

import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class     __UpperCamelCase     (       _a  ,  unittest.TestCase    ):
	SCREAMING_SNAKE_CASE__     					=  GPTSanJapaneseTokenizer
	SCREAMING_SNAKE_CASE__     					=  False
	SCREAMING_SNAKE_CASE__     					=  {'''do_clean_text''': False, '''add_prefix_space''': False}




	def    __A       (		self						:    int				):


		'''simple docstring'''







		super().setUp()

		# fmt: off
		UpperCAmelCase_												=      ["こん", "こんに", "にちは", "ばんは", "世界,㔺界", "、", "。", "<BR>", "<SP>", "<TAB>", "<URL>", "<EMAIL>", "<TEL>", "<DATE>", "<PRICE>", "<BLOCK>", "<KIGOU>", "<U2000U2BFF>", "<|emoji1|>", "<unk>", "<|bagoftoken|>", "<|endoftext|>"]
		# fmt: on
		UpperCAmelCase_												=      {"emoji": {"\ud83d\ude00": "<|emoji1|>"}, "emoji_inv": {"<|emoji1|>": "\ud83d\ude00"}}  # 😀
		UpperCAmelCase_												=      {"unk_token": "<unk>"}

		UpperCAmelCase_												=      os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["vocab_file"]				)
		UpperCAmelCase_												=      os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["emoji_file"]				)
		with open(self.vocab_file		,						"w"		,						encoding="utf-8"				) as vocab_writer:
			vocab_writer.write("".join([x + "\n" for x in vocab_tokens]				)				)
		with open(self.emoji_file		,						"w"				) as emoji_writer:
			emoji_writer.write(json.dumps(lowerCAmelCase				)				)




	def    __A       (		self						:    int		,						**lowerCAmelCase						:    Optional[int]				):


		'''simple docstring'''







		kwargs.update(self.special_tokens_map				)
		return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname		,						**lowerCAmelCase				)




	def    __A       (		self						:    Optional[int]		,						lowerCAmelCase						:    int				):


		'''simple docstring'''







		UpperCAmelCase_												=      "こんにちは、世界。 \nこんばんは、㔺界。😀"
		UpperCAmelCase_												=      "こんにちは、世界。 \nこんばんは、世界。😀"
		return input_text, output_text




	def    __A       (		self						:    int		,						lowerCAmelCase						:    Any				):


		'''simple docstring'''







		UpperCAmelCase_					, UpperCAmelCase_												=      self.get_input_output_texts(lowerCAmelCase				)
		UpperCAmelCase_												=      tokenizer.encode(lowerCAmelCase		,						add_special_tokens=lowerCAmelCase				)
		UpperCAmelCase_												=      tokenizer.decode(lowerCAmelCase		,						clean_up_tokenization_spaces=lowerCAmelCase				)
		return text, ids




	def    __A       (		self						:    Dict				):


		'''simple docstring'''







		pass  # TODO add if relevant




	def    __A       (		self						:    Tuple				):


		'''simple docstring'''







		pass  # TODO add if relevant




	def    __A       (		self						:    Optional[int]				):


		'''simple docstring'''







		pass  # TODO add if relevant




	def    __A       (		self						:    int				):


		'''simple docstring'''







		UpperCAmelCase_												=      self.get_tokenizer()

		# Testing tokenization
		UpperCAmelCase_												=      "こんにちは、世界。　こんばんは、㔺界。"
		UpperCAmelCase_												=      ["こん", "にちは", "、", "世界", "。", "<SP>", "こん", "ばんは", "、", "㔺界", "。"]
		UpperCAmelCase_												=      tokenizer.tokenize(lowerCAmelCase				)
		self.assertListEqual(lowerCAmelCase		,						lowerCAmelCase				)

		# Testing conversion to ids without special tokens
		UpperCAmelCase_												=      [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
		UpperCAmelCase_												=      tokenizer.convert_tokens_to_ids(lowerCAmelCase				)
		self.assertListEqual(lowerCAmelCase		,						lowerCAmelCase				)

