


import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer






def 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		Any						):





			"""simple docstring"""




			if (
			    (cp >= 0x4e_00 and cp <= 0x9f_ff)
			    or (cp >= 0x34_00 and cp <= 0x4d_bf)  #
			    or (cp >= 0x2_00_00 and cp <= 0x2_a6_df)  #
			    or (cp >= 0x2_a7_00 and cp <= 0x2_b7_3f)  #
			    or (cp >= 0x2_b7_40 and cp <= 0x2_b8_1f)  #
			    or (cp >= 0x2_b8_20 and cp <= 0x2_ce_af)  #
			    or (cp >= 0xf9_00 and cp <= 0xfa_ff)
			    or (cp >= 0x2_f8_00 and cp <= 0x2_fa_1f)  #
			):  #
						return True

			return False






def 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		str						):





			"""simple docstring"""




			for char in word:
						UpperCamelCase								=       ord(_UpperCAmelCase						)
						if not _is_chinese_char(_UpperCAmelCase						):
									return 0
			return 1






def 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		List[str]						):





			"""simple docstring"""




			UpperCamelCase								=       set()

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






def 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		List[str]							,	SCREAMING_SNAKE_CASE_ :		set()						):





			"""simple docstring"""




			if not chinese_word_set:
						return bert_tokens
			UpperCamelCase								=       max([len(_UpperCAmelCase						) for w in chinese_word_set]						)

			UpperCamelCase								=       bert_tokens
			UpperCamelCase	,	UpperCamelCase								=       0, len(_UpperCAmelCase						)
			while start < end:
						UpperCamelCase								=       True
						if is_chinese(bert_word[start]						):
									UpperCamelCase								=       min(end - start							,	_UpperCAmelCase						)
									for i in range(_UpperCAmelCase							,	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 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		List[str]							,	SCREAMING_SNAKE_CASE_ :		LTP							,	SCREAMING_SNAKE_CASE_ :		BertTokenizer						):





			"""simple docstring"""




			UpperCamelCase								=       []

			for i in range(0							,	len(_UpperCAmelCase						)							,	100						):
						UpperCamelCase								=       ltp_tokenizer.pipeline(lines[i : i + 100]							,	tasks=["""cws"""]						).cws
						UpperCamelCase								=       [get_chinese_word(_UpperCAmelCase						) for r in res]
						ltp_res.extend(_UpperCAmelCase						)
			assert len(_UpperCAmelCase						) == len(_UpperCAmelCase						)

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

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

			assert len(_UpperCAmelCase						) == len(_UpperCAmelCase						)

			return ref_ids






def 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		Dict						):





			"""simple docstring"""




			with open(args.file_name							,	"""r"""							,	encoding="""utf-8"""						) as f:
						UpperCamelCase								=       f.readlines()
			UpperCamelCase								=       [line.strip() for line in data if len(_UpperCAmelCase						) > 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(_UpperCAmelCase							,	_UpperCAmelCase							,	_UpperCAmelCase						)

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


if __name__ == "__main__":
			__snake_case      = 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",
			)

			__snake_case      = parser.parse_args()
			main(args)











import requests

a__      :     Any         =		'YOUR API KEY'

def      UpperCAmelCase_    (    _UpperCAmelCase							:str  ,						_UpperCAmelCase							:str = giphy_api_key				)	->				list:
     '''simple docstring'''


     A_          =       '''+'''.join(query.split()				)
     A_          =       f'https://api.giphy.com/v1/gifs/search?q={formatted_query}&api_key={api_key}'
     A_          =       requests.get(_UpperCAmelCase				).json()['''data''']
     return [gif["url"] for gif in gifs]


if __name__ == "__main__":
      print('\n'.join(get_gifs('space ship')))



