





import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase	:	Optional[Any]		     =       logging.get_logger(__name__)


UpperCAmelCase	:	List[str]		     =       {
    """vocab_file""": """vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
    """merges_file""": """merges.txt""",
}

UpperCAmelCase	:	Any		     =       {
    """vocab_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"""
        ),
    },
    """tokenizer_config_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"""
        ),
    },
    """merges_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"""
        ),
    },
}

UpperCAmelCase	:	List[Any]		     =       """</w>"""
UpperCAmelCase	:	Tuple		     =       """@@ """
def      _A       (		SCREAMING_SNAKE_CASE     :   Optional[int]						):





  """simple docstring"""



  a__	:					Any										=set()
  a__	:					Union[str, Any]										=word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)						)
    a__	:					Any										=char
  return pairs


# Speech2Text2 has no max input length
UpperCAmelCase	:	Any		     =       {"""facebook/s2t-wav2vec2-large-en-de""": 1024}







class 				__lowerCAmelCase       (    UpperCamelCase__):
      _lowercase				:					str						=			VOCAB_FILES_NAMES
      _lowercase				:					Any						=			PRETRAINED_VOCAB_FILES_MAP
      _lowercase				:					List[Any]						=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowercase				:					Optional[int]						=			["""input_ids""", """attention_mask"""]







      def __init__(    self		,      lowerCAmelCase__		,      lowerCAmelCase__="<s>"		,      lowerCAmelCase__="<pad>"		,      lowerCAmelCase__="</s>"		,      lowerCAmelCase__="<unk>"		,      lowerCAmelCase__=False		,      lowerCAmelCase__=None		,      **lowerCAmelCase__		,      )   ->						Union[str, Any]:



        '''simple docstring'''




        super().__init__(
            unk_token=lowerCAmelCase__		,      bos_token=lowerCAmelCase__		,      eos_token=lowerCAmelCase__		,      pad_token=lowerCAmelCase__		,      do_lower_case=lowerCAmelCase__		,      **lowerCAmelCase__		,      )

        a__	:					Any										=do_lower_case

        with open(lowerCAmelCase__		,      encoding="utf-8"							) as vocab_handle:
          a__	:					Tuple										=json.load(lowerCAmelCase__							)
        a__	:					Any										={v: k for k, v in self.encoder.items()}

        if merges_file is None:
          logger.info(F'''No merges files provided. {self.__class__.__name__} can only be used for decoding.'''							)

          a__	:					List[Any]										=None
          a__	:					Tuple										=None
        else:
          with open(lowerCAmelCase__		,      encoding="utf-8"							) as merges_handle:
            a__	:					int										=merges_handle.read().split("\n"							)[:-1]

          a__	:					int										=[tuple(merge.split()[:2]							) for merge in merges]
          a__	:					Optional[int]										=dict(zip(lowerCAmelCase__		,      range(len(lowerCAmelCase__							)							)							)							)
          a__	:					Dict										={}







      @property
      def    _lowercase  (    self							)   ->						int:



        '''simple docstring'''




        return len(self.decoder							)







      def    _lowercase  (    self							)   ->						Dict:



        '''simple docstring'''




        return dict(self.encoder		,      **self.added_tokens_encoder							)







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						int:



        '''simple docstring'''




        a__	:					Any										=tuple(token[:-1]							) + (token[-1] + BPE_TOKEN_MERGES,)
        if token in self.cache:
          return self.cache[token]
        a__	:					Any										=get_pairs(lowerCAmelCase__							)

        if not pairs:
          return token

        while True:
          a__	:					str										=min(lowerCAmelCase__		,      key=lambda lowerCAmelCase__							: self.bpe_ranks.get(lowerCAmelCase__		,      float("inf"							)							)							)
          if bigram not in self.bpe_ranks:
            break
          a__					,							a__	:					List[str]										=bigram
          a__	:					Union[str, Any]										=[]
          a__	:					Optional[int]										=0
          while i < len(lowerCAmelCase__							):
            try:
              a__	:					Optional[int]										=word.index(lowerCAmelCase__		,      lowerCAmelCase__							)
            except ValueError:
              new_word.extend(word[i:]							)
              break
            else:
              new_word.extend(word[i:j]							)
              a__	:					List[Any]										=j

            if word[i] == first and i < len(lowerCAmelCase__							) - 1 and word[i + 1] == second:
              new_word.append(first + second							)
              i += 2
            else:
              new_word.append(word[i]							)
              i += 1
          a__	:					Dict										=tuple(lowerCAmelCase__							)
          a__	:					Dict										=new_word
          if len(lowerCAmelCase__							) == 1:
            break
          else:
            a__	:					Dict										=get_pairs(lowerCAmelCase__							)
        a__	:					str										=" ".join(lowerCAmelCase__							)
        if word == "\n  " + BPE_TOKEN_MERGES:
          a__	:					Any										="\n" + BPE_TOKEN_MERGES

        if word.endswith(lowerCAmelCase__							):
          a__	:					Dict										=word.replace(lowerCAmelCase__		,      ""							)

        a__	:					List[Any]										=word.replace(" "		,      lowerCAmelCase__							)
        a__	:					List[Any]										=word
        return word







