelCase__      :	int						=int(k / 4     )
			lowerCamelCase__      :	int						=int(d + k     )
			lowerCamelCase__      :	int						=int(t + u + v + x     )
			lowerCamelCase__      :	int						=int(z - (2 * c)     )
			lowerCamelCase__      :	int						=round(w % 7     )
			# End math

			# Validate math
			if f != convert_datetime_days[dt_ck.weekday()]:
						raise AssertionError('The date was evaluated incorrectly. Contact developer.'     )

			# Response
			lowerCamelCase__      :	str						=f"""Your date {date_input}, is a {days[str(snake_case_     )]}!"""
			return response


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							lowerCAmelCase								=		argparse.ArgumentParser(
							    description=(
							        """Find out what day of the week nearly any date is or was. Enter """
							        """date as a string in the mm-dd-yyyy or mm/dd/yyyy format"""
							    )
							)
							parser.add_argument(
							    """date_input""", type=str, help="""Date as a string (mm-dd-yyyy or mm/dd/yyyy)"""
							)
							lowerCAmelCase								=		parser.parse_args()
							zeller(args.date_input)



'''simple docstring'''
import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer




def 	_A  (       A							)  ->				int:
	# 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 	_A  (       A							)  ->				List[Any]:
	# word like '180' or '身高' or '神'
	for char in word:
		lowercase						:		int   					=		ord(A							)
		if not _is_chinese_char(A							):
			return 0
	return 1




def 	_A  (       A							)  ->				Dict:
	lowercase						:		Any   					=		set()

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




def 	_A  (       A							,A							)  ->				Tuple:
	if not chinese_word_set:
		return bert_tokens
	lowercase						:		Optional[Any]   					=		max([len(A							) for w in chinese_word_set]							)

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




def 	_A  (       A							,A							,A							)  ->				List[Any]:
	lowercase						:		List[Any]   					=		[]

	for i in range(0							,len(A							)							,1_0_0							):
		lowercase						:		int   					=		ltp_tokenizer.seg(lines[i : i + 1_0_0]							)[0]
		lowercase						:		Dict   					=		[get_chinese_word(A							) for r in res]
		ltp_res.extend(A							)
	assert len(A							) == len(A							)

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

	lowercase						:		Optional[Any]   					=		[]
	for input_ids, chinese_word in zip(A							,A							):
		lowercase						:		str   					=		[]
		for id in input_ids:
			lowercase						:		Any   					=		bert_tokenizer._convert_id_to_token(A							)
			input_tokens.append(A							)
		lowercase						:		Tuple   					=		add_sub_symbol(A							,A							)
		lowercase						:		Tuple   					=		[]
		# 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] == "##":
				lowercase						:		Any   					=		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 	_A  (       A							)  ->				Union[str, Any]:
	# 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:
		lowercase						:		List[str]   					=		f.readlines()
	lowercase						:		Tuple   					=		[line.strip() for line in data if len(A							) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
	lowercase						:		Any   					=		LTP(args.ltp							)  # faster in GPU device
	lowercase						:		int   					=		BertTokenizer.from_pretrained(args.bert							)

	lowercase						:		List[str]   					=		prepare_ref(A							,A							,A							)

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


if __name__ == "__main__":
					lowerCAmelCase   : List[Any]             =				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""")

					lowerCAmelCase   : Union[str, Any]             =				parser.parse_args()
					main(args)


