





'''simple docstring'''





import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class SCREAMING_SNAKE_CASE_ (					lowercase_							,       unittest.TestCase   ):





					"""simple docstring"""


					A__				 =    CLIPTokenizer
					A__				 =    CLIPTokenizerFast
					A__				 =    True
					A__				 =    {}
					A__				 =    False





					def 					__magic_name__ ( self	):
										super().setUp()

										# fmt: off
										lowerCamelCase__       =       ["l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "lo", "l</w>", "w</w>", "r</w>", "t</w>", "low</w>", "er</w>", "lowest</w>", "newer</w>", "wider", "<unk>", "<|startoftext|>", "<|endoftext|>"]
										# fmt: on
										lowerCamelCase__       =       dict(zip(_lowerCAmelCase	,  range(len(_lowerCAmelCase	)	)	)	)
										lowerCamelCase__       =       ["#version: 0.2", "l o", "lo w</w>", "e r</w>"]
										lowerCamelCase__       =       {"unk_token": "<unk>"}

										lowerCamelCase__       =       os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["vocab_file"]	)
										lowerCamelCase__       =       os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["merges_file"]	)
										with open(self.vocab_file	,  "w"	,  encoding="utf-8"	) as fp:
															fp.write(json.dumps(_lowerCAmelCase	) + "\n"	)
										with open(self.merges_file	,  "w"	,  encoding="utf-8"	) as fp:
															fp.write("\n".join(_lowerCAmelCase	)	)





					def 					__magic_name__ ( self	,  **_lowerCAmelCase	):
										kwargs.update(self.special_tokens_map	)
										return CLIPTokenizer.from_pretrained(self.tmpdirname	,  **_lowerCAmelCase	)





					def 					__magic_name__ ( self	,  **_lowerCAmelCase	):
										kwargs.update(self.special_tokens_map	)
										return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,  **_lowerCAmelCase	)





					def 					__magic_name__ ( self	,  _lowerCAmelCase	):
										lowerCamelCase__       =       "lower newer"
										lowerCamelCase__       =       "lower newer"
										return input_text, output_text





					def 					__magic_name__ ( self	):
										lowerCamelCase__       =       CLIPTokenizer(self.vocab_file	,  self.merges_file	,  **self.special_tokens_map	)
										lowerCamelCase__       =       "lower newer"
										lowerCamelCase__       =       ["lo", "w", "er</w>", "n", "e", "w", "er</w>"]
										lowerCamelCase__       =       tokenizer.tokenize(_lowerCAmelCase	)
										self.assertListEqual(_lowerCAmelCase	,  _lowerCAmelCase	)

										lowerCamelCase__       =       tokens + [tokenizer.unk_token]
										lowerCamelCase__       =       [10, 2, 16, 9, 3, 2, 16, 20]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase	)	,  _lowerCAmelCase	)





					@require_ftfy
					def 					__magic_name__ ( self	):
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"	):
																				lowerCamelCase__       =       self.tokenizer_class.from_pretrained(_lowerCAmelCase	,  **_lowerCAmelCase	)
																				lowerCamelCase__       =       self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase	,  **_lowerCAmelCase	)

																				lowerCamelCase__       =       "A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."
																				lowerCamelCase__       =       tokenizer_s.tokenize(_lowerCAmelCase	)
																				lowerCamelCase__       =       tokenizer_r.tokenize(_lowerCAmelCase	)

																				self.assertListEqual(_lowerCAmelCase	,  _lowerCAmelCase	)

																				# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
																				# with Tilde) encoded in 2 different ways
																				lowerCamelCase__       =       "xa\u0303y" + " " + "x\xe3y"
																				lowerCamelCase__       =       tokenizer_s.tokenize(_lowerCAmelCase	)
																				lowerCamelCase__       =       tokenizer_r.tokenize(_lowerCAmelCase	)

																				self.assertListEqual(_lowerCAmelCase	,  _lowerCAmelCase	)

																				# Test that the tokenization is identical on unicode of space type
																				lowerCamelCase__       =       [
																				    "\u0009",  # (horizontal tab, '\t')
																				    "\u000B",  # (vertical tab)
																				    "\u000C",  # (form feed)
																				    "\u0020",  # (space, ' ')
																				    "\u200E",  # (left-to-right mark):w
																				    "\u200F",  # (right-to-left mark)
																				]
																				for unicode_seq in spaces_unicodes:
																									lowerCamelCase__       =       tokenizer_s.tokenize(_lowerCAmelCase	)
																									lowerCamelCase__       =       tokenizer_r.tokenize(_lowerCAmelCase	)

