



"""simple docstring"""
import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class    SCREAMING_SNAKE_CASE__ (							__snake_case      ,  unittest.TestCase   ):
    lowercase__      =   OpenAIGPTTokenizer
    lowercase__      =   OpenAIGPTTokenizerFast
    lowercase__      =   True
    lowercase__      =   False

    def 					_UpperCAmelCase	(				self			:				Dict):







      """simple docstring"""







      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      lowercase_								= [
          """l""",
          """o""",
          """w""",
          """e""",
          """r""",
          """s""",
          """t""",
          """i""",
          """d""",
          """n""",
          """w</w>""",
          """r</w>""",
          """t</w>""",
          """lo""",
          """low""",
          """er</w>""",
          """low</w>""",
          """lowest</w>""",
          """newer</w>""",
          """wider</w>""",
          """<unk>""",
      ]
      lowercase_								= dict(zip(__UpperCamelCase ,  range(len(__UpperCamelCase))))
      lowercase_								= ["""#version: 0.2""", """l o""", """lo w""", """e r</w>""", """"""]

      lowercase_								= os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES["""vocab_file"""])
      lowercase_								= os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES["""merges_file"""])
      with open(self.vocab_file ,  """w""") as fp:
        fp.write(json.dumps(__UpperCamelCase))
      with open(self.merges_file ,  """w""") as fp:
        fp.write("""\n""".join(__UpperCamelCase))

    def 					_UpperCAmelCase	(				self			:				str ,  lowerCAmelCase_			:				Dict):







      """simple docstring"""







      return "lower newer", "lower newer"

    def 					_UpperCAmelCase	(				self			:				Tuple):







      """simple docstring"""







      lowercase_								= OpenAIGPTTokenizer(self.vocab_file ,  self.merges_file)

      lowercase_								= """lower"""
      lowercase_								= ["""low""", """er</w>"""]
      lowercase_								= tokenizer.tokenize(__UpperCamelCase)
      self.assertListEqual(__UpperCamelCase ,  __UpperCamelCase)

      lowercase_								= tokens + ["""<unk>"""]
      lowercase_								= [1_4, 1_5, 2_0]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase) ,  __UpperCamelCase)

    def 					_UpperCAmelCase	(				self			:				Optional[Any] ,  lowerCAmelCase_			:				Optional[int]=1_5):







      """simple docstring"""







      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''):
          lowercase_								= self.rust_tokenizer_class.from_pretrained(__UpperCamelCase ,  **__UpperCamelCase)

          # Simple input
          lowercase_								= """This is a simple input"""
          lowercase_								= ["""This is a simple input 1""", """This is a simple input 2"""]
          lowercase_								= ("""This is a simple input""", """This is a pair""")
          lowercase_								= [
              ("""This is a simple input 1""", """This is a simple input 2"""),
              ("""This is a simple pair 1""", """This is a simple pair 2"""),
          ]

          # Simple input tests
          self.assertRaises(__UpperCamelCase ,  tokenizer_r.encode ,  __UpperCamelCase ,  max_length=__UpperCamelCase ,  padding="""max_length""")

          # Simple input
          self.assertRaises(__UpperCamelCase ,  tokenizer_r.encode_plus ,  __UpperCamelCase ,  max_length=__UpperCamelCase ,  padding="""max_length""")

          # Simple input
          self.assertRaises(
              __UpperCamelCase ,  tokenizer_r.batch_encode_plus ,  __UpperCamelCase ,  max_length=__UpperCamelCase ,  padding="""max_length""" ,  )

          # Pair input
          self.assertRaises(__UpperCamelCase ,  tokenizer_r.encode ,  __UpperCamelCase ,  max_length=__UpperCamelCase ,  padding="""max_length""")

          # Pair input
          self.assertRaises(__UpperCamelCase ,  tokenizer_r.encode_plus ,  __UpperCamelCase ,  max_length=__UpperCamelCase ,  padding="""max_length""")

          # Pair input
          self.assertRaises(
              __UpperCamelCase ,  tokenizer_r.batch_encode_plus ,  __UpperCamelCase ,  max_length=__UpperCamelCase ,  padding="""max_length""" ,  )




    def 					_UpperCAmelCase	(				self			:				str):







      """simple docstring"""







      pass







@require_ftfy
@require_spacy
@require_tokenizers
class    SCREAMING_SNAKE_CASE__ (							__snake_case   ):
    pass






"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase						:		Any			= {
    "configuration_blip": [
        "BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlipConfig",
        "BlipTextConfig",
        "BlipVisionConfig",
    ],
    "processing_blip": ["BlipProcessor"],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		Any			= ["BlipImageProcessor"]


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		Optional[int]			= [
           "BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
           "BlipModel",
           "BlipPreTrainedModel",
           "BlipForConditionalGeneration",
           "BlipForQuestionAnswering",
           "BlipVisionModel",
           "BlipTextModel",
           "BlipForImageTextRetrieval",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		str			= [
           "TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFBlipModel",
           "TFBlipPreTrainedModel",
           "TFBlipForConditionalGeneration",
           "TFBlipForQuestionAnswering",
           "TFBlipVisionModel",
           "TFBlipTextModel",
           "TFBlipForImageTextRetrieval",
       ]

if TYPE_CHECKING:
       from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
       from .processing_blip import BlipProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_blip import BlipImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_blip import (
                  BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  BlipForConditionalGeneration,
                  BlipForImageTextRetrieval,
                  BlipForQuestionAnswering,
                  BlipModel,
                  BlipPreTrainedModel,
                  BlipTextModel,
                  BlipVisionModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_blip import (
                  TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFBlipForConditionalGeneration,
                  TFBlipForImageTextRetrieval,
                  TFBlipForQuestionAnswering,
                  TFBlipModel,
                  TFBlipPreTrainedModel,
                  TFBlipTextModel,
                  TFBlipVisionModel,
              )

else:
       import sys

       UpperCAmelCase						:		Any			= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

