

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 						__magic_name__			(							A__		,       unittest.TestCase							):

   '''simple docstring'''




   lowerCamelCase__ :	Dict    =   CLIPTokenizer
   lowerCamelCase__ :	List[str]    =   CLIPTokenizerFast
   lowerCamelCase__ :	Dict    =   True
   lowerCamelCase__ :	Any    =   {}
   lowerCamelCase__ :	Optional[Any]    =   False



   def  _UpperCAmelCase (				self       )							->    Union[str, Any]:






     """simple docstring"""






     super().setUp()

     # fmt: off
     a__  =['''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__  =dict(zip(UpperCamelCase_,    range(len(UpperCamelCase_       )       )       )       )
     a__  =['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''']
     a__  ={'''unk_token''': '''<unk>'''}

     a__  =os.path.join(self.tmpdirname,    VOCAB_FILES_NAMES['''vocab_file''']       )
     a__  =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(UpperCamelCase_       ) + '''\n'''       )
     with open(self.merges_file,    '''w''',    encoding='''utf-8'''       ) as fp:
       fp.write('''\n'''.join(UpperCamelCase_       )       )



   def  _UpperCAmelCase (				self,    **lowercase_       )							->    str:






     """simple docstring"""






     kwargs.update(self.special_tokens_map       )
     return CLIPTokenizer.from_pretrained(self.tmpdirname,    **UpperCamelCase_       )



   def  _UpperCAmelCase (				self,    **lowercase_       )							->    List[str]:






     """simple docstring"""






     kwargs.update(self.special_tokens_map       )
     return CLIPTokenizerFast.from_pretrained(self.tmpdirname,    **UpperCamelCase_       )



   def  _UpperCAmelCase (				self,    lowercase_       )							->    int:






     """simple docstring"""






     a__  ='''lower newer'''
     a__  ='''lower newer'''
     return input_text, output_text



   def  _UpperCAmelCase (				self       )							->    Optional[Any]:






     """simple docstring"""






     a__  =CLIPTokenizer(self.vocab_file,    self.merges_file,    **self.special_tokens_map       )
     a__  ='''lower newer'''
     a__  =['''lo''', '''w''', '''er</w>''', '''n''', '''e''', '''w''', '''er</w>''']
     a__  =tokenizer.tokenize(UpperCamelCase_       )
     self.assertListEqual(UpperCamelCase_,    UpperCamelCase_       )

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



   @require_ftfy
   def  _UpperCAmelCase (				self       )							->    Tuple:






     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
         a__  =self.tokenizer_class.from_pretrained(UpperCamelCase_,    **UpperCamelCase_       )
         a__  =self.rust_tokenizer_class.from_pretrained(UpperCamelCase_,    **UpperCamelCase_       )

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

         self.assertListEqual(UpperCamelCase_,    UpperCamelCase_       )

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

         self.assertListEqual(UpperCamelCase_,    UpperCamelCase_       )

         # Test that the tokenization is identical on unicode of space type
         a__  =[
             '''\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__  =tokenizer_s.tokenize(UpperCamelCase_       )
           a__  =tokenizer_r.tokenize(UpperCamelCase_       )

           self.assertListEqual(UpperCamelCase_,    UpperCamelCase_       )

         # Test that the tokenization is identical on unicode of line break type
         a__  =[
             '''\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__  =tokenizer_s.tokenize(UpperCamelCase_       )
           a__  =tokenizer_r.tokenize(UpperCamelCase_       )

           self.assertListEqual(UpperCamelCase_,    UpperCamelCase_       )



   def  _UpperCAmelCase (				self       )							->    Tuple:






     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
         a__  ='''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
         a__  =F"""{text_of_1_token} {text_of_1_token}"""

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

         a__  =F""" {text}"""

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



   def  _UpperCAmelCase (				self       )							->    Any:






     """simple docstring"""






     with self.assertRaises(UpperCamelCase_       ) 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  _UpperCAmelCase (				self       )							->    List[str]:






     """simple docstring"""






     super().test_tokenization_python_rust_equals()



   def  _UpperCAmelCase (				self       )							->    str:






     """simple docstring"""






     pass




'''simple docstring'''
from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


__snake_case							      =     {'''configuration_dpt''': ['''DPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPTConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							      =     ['''DPTFeatureExtractor''']
		__snake_case							      =     ['''DPTImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							      =     [
		    '''DPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''DPTForDepthEstimation''',
		    '''DPTForSemanticSegmentation''',
		    '''DPTModel''',
		    '''DPTPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_dpt import DPTFeatureExtractor
				from .image_processing_dpt import DPTImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_dpt import (
				    DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DPTForDepthEstimation,
				    DPTForSemanticSegmentation,
				    DPTModel,
				    DPTPreTrainedModel,
				)


else:
		import sys

		__snake_case							      =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)