		# Testing conversion to ids with special tokens
		UpperCAmelCase_												=      tokens + [tokenizer.unk_token]
		UpperCAmelCase_												=      [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
		UpperCAmelCase_												=      tokenizer.convert_tokens_to_ids(lowerCAmelCase				)
		self.assertListEqual(lowerCAmelCase		,						lowerCAmelCase				)




	def    __A       (		self						:    Dict				):


		'''simple docstring'''







		UpperCAmelCase_												=      self.get_tokenizer()

		# Testing tokenization
		UpperCAmelCase_												=      "こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。"
		UpperCAmelCase_												=      "こんにちは、、、、世界。こんばんは、、、、世界。"
		UpperCAmelCase_												=      tokenizer.encode(lowerCAmelCase				)
		UpperCAmelCase_												=      tokenizer.decode(lowerCAmelCase				)
		self.assertEqual(lowerCAmelCase		,						lowerCAmelCase				)




	@slow
	def    __A       (		self						:    List[Any]				):


		'''simple docstring'''







		UpperCAmelCase_												=      self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"				)

		# Testing tokenization
		UpperCAmelCase_												=      "こんにちは、世界。"
		UpperCAmelCase_												=      "こんばんは、㔺界。😀"
		UpperCAmelCase_												=      "こんにちは、世界。こんばんは、世界。😀"
		UpperCAmelCase_												=      tokenizer.encode(prefix_text + input_text				)
		UpperCAmelCase_												=      tokenizer.encode(""		,						prefix_text=prefix_text + input_text				)
		UpperCAmelCase_												=      tokenizer.encode(lowerCAmelCase		,						prefix_text=lowerCAmelCase				)
		UpperCAmelCase_												=      tokenizer.decode(lowerCAmelCase				)
		UpperCAmelCase_												=      tokenizer.decode(lowerCAmelCase				)
		UpperCAmelCase_												=      tokenizer.decode(lowerCAmelCase				)
		self.assertEqual(lowerCAmelCase		,						lowerCAmelCase				)
		self.assertEqual(lowerCAmelCase		,						lowerCAmelCase				)
		self.assertEqual(lowerCAmelCase		,						lowerCAmelCase				)




	@slow
	def    __A       (		self						:    List[Any]				):


		'''simple docstring'''







		UpperCAmelCase_												=      self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"				)

		# Testing tokenization
		UpperCAmelCase_												=      "こんにちは、世界。"
		UpperCAmelCase_												=      "こんばんは、㔺界。😀"

		UpperCAmelCase_												=      len(tokenizer.encode(lowerCAmelCase				)				) - 2
		UpperCAmelCase_												=      len(tokenizer.encode(lowerCAmelCase				)				) - 2

		UpperCAmelCase_												=      [1] + [0] * (len_prefix + len_text + 1)
		UpperCAmelCase_												=      [1] * (len_prefix + len_text + 1) + [0]
		UpperCAmelCase_												=      [1] + [1] * (len_prefix) + [0] * (len_text + 1)

		UpperCAmelCase_												=      tokenizer(prefix_text + input_text				).token_type_ids
		UpperCAmelCase_												=      tokenizer(""		,						prefix_text=prefix_text + input_text				).token_type_ids
		UpperCAmelCase_												=      tokenizer(lowerCAmelCase		,						prefix_text=lowerCAmelCase				).token_type_ids
		self.assertListEqual(lowerCAmelCase		,						lowerCAmelCase				)
		self.assertListEqual(lowerCAmelCase		,						lowerCAmelCase				)
		self.assertListEqual(lowerCAmelCase		,						lowerCAmelCase				)




	@slow
	def    __A       (		self						:    List[str]				):


		'''simple docstring'''







		UpperCAmelCase_												=      self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"				)

		UpperCAmelCase_												=      tokenizer.encode("あンいワ"				)
		UpperCAmelCase_												=      tokenizer.encode(""		,						prefix_text="あンいワ"				)
		UpperCAmelCase_												=      tokenizer.encode("いワ"		,						prefix_text="あン"				)

		self.assertEqual(tokenizer.decode(lowerCAmelCase				)		,						tokenizer.decode(lowerCAmelCase				)				)
		self.assertEqual(tokenizer.decode(lowerCAmelCase				)		,						tokenizer.decode(lowerCAmelCase				)				)
		self.assertNotEqual(lowerCAmelCase		,						lowerCAmelCase				)
		self.assertNotEqual(lowerCAmelCase		,						lowerCAmelCase				)
		self.assertEqual(x_token_a[1]		,						x_token_a[-1]				)  # SEG token
		self.assertEqual(x_token_a[1]		,						x_token_a[3]				)  # SEG token




	@slow
	def    __A       (		self						:    Dict				):


		'''simple docstring'''







		UpperCAmelCase_												=      self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"				)

		UpperCAmelCase_												=      [["武田信玄", "は、"], ["織田信長", "の配下の、"]]
		UpperCAmelCase_												=      tokenizer(lowerCAmelCase		,						padding=lowerCAmelCase				)
		UpperCAmelCase_												=      tokenizer.batch_encode_plus(lowerCAmelCase		,						padding=lowerCAmelCase				)

		# fmt: off
		UpperCAmelCase_												=      [[35_993, 8_640, 25_948, 35_998, 30_647, 35_675, 35_999, 35_999], [35_993, 10_382, 9_868, 35_998, 30_646, 9_459, 30_646, 35_675]]
		UpperCAmelCase_												=      [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
		UpperCAmelCase_												=      [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
		# fmt: on
		self.assertListEqual(x_token.input_ids		,						lowerCAmelCase				)
		self.assertListEqual(x_token.token_type_ids		,						lowerCAmelCase				)
		self.assertListEqual(x_token.attention_mask		,						lowerCAmelCase				)
		self.assertListEqual(x_token_a.input_ids		,						lowerCAmelCase				)
		self.assertListEqual(x_token_a.token_type_ids		,						lowerCAmelCase				)
		self.assertListEqual(x_token_a.attention_mask		,						lowerCAmelCase				)




	def    __A       (		self						:    List[str]				):


		'''simple docstring'''







		pass




	def    __A       (		self						:    Union[str, Any]				):


		'''simple docstring'''







		pass







from math import sqrt

import numpy as np
from sympy import symbols

# Coefficient
# Speed of light (m/s)
_SCREAMING_SNAKE_CASE   =  2_99_79_24_58

# Symbols
_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   =  symbols("ct x y z")





def        _snake_case   (_snake_case				:       float)					->	float:
   if velocity > c:
      raise ValueError('Speed must not exceed light speed 299,792,458 [m/s]!')
   elif velocity < 1:
      # Usually the speed should be much higher than 1 (c order of magnitude)
      raise ValueError('Speed must be greater than or equal to 1!')

   return velocity / c





def        _snake_case   (_snake_case				:       float)					->	float:
   return 1 / sqrt(1 - beta(_snake_case) ** 2)





def        _snake_case   (_snake_case				:       float)					->	np.ndarray:
   return np.array(
       [
           [gamma(_snake_case), -gamma(_snake_case) * beta(_snake_case), 0, 0],
           [-gamma(_snake_case) * beta(_snake_case), gamma(_snake_case), 0, 0],
           [0, 0, 1, 0],
           [0, 0, 0, 1],
       ])





def        _snake_case   (_snake_case				:       float      ,    _snake_case				:       np.ndarray | None = None)					->	np.ndarray:
   # Ensure event is not empty
   if event is None:
      _lowercase              =np.array([ct, x, y, z])  # Symbolic four vector
   else:
      event[0] *= c  # x0 is ct (speed of light * time)

   return transformation_matrix(_snake_case) @ event


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    # Example of symbolic vector:
    _SCREAMING_SNAKE_CASE   =  transform(29_97_92_45)
    print("Example of four vector: ")
    print(f'''ct\' = {four_vector[0]}''')
    print(f'''x\' = {four_vector[1]}''')
    print(f'''y\' = {four_vector[2]}''')
    print(f'''z\' = {four_vector[3]}''')

    # Substitute symbols with numerical values
    _SCREAMING_SNAKE_CASE   =  {ct: c, x: 1, y: 1, z: 1}
    _SCREAMING_SNAKE_CASE   =  [four_vector[i].subs(sub_dict) for i in range(4)]

    print(f'''\n{numerical_vector}''')


