



"""simple docstring"""
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    SCREAMING_SNAKE_CASE__						(      unittest.TestCase				):

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





    '''simple docstring'''




    UpperCAmelCase			:      Tuple			=			tempfile.mkdtemp()

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

    UpperCAmelCase			:      int			=			os.path.join(self.tmpdirname   ,  VOCAB_FILES_NAMES["""vocab_file"""]		)
    UpperCAmelCase			:      Dict			=			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(_SCREAMING_SNAKE_CASE		) + """\n"""		)
    with open(self.merges_file   ,  """w"""   ,  encoding="""utf-8"""		) as fp:
     fp.write("""\n""".join(_SCREAMING_SNAKE_CASE		)		)

    UpperCAmelCase			:      int			=			{
        """do_resize""": True,
        """size""": 20,
        """do_center_crop""": True,
        """crop_size""": 18,
        """do_normalize""": True,
        """image_mean""": [0.4814_5466, 0.457_8275, 0.4082_1073],
        """image_std""": [0.2686_2954, 0.2613_0258, 0.2757_7711],
    }
    UpperCAmelCase			:      str			=			os.path.join(self.tmpdirname   ,  _SCREAMING_SNAKE_CASE		)
    with open(self.image_processor_file   ,  """w"""   ,  encoding="""utf-8"""		) as fp:
     json.dump(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  **_SCREAMING_SNAKE_CASE		)						->   Tuple:





    '''simple docstring'''




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

   def 			SCREAMING_SNAKE_CASE  (     self   ,  **_SCREAMING_SNAKE_CASE		)						->   Optional[int]:





    '''simple docstring'''




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

   def 			SCREAMING_SNAKE_CASE  (     self   ,  **_SCREAMING_SNAKE_CASE		)						->   Optional[Any]:





    '''simple docstring'''




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

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





    '''simple docstring'''




    shutil.rmtree(self.tmpdirname		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    UpperCAmelCase			:      Tuple			=			[np.random.randint(255   ,  size=(3, 30, 400)   ,  dtype=np.uinta		)]

    UpperCAmelCase			:      str			=			[Image.fromarray(np.moveaxis(_SCREAMING_SNAKE_CASE   ,  0   ,  -1		)		) for x in image_inputs]

    return image_inputs

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





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			self.get_tokenizer()
    UpperCAmelCase			:      Tuple			=			self.get_rust_tokenizer()
    UpperCAmelCase			:      Any			=			self.get_image_processor()

    UpperCAmelCase			:      str			=			CLIPSegProcessor(tokenizer=_SCREAMING_SNAKE_CASE   ,  image_processor=_SCREAMING_SNAKE_CASE		)
    processor_slow.save_pretrained(self.tmpdirname		)
    UpperCAmelCase			:      Optional[Any]			=			CLIPSegProcessor.from_pretrained(self.tmpdirname   ,  use_fast=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      Optional[Any]			=			CLIPSegProcessor(tokenizer=_SCREAMING_SNAKE_CASE   ,  image_processor=_SCREAMING_SNAKE_CASE		)
    processor_fast.save_pretrained(self.tmpdirname		)
    UpperCAmelCase			:      Optional[int]			=			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   ,  _SCREAMING_SNAKE_CASE		)
    self.assertIsInstance(processor_fast.tokenizer   ,  _SCREAMING_SNAKE_CASE		)

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

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





    '''simple docstring'''




    UpperCAmelCase			:      Union[str, Any]			=			CLIPSegProcessor(tokenizer=self.get_tokenizer()   ,  image_processor=self.get_image_processor()		)
    processor.save_pretrained(self.tmpdirname		)

    UpperCAmelCase			:      int			=			self.get_tokenizer(bos_token="""(BOS)"""   ,  eos_token="""(EOS)"""		)
    UpperCAmelCase			:      Optional[Any]			=			self.get_image_processor(do_normalize=_SCREAMING_SNAKE_CASE   ,  padding_value=1.0		)

    UpperCAmelCase			:      str			=			CLIPSegProcessor.from_pretrained(
        self.tmpdirname   ,  bos_token="""(BOS)"""   ,  eos_token="""(EOS)"""   ,  do_normalize=_SCREAMING_SNAKE_CASE   ,  padding_value=1.0		)

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

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

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




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

    UpperCAmelCase			:      List[Any]			=			CLIPSegProcessor(tokenizer=_SCREAMING_SNAKE_CASE   ,  image_processor=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      Tuple			=			self.prepare_image_inputs()

    UpperCAmelCase			:      Tuple			=			image_processor(_SCREAMING_SNAKE_CASE   ,  return_tensors="""np"""		)
    UpperCAmelCase			:      Optional[Any]			=			processor(images=_SCREAMING_SNAKE_CASE   ,  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 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			self.get_image_processor()
    UpperCAmelCase			:      str			=			self.get_tokenizer()

    UpperCAmelCase			:      Tuple			=			CLIPSegProcessor(tokenizer=_SCREAMING_SNAKE_CASE   ,  image_processor=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      str			=			"""lower newer"""

    UpperCAmelCase			:      Dict			=			processor(text=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      int			=			tokenizer(_SCREAMING_SNAKE_CASE		)

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

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Dict:





    '''simple docstring'''




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

    UpperCAmelCