






import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
      from PIL import Image

      from transformers import CLIPSegProcessor, ViTImageProcessor





@require_vision
class 					A							(    unittest.TestCase					):


   def       lowercase_				(self					:						Optional[Any]		)						->    Any:
         """simple docstring"""



         UpperCAmelCase__								=  tempfile.mkdtemp()

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

         UpperCAmelCase__								=  os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["vocab_file"]		)
         UpperCAmelCase__								=  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		)		)

         UpperCAmelCase__								=  {
             "do_resize": True,
             "size": 2_0,
             "do_center_crop": True,
             "crop_size": 1_8,
             "do_normalize": True,
             "image_mean": [0.48145466, 0.4578275, 0.40821073],
             "image_std": [0.26862954, 0.26130258, 0.27577711],
         }
         UpperCAmelCase__								=  os.path.join(self.tmpdirname	,  __UpperCAmelCase		)
         with open(self.image_processor_file	,  "w"	,  encoding="utf-8"		) as fp:
               json.dump(__UpperCAmelCase	,  __UpperCAmelCase		)


   def       lowercase_				(self					:						List[str]	,  **__UpperCAmelCase					:						List[str]		)						->    Tuple:
         """simple docstring"""



         return CLIPTokenizer.from_pretrained(self.tmpdirname	,  **__UpperCAmelCase		)


   def       lowercase_				(self					:						Dict	,  **__UpperCAmelCase					:						List[Any]		)						->    Optional[int]:
         """simple docstring"""



         return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,  **__UpperCAmelCase		)


   def       lowercase_				(self					:						Optional[int]	,  **__UpperCAmelCase					:						Optional[int]		)						->    Any:
         """simple docstring"""



         return ViTImageProcessor.from_pretrained(self.tmpdirname	,  **__UpperCAmelCase		)


   def       lowercase_				(self					:						Dict		)						->    int:
         """simple docstring"""



         shutil.rmtree(self.tmpdirname		)


   def       lowercase_				(self					:						str		)						->    Tuple:
         """simple docstring"""



         UpperCAmelCase__								=  [np.random.randint(2_5_5	,  size=(3, 3_0, 4_0_0)	,  dtype=np.uinta		)]

         UpperCAmelCase__								=  [Image.fromarray(np.moveaxis(__UpperCAmelCase	,  0	,  -1		)		) for x in image_inputs]

         return image_inputs


   def       lowercase_				(self					:						List[Any]		)						->    Any:
         """simple docstring"""



         UpperCAmelCase__								=  self.get_tokenizer()
         UpperCAmelCase__								=  self.get_rust_tokenizer()
         UpperCAmelCase__								=  self.get_image_processor()

         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=__UpperCAmelCase	,  image_processor=__UpperCAmelCase		)
         processor_slow.save_pretrained(self.tmpdirname		)
         UpperCAmelCase__								=  CLIPSegProcessor.from_pretrained(self.tmpdirname	,  use_fast=__UpperCAmelCase		)

         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=__UpperCAmelCase	,  image_processor=__UpperCAmelCase		)
         processor_fast.save_pretrained(self.tmpdirname		)
         UpperCAmelCase__								=  CLIPSegProcessor.from_pretrained(self.tmpdirname		)

         self.assertEqual(processor_slow.tokenizer.get_vocab()	,  tokenizer_slow.get_vocab()		)
         self.assertEqual(processor_fast.tokenizer.get_vocab()	,  tokenizer_fast.get_vocab()		)
         self.assertEqual(tokenizer_slow.get_vocab()	,  tokenizer_fast.get_vocab()		)
         self.assertIsInstance(processor_slow.tokenizer	,  __UpperCAmelCase		)
         self.assertIsInstance(processor_fast.tokenizer	,  __UpperCAmelCase		)

         self.assertEqual(processor_slow.image_processor.to_json_string()	,  image_processor.to_json_string()		)
         self.assertEqual(processor_fast.image_processor.to_json_string()	,  image_processor.to_json_string()		)
         self.assertIsInstance(processor_slow.image_processor	,  __UpperCAmelCase		)
         self.assertIsInstance(processor_fast.image_processor	,  __UpperCAmelCase		)


   def       lowercase_				(self					:						str		)						->    Any:
         """simple docstring"""



         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=self.get_tokenizer()	,  image_processor=self.get_image_processor()		)
         processor.save_pretrained(self.tmpdirname		)

         UpperCAmelCase__								=  self.get_tokenizer(bos_token="(BOS)"	,  eos_token="(EOS)"		)
         UpperCAmelCase__								=  self.get_image_processor(do_normalize=__UpperCAmelCase	,  padding_value=1.0		)

         UpperCAmelCase__								=  CLIPSegProcessor.from_pretrained(
             self.tmpdirname	,  bos_token="(BOS)"	,  eos_token="(EOS)"	,  do_normalize=__UpperCAmelCase	,  padding_value=1.0		)

         self.assertEqual(processor.tokenizer.get_vocab()	,  tokenizer_add_kwargs.get_vocab()		)
         self.assertIsInstance(processor.tokenizer	,  __UpperCAmelCase		)

         self.assertEqual(processor.image_processor.to_json_string()	,  image_processor_add_kwargs.to_json_string()		)
         self.assertIsInstance(processor.image_processor	,  __UpperCAmelCase		)


   def       lowercase_				(self					:						Tuple		)						->    Tuple:
         """simple docstring"""



         UpperCAmelCase__								=  self.get_image_processor()
         UpperCAmelCase__								=  self.get_tokenizer()

         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=__UpperCAmelCase	,  image_processor=__UpperCAmelCase		)

         UpperCAmelCase__								=  self.prepare_image_inputs()

         UpperCAmelCase__								=  image_processor(__UpperCAmelCase	,  return_tensors="np"		)
         UpperCAmelCase__								=  processor(images=__UpperCAmelCase	,  return_tensors="np"		)

         for key in input_feat_extract.keys():
               self.assertAlmostEqual(input_feat_extract[key].sum()	,  input_processor[key].sum()	,  delta=1E-2		)


   def       lowercase_				(self					:						Any		)						->    Union[str, Any]:
         """simple docstring"""



         UpperCAmelCase__								=  self.get_image_processor()
         UpperCAmelCase__								=  self.get_tokenizer()

         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=__UpperCAmelCase	,  image_processor=__UpperCAmelCase		)

         UpperCAmelCase__								=  "lower newer"

         UpperCAmelCase__								=  processor(text=__UpperCAmelCase		)

         UpperCAmelCase__								=  tokenizer(__UpperCAmelCase		)

         for key in encoded_tok.keys():
               self.assertListEqual(encoded_tok[key]	,  encoded_processor[key]		)


   def       lowercase_				(self					:						List[str]		)						->    Any:
         """simple docstring"""



         UpperCAmelCase__								=  self.get_image_processor()
         UpperCAmelCase__								=  self.get_tokenizer()

         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=__UpperCAmelCase	,  image_processor=__UpperCAmelCase		)

         UpperCAmelCase__								=  "lower newer"
         UpperCAmelCase__								=  self.prepare_image_inputs()

         UpperCAmelCase__								=  processor(text=__UpperCAmelCase	,  images=__UpperCAmelCase		)

         self.assertListEqual(list(inputs.keys()		)	,  ["input_ids", "attention_mask", "pixel_values"]		)

         # test if it raises when no input is passed
         with pytest.raises(__UpperCAmelCase		):
               processor()


   def       lowercase_				(self					:						str		)						->    Optional[Any]:
         """simple docstring"""



         UpperCAmelCase__								=  self.get_image_processor()
         UpperCAmelCase__								=  self.get_tokenizer()

         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=__UpperCAmelCase	,  image_processor=__UpperCAmelCase		)

         UpperCAmelCase__								=  self.prepare_image_inputs()
         UpperCAmelCase__								=  self.prepare_image_inputs()

         UpperCAmelCase__								=  processor(images=__UpperCAmelCase	,  visual_prompt=__UpperCAmelCase		)

         self.assertListEqual(list(inputs.keys()		)	,  ["pixel_values", "conditional_pixel_values"]		)

         # test if it raises when no input is passed
         with pytest.raises(__UpperCAmelCase		):
               processor()





   def       lowercase_				(self					:						str		)						->    str:
         """simple docstring"""



         UpperCAmelCase__								=  self.get_image_processor()
         UpperCAmelCase__								=  self.get_tokenizer()

         UpperCAmelCase__								=  CLIPSegProcessor(tokenizer=__UpperCAmelCase	,  image_processor=__UpperCAmelCase		)

         UpperCAmelCase__								=  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         UpperCAmelCase__								=  processor.batch_decode(__UpperCAmelCase		)
         UpperCAmelCase__								=  tokenizer.batch_decode(__UpperCAmelCase		)

         self.assertListEqual(__UpperCAmelCase	,  __UpperCAmelCase		)




import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


UpperCamelCase__    							= logging.get_logger(__name__)


UpperCamelCase__    							= {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all BART models at https://huggingface.co/models?filter=bart
UpperCamelCase__    							= {
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json',
    },
}

UpperCamelCase__    							= {
    'facebook/bart-base': 1_0_2_4,
    'facebook/bart-large': 1_0_2_4,
    'facebook/bart-large-mnli': 1_0_2_4,
    'facebook/bart-large-cnn': 1_0_2_4,
    'facebook/bart-large-xsum': 1_0_2_4,
    'yjernite/bart_eli5': 1_0_2_4,
}





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			List[str]              =      VOCAB_FILES_NAMES
   __UpperCAmelCase			:			int              =      PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase			:			int              =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase			:			str              =      ['input_ids', 'attention_mask']
   __UpperCAmelCase			:			str              =      BartTokenizer


   def __init__(self					:						Tuple	,  __UpperCAmelCase					:						int=None	,  __UpperCAmelCase					:						Optional[int]=None	,  __UpperCAmelCase					:						int=None	,  __UpperCAmelCase					:						str="replace"	,  __UpperCAmelCase					:						List[str]="<s>"	,  __UpperCAmelCase					:						Tuple="</s>"	,  __UpperCAmelCase					:						List[Any]="</s>"	,  __UpperCAmelCase					:						Tuple="<s>"	,  __UpperCAmelCase					:						List[str]="<unk>"	,  __UpperCAmelCase					:						Optional[int]="<pad>"	,  __UpperCAmelCase					:						List[Any]="<mask>"	,  __UpperCAmelCase					:						Any=False	,  __UpperCAmelCase					:						str=True	,  **__UpperCAmelCase					:						Tuple	,  )						->    Any:
         """simple docstring"""



         super().__init__(
             __UpperCAmelCase	,  __UpperCAmelCase	,  tokenizer_file=__UpperCAmelCase	,  errors=__UpperCAmelCase	,  bos_token=__UpperCAmelCase	,  eos_token=__UpperCAmelCase	,  sep_token=__UpperCAmelCase	,  cls_token=__UpperCAmelCase	,  unk_token=__UpperCAmelCase	,  pad_token=__UpperCAmelCase	,  mask_token=__UpperCAmelCase	,  add_prefix_space=__UpperCAmelCase	,  trim_offsets=__UpperCAmelCase	,  **__UpperCAmelCase	,  )

         UpperCAmelCase__								=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
         if pre_tok_state.get("add_prefix_space"	,  __UpperCAmelCase		) != add_prefix_space:
               UpperCAmelCase__								=  getattr(__UpperCAmelCase	,  pre_tok_state.pop("type"		)		)
               UpperCAmelCase__								=  add_prefix_space
               UpperCAmelCase__								=  pre_tok_class(**__UpperCAmelCase		)

         UpperCAmelCase__								=  add_prefix_space

         # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
         UpperCAmelCase__								=  "post_processor"
         UpperCAmelCase__								=  getattr(self.backend_tokenizer	,  __UpperCAmelCase	,  __UpperCAmelCase		)
         if tokenizer_component_instance:
               UpperCAmelCase__								=  json.loads(tokenizer_component_instance.__getstate__()		)

               # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
               if "sep" in state:
                     UpperCAmelCase__								=  tuple(state["sep"]		)
               if "cls" in state:
                     UpperCAmelCase__								=  tuple(state["cls"]		)

               UpperCAmelCase__								=  False

               if state.get("add_prefix_space"	,  __UpperCAmelCase		) != add_prefix_space:
                     UpperCAmelCase__								=  add_prefix_space
                     UpperCAmelCase__								=  True

               if state.get("trim_offsets"	,  __UpperCAmelCase		) != trim_offsets:
                     UpperCAmelCase__								=  trim_offsets
                     UpperCAmelCase__								=  True

               if changes_to_apply:
                     UpperCAmelCase__								=  getattr(__UpperCAmelCase	,  state.pop("type"		)		)
                     UpperCAmelCase__								=  component_class(**__UpperCAmelCase		)
                     setattr(self.backend_tokenizer	,  __UpperCAmelCase	,  __UpperCAmelCase		)


   @property
   def       lowercase_				(self					:						Tuple		)						->    str:
         """simple docstring"""



         if self._mask_token is None:
               if self.verbose:
                     logger.error("Using mask_token, but it is not set yet."		)
               return None
         return str(self._mask_token		)


   @mask_token.setter
   def       lowercase_				(self					:						Optional[int]	,  __UpperCAmelCase					:						Union[str, Any]		)						->    Tuple:
         """simple docstring"""



         UpperCAmelCase__								=  AddedToken(__UpperCAmelCase	,  lstrip=__UpperCAmelCase	,  rstrip=__UpperCAmelCase		) if isinstance(__UpperCAmelCase	,  __UpperCAmelCase		) else value
         UpperCAmelCase__								=  value


   def       lowercase_				(self					:						List[str]	,  *__UpperCAmelCase					:						str	,  **__UpperCAmelCase					:						List[str]		)						->    BatchEncoding:
         """simple docstring"""



         UpperCAmelCase__								=  kwargs.get("is_split_into_words"	,  __UpperCAmelCase		)

         if is_split_into_words and not self.add_prefix_space:
               raise ValueError(
                   f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
                   "to use it with pretokenized inputs."		)

         return super()._batch_encode_plus(*__UpperCAmelCase	,  **__UpperCAmelCase		)


   def       lowercase_				(self					:						List[Any]	,  *__UpperCAmelCase					:						Optional[Any]	,  **__UpperCAmelCase					:						Optional[Any]		)						->    BatchEncoding:
         """simple docstring"""



         UpperCAmelCase__								=  kwargs.get("is_split_into_words"	,  __UpperCAmelCase		)

         if is_split_into_words and not self.add_prefix_space:
               raise ValueError(
                   f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
                   "to use it with pretokenized inputs."		)

         return super()._encode_plus(*__UpperCAmelCase	,  **__UpperCAmelCase		)


   def       lowercase_				(self					:						Any	,  __UpperCAmelCase					:						str	,  __UpperCAmelCase					:						Optional[str] = None		)						->    Tuple[str]:
         """simple docstring"""



         UpperCAmelCase__								=  self._tokenizer.model.save(__UpperCAmelCase	,  name=__UpperCAmelCase		)
         return tuple(__UpperCAmelCase		)


   def       lowercase_				(self					:						Optional[Any]	,  __UpperCAmelCase					:						int	,  __UpperCAmelCase					:						Dict=None		)						->    Optional[int]:
         """simple docstring"""



         UpperCAmelCase__								=  [self.bos_token_id] + token_ids_a + [self.eos_token_id]
         if token_ids_a is None:
               return output

         return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





   def       lowercase_				(self					:						Union[str, Any]	,  __UpperCAmelCase					:						List[int]	,  __UpperCAmelCase					:						Optional[List[int]] = None		)						->    List[int]:
         """simple docstring"""



         UpperCAmelCase__								=  [self.sep_token_id]
         UpperCAmelCase__								=  [self.cls_token_id]

         if token_ids_a is None:
               return len(cls + token_ids_a + sep		) * [0]
         return len(cls + token_ids_a + sep + sep + token_ids_a + sep		) * [0]