																									self.assertListEqual(_lowerCAmelCase	,  _lowerCAmelCase	)

																				# Test that the tokenization is identical on unicode of line break type
																				lowerCamelCase__       =       [
																				    "\u000A",  # (line feed, '\n')
																				    "\r\n",  # (carriage return and line feed, '\r\n')
																				    "\u000D",  # (carriage return, '\r')
																				    "\r",  # (carriage return, '\r')
																				    "\u000D",  # (carriage return, '\r')
																				    "\u2028",  # (line separator)
																				    "\u2029",  # (paragraph separator)
																				    # "\u0085", # (next line)
																				]

																				# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
																				# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
																				# space (and thus into an empty list).

																				for unicode_seq in line_break_unicodes:
																									lowerCamelCase__       =       tokenizer_s.tokenize(_lowerCAmelCase	)
																									lowerCamelCase__       =       tokenizer_r.tokenize(_lowerCAmelCase	)

																									self.assertListEqual(_lowerCAmelCase	,  _lowerCAmelCase	)





					def 					__magic_name__ ( self	):
										# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"	):
																				lowerCamelCase__       =       "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																				lowerCamelCase__       =       F"{text_of_1_token} {text_of_1_token}"

																				lowerCamelCase__       =       self.rust_tokenizer_class.from_pretrained(
																				    _lowerCAmelCase	,  use_fast=_lowerCAmelCase	,  )
																				lowerCamelCase__       =       tokenizer_r(_lowerCAmelCase	,  return_offsets_mapping=_lowerCAmelCase	,  add_special_tokens=_lowerCAmelCase	)
																				self.assertEqual(encoding.offset_mapping[0]	,  (0, len(_lowerCAmelCase	))	)
																				self.assertEqual(
																				    encoding.offset_mapping[1]	,  (len(_lowerCAmelCase	) + 1, len(_lowerCAmelCase	) + 1 + len(_lowerCAmelCase	))	,  )

																				lowerCamelCase__       =       F" {text}"

																				lowerCamelCase__       =       self.rust_tokenizer_class.from_pretrained(
																				    _lowerCAmelCase	,  use_fast=_lowerCAmelCase	,  )
																				lowerCamelCase__       =       tokenizer_r(_lowerCAmelCase	,  return_offsets_mapping=_lowerCAmelCase	,  add_special_tokens=_lowerCAmelCase	)
																				self.assertEqual(encoding.offset_mapping[0]	,  (1, 1 + len(_lowerCAmelCase	))	)
																				self.assertEqual(
																				    encoding.offset_mapping[1]	,  (1 + len(_lowerCAmelCase	) + 1, 1 + len(_lowerCAmelCase	) + 1 + len(_lowerCAmelCase	))	,  )





					def 					__magic_name__ ( self	):
										# Test related to the breaking change introduced in transformers v4.17.0
										# We need to check that an error in raised when the user try to load a previous version of the tokenizer.
										with self.assertRaises(_lowerCAmelCase	) as context:
															self.rust_tokenizer_class.from_pretrained("robot-test/old-clip-tokenizer"	)

										self.assertTrue(
										    context.exception.args[0].startswith(
										        "The `backend_tokenizer` provided does not match the expected format."	)	)





					@require_ftfy
					def 					__magic_name__ ( self	):
										super().test_tokenization_python_rust_equals()






					def 					__magic_name__ ( self	):
										# CLIP always lower cases letters
										pass








def    __UpperCamelCase      (    a) ->float:
					return 10 - x * x





def    __UpperCamelCase      (    a,     a) ->float:
					# Bolzano theory in order to find if there is a root between a and b
					if equation(a) * equation(a) >= 0:
										raise ValueError("Wrong space!")

					lowerCamelCase__       =       a
					while (b - a) >= 0.0_1:
										# Find middle point
										lowerCamelCase__       =       (a + b) / 2
										# Check if middle point is root
										if equation(a) == 0.0:
															break
										# Decide the side to repeat the steps
										if equation(a) * equation(a) < 0:
															lowerCamelCase__       =       c
										else:
															lowerCamelCase__       =       c
					return c


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						print(bisection(-2, 5))
						print(bisection(0, 6))