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						List[Any]:



        '''simple docstring'''




        if self.bpe_ranks is None:
          raise ValueError(
              "This tokenizer was instantiated without a `merges.txt` file, so"
              " that it can only be used for decoding, not for encoding."
              "Make sure to provide `merges.txt` file at instantiation to enable "
              "encoding."							)

        if self.do_lower_case:
          a__	:					Optional[int]										=text.lower()

        a__	:					str										=text.split()

        a__	:					Union[str, Any]										=[]
        for token in text:
          if token:
            split_tokens.extend(list(self.bpe(lowerCAmelCase__							).split(" "							)							)							)

        return split_tokens







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						int:



        '''simple docstring'''




        return self.encoder.get(lowerCAmelCase__		,      self.encoder.get(self.unk_token							)							)







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						str:



        '''simple docstring'''




        a__	:					List[Any]										=self.decoder.get(lowerCAmelCase__		,      self.unk_token							)
        return result







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						str:



        '''simple docstring'''




        a__	:					Dict										=" ".join(lowerCAmelCase__							)

        # make sure @@ tokens are concatenated
        a__	:					Dict										="".join(string.split(lowerCAmelCase__							)							)

        return string







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None							)   ->						Tuple[str]:



        '''simple docstring'''




        if not os.path.isdir(lowerCAmelCase__							):
          logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
          return
        a__	:					Any										=os.path.join(
            lowerCAmelCase__		,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)
        a__	:					Optional[Any]										=os.path.join(
            lowerCAmelCase__		,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]							)

        with open(lowerCAmelCase__		,      "w"		,      encoding="utf-8"							) as f:
          f.write(json.dumps(self.encoder		,      indent=2		,      sort_keys=lowerCAmelCase__		,      ensure_ascii=lowerCAmelCase__							) + "\n"							)

        a__	:					Optional[Any]										=0
        if self.bpe_ranks is None:
          return (vocab_file,)

        with open(lowerCAmelCase__		,      "w"		,      encoding="utf-8"							) as writer:
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,      key=lambda lowerCAmelCase__							: kv[1]							):
            if index != token_index:
              logger.warning(
                  F'''Saving vocabulary to {merges_file}: BPE merge indices are not consecutive.'''
                  " Please check that the tokenizer is not corrupted!"							)
              a__	:					Tuple										=token_index
            writer.write(" ".join(lowerCAmelCase__							) + "\n"							)
            index += 1

        return (vocab_file, merges_file)













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 				__lowerCAmelCase       (    unittest.TestCase):







      def    _lowercase  (    self							)   ->						Dict:



        '''simple docstring'''




        a__	:					Any										=tempfile.mkdtemp()

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

        a__	:					Optional[Any]										=os.path.join(self.tmpdirname		,      VOCAB_FILES_NAMES["vocab_file"]							)
        a__	:					Tuple										=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__							)							)

        a__	:					Optional[Any]										={
            "do_resize": True,
            "size": 2_0,
            "do_center_crop": True,
            "crop_size": 1_8,
            "do_normalize": True,
            "image_mean": [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
            "image_std": [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
        }
        a__	:					Dict										=os.path.join(self.tmpdirname		,      lowerCAmelCase__							)
        with open(self.image_processor_file		,      "w"		,      encoding="utf-8"							) as fp:
          json.dump(lowerCAmelCase__		,      lowerCAmelCase__							)







      def    _lowercase  (    self		,      **lowerCAmelCase__							)   ->						Union[str, Any]:



        '''simple docstring'''




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







      def    _lowercase  (    self		,      **lowerCAmelCase__							)   ->						List[Any]:



        '''simple docstring'''




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







      def    _lowercase  (    self		,      **lowerCAmelCase__							)   ->						Any:



        '''simple docstring'''




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







      def    _lowercase  (    self							)   ->						Optional[int]:



        '''simple docstring'''




        shutil.rmtree(self.tmpdirname							)







      def    _lowercase  (    self							)   ->						Any:



        '''simple docstring'''




        a__	:					Optional[Any]										=[np.random.randint(2_5_5		,      size=(3, 3_0, 4_0_0)		,      dtype=np.uinta							)]

        a__	:					List[Any]										=[Image.fromarray(np.moveaxis(lowerCAmelCase__		,      0		,      -1							)							) for x in image_inputs]

        return image_inputs







      def    _lowercase  (    self							)   ->						Dict:



        '''simple docstring'''




        a__	:					Union[str, Any]										=self.get_tokenizer()
        a__	:					int										=self.get_rust_tokenizer()
        a__	:					List[str]										=self.get_image_processor()

        a__	:					Dict										=CLIPSegProcessor(tokenizer=lowerCAmelCase__		,      image_processor=lowerCAmelCase__							)
        processor_slow.save_pretrained(self.tmpdirname							)
        a__	:					Optional[Any]										=CLIPSegProcessor.from_pretrained(self.tmpdirname		,      use_fast=lowerCAmelCase__							)

        a__	:					Tuple										=CLIPSegProcessor(tokenizer=lowerCAmelCase__		,      image_processor=lowerCAmelCase__							)
        processor_fast.save_pretrained(self.tmpdirname							)
        a__	:					Dict										=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		,      lowerCAmelCase__							)
        self.assertIsInstance(processor_fast.tokenizer		,      lowerCAmelCase__							)

        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		,      lowerCAmelCase__							)
        self.assertIsInstance(processor_fast.image_processor		,      lowerCAmelCase__							)







      def    _lowercase  (    self							)   ->						Any:



        '''simple docstring'''




        a__	:					List[str]										=CLIPSegProcessor(tokenizer=self.get_tokenizer()		,      image_processor=self.get_image_processor()							)
        processor.save_pretrained(self.tmpdirname							)

        a__	:					str										=self.get_tokenizer(bos_token="(BOS)"		,      eos_token="(EOS)"							)
        a__	:					int										=self.get_image_processor(do_normalize=lowerCAmelCase__		,      padding_value=1.0							)

        a__	:					Optional[Any]										=CLIPSegProcessor.from_pretrained(
            self.tmpdirname		,      bos_token="(BOS)"		,      eos_token="(EOS)"		,      do_normalize=lowerCAmelCase__		,      padding_value=1.0							)

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

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







      def    _lowercase  (    self							)   ->						List[Any]:



        '''simple docstring'''




        a__	:					str										=self.get_image_processor()
        a__	:					Optional[int]										=self.get_tokenizer()

        a__	:					Dict										=CLIPSegProcessor(tokenizer=lowerCAmelCase__		,      image_processor=lowerCAmelCase__							)

        a__	:					str										=self.prepare_image_inputs()

        a__	:					Any										=image_processor(lowerCAmelCase__		,      return_tensors="np"							)
        a__	:					Optional[int]										=processor(images=lowerCAmelCase__		,      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							)   ->						Union[str, Any]:



        '''simple docstring'''




        a__	:					Optional[int]										=self.get_image_processor()
        a__	:					List[Any]										=self.get_tokenizer()

        a__	:					Optional[int]										=CLIPSegProcessor(tokenizer=lowerCAmelCase__		,      image_processor=lowerCAmelCase__							)

        a__	:					Union[str, Any]										="lower newer"

        a__	:					List[str]										=processor(text=lowerCAmelCase__							)

        a__	:					str										=tokenizer(lowerCAmelCase__							)

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







      def    _lowercase  (    self							)   ->						Optional[int]:



        '''simple docstring'''




        a__	:					Any										=self.get_image_processor()
        a__	:					Dict										=self.get_tokenizer()

        a__	:					Union[str, Any]										=CLIPSegProcessor(tokenizer=lowerCAmelCase__		,      image_processor=lowerCAmelCase__							)

        a__	:					Dict										="lower newer"
        a__	:					int										=self.prepare_image_inputs()

        a__	:					Any										=processor(text=lowerCAmelCase__		,      images=lowerCAmelCase__							)

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

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







      def    _lowercase  (    self							)   ->						str:



        '''simple docstring'''




        a__	:					Union[str, Any]										=self.get_image_processor()
        a__	:					Optional[Any]										=self.get_tokenizer()

        a__	:					str										=CLIPSegProcessor(tokenizer=lowerCAmelCase__		,      image_processor=lowerCAmelCase__							)

        a__	:					int										=self.prepare_image_inputs()
        a__	:					Union[str, Any]										=self.prepare_image_inputs()

        a__	:					Tuple										=processor(images=lowerCAmelCase__		,      visual_prompt=lowerCAmelCase__							)

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

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







      def    _lowercase  (    self							)   ->						Tuple:



        '''simple docstring'''




        a__	:					Optional[int]										=self.get_image_processor()
        a__	:					Any										=self.get_tokenizer()

        a__	:					Tuple										=CLIPSegProcessor(tokenizer=lowerCAmelCase__		,      image_processor=lowerCAmelCase__							)

        a__	:					Dict										=[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        a__	:					Optional[Any]										=processor.batch_decode(lowerCAmelCase__							)
        a__	:					Dict										=tokenizer.batch_decode(lowerCAmelCase__							)

        self.assertListEqual(lowerCAmelCase__		,      lowerCAmelCase__							)






