




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 		lowercase							(     a__,unittest.TestCase	):
     _a											=		CLIPTokenizer
     _a											=		CLIPTokenizerFast
     _a											=		True
     _a											=		{}
     _a											=		False

     def       a__			(						self       )		->							Any:
           super().setUp()

           # fmt: off
           _A							:  Dict    =		["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
           _A							:  Any    =		dict(zip(lowerCAmelCase__	,  range(len(lowerCAmelCase__       )       )       )       )
           _A							:  Optional[int]    =		["#version: 0.2", "l o", "lo w</w>", "e r</w>"]
           _A							:  List[str]    =		{"unk_token": "<unk>"}

           _A							:  Dict    =		os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["""vocab_file"""]       )
           _A							:  List[str]    =		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       a__			(						self	,  **_a       )		->							List[Any]:
           kwargs.update(self.special_tokens_map       )
           return CLIPTokenizer.from_pretrained(self.tmpdirname	,  **lowerCAmelCase__       )

     def       a__			(						self	,  **_a       )		->							int:
           kwargs.update(self.special_tokens_map       )
           return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,  **lowerCAmelCase__       )

     def       a__			(						self	,  _a       )		->							Optional[int]:
           _A							:  List[Any]    =		"lower newer"
           _A							:  int    =		"lower newer"
           return input_text, output_text

     def       a__			(						self       )		->							str:
           _A							:  Optional[Any]    =		CLIPTokenizer(self.vocab_file	,  self.merges_file	,  **self.special_tokens_map       )
           _A							:  List[Any]    =		"lower newer"
           _A							:  Optional[int]    =		["lo", "w", "er</w>", "n", "e", "w", "er</w>"]
           _A							:  List[str]    =		tokenizer.tokenize(lowerCAmelCase__       )
           self.assertListEqual(lowerCAmelCase__	,  lowerCAmelCase__       )

           _A							:  List[Any]    =		tokens + [tokenizer.unk_token]
           _A							:  List[Any]    =		[10, 2, 16, 9, 3, 2, 16, 20]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase__       )	,  lowerCAmelCase__       )

     @require_ftfy
     def       a__			(						self       )		->							Dict:
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
                       _A							:  List[str]    =		self.tokenizer_class.from_pretrained(lowerCAmelCase__	,  **lowerCAmelCase__       )
                       _A							:  List[Any]    =		self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__	,  **lowerCAmelCase__       )

                       _A							:  Any    =		"A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."
                       _A							:  str    =		tokenizer_s.tokenize(lowerCAmelCase__       )
                       _A							:  Union[str, Any]    =		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
                       _A							:  List[Any]    =		"xa\u0303y" + " " + "x\xe3y"
                       _A							:  str    =		tokenizer_s.tokenize(lowerCAmelCase__       )
                       _A							:  Optional[int]    =		tokenizer_r.tokenize(lowerCAmelCase__       )

                       self.assertListEqual(lowerCAmelCase__	,  lowerCAmelCase__       )

                       # Test that the tokenization is identical on unicode of space type
                       _A							:  Any    =		[
                           "\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:
                             _A							:  Any    =		tokenizer_s.tokenize(lowerCAmelCase__       )
                             _A							:  Dict    =		tokenizer_r.tokenize(lowerCAmelCase__       )

                             self.assertListEqual(lowerCAmelCase__	,  lowerCAmelCase__       )

                       # Test that the tokenization is identical on unicode of line break type
                       _A							:  Any    =		[
                           "\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:
                             _A							:  List[str]    =		tokenizer_s.tokenize(lowerCAmelCase__       )
                             _A							:  Tuple    =		tokenizer_r.tokenize(lowerCAmelCase__       )

                             self.assertListEqual(lowerCAmelCase__	,  lowerCAmelCase__       )

     def       a__			(						self       )		->							List[str]:
           # 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})'''       ):
                       _A							:  Tuple    =		"hello"  # `hello` is a token in the vocabulary of `pretrained_name`
                       _A							:  Tuple    =		F'''{text_of_1_token} {text_of_1_token}'''

                       _A							:  Union[str, Any]    =		self.rust_tokenizer_class.from_pretrained(
                           lowerCAmelCase__	,  use_fast=lowerCAmelCase__	,  )
                       _A							:  str    =		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__       ))	,  )

                       _A							:  Optional[Any]    =		F''' {text}'''

                       _A							:  Optional[int]    =		self.rust_tokenizer_class.from_pretrained(
                           lowerCAmelCase__	,  use_fast=lowerCAmelCase__	,  )
                       _A							:  Any    =		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       a__			(						self       )		->							Union[str, Any]:
           # 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       a__			(						self       )		->							Union[str, Any]:
           super().test_tokenization_python_rust_equals()



     def       a__			(						self       )		->							List[str]:
           # CLIP always lower cases letters
           pass










from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean







def        lowerCAmelCase_			(  snake_case_  ):

      # A local function to see if a dot lands in the circle.
      def is_in_circle(snake_case_,snake_case_  ) -> bool:
            _A							:  List[str]    =		sqrt((x**2) + (y**2)  )
            # Our circle has a radius of 1, so a distance
            # greater than 1 would land outside the circle.
            return distance_from_centre <= 1

      # The proportion of guesses that landed in the circle
      _A							:  Optional[int]    =		mean(
          int(is_in_circle(uniform(-1.0,1.0  ),uniform(-1.0,1.0  )  )  )
          for _ in range(snake_case_  )  )
      # The ratio of the area for circle to square is pi/4.
      _A							:  List[str]    =		proportion * 4
      print(f'''The estimated value of pi is {pi_estimate}'''  )
      print(f'''The numpy value of pi is {pi}'''  )
      print(f'''The total error is {abs(pi - pi_estimate  )}'''  )







def        lowerCAmelCase_			(  snake_case_,snake_case_,snake_case_ = 0.0,snake_case_ = 1.0,):
      return mean(
          function_to_integrate(uniform(snake_case_,snake_case_  )  ) for _ in range(snake_case_  )  ) * (max_value - min_value)







def        lowerCAmelCase_			(  snake_case_,snake_case_ = 0.0,snake_case_ = 1.0  ):

      def identity_function(snake_case_  ) -> float:
            return x

      _A							:  Any    =		area_under_curve_estimator(
          snake_case_,snake_case_,snake_case_,snake_case_  )
      _A							:  Tuple    =		(max_value * max_value - min_value * min_value) / 2

      print("""******************"""  )
      print(f'''Estimating area under y=x where x varies from {min_value} to {max_value}'''  )
      print(f'''Estimated value is {estimated_value}'''  )
      print(f'''Expected value is {expected_value}'''  )
      print(f'''Total error is {abs(estimated_value - expected_value  )}'''  )
      print("""******************"""  )







def        lowerCAmelCase_			(  snake_case_  ):

      def function_to_integrate(snake_case_  ) -> float:
            return sqrt(4.0 - x * x  )

      _A							:  Optional[int]    =		area_under_curve_estimator(
          snake_case_,snake_case_,0.0,2.0  )

      print("""******************"""  )
      print("""Estimating pi using area_under_curve_estimator"""  )
      print(f'''Estimated value is {estimated_value}'''  )
      print(f'''Expected value is {pi}'''  )
      print(f'''Total error is {abs(estimated_value - pi  )}'''  )
      print("""******************"""  )


if __name__ == "__main__":
  import doctest

  doctest.testmod()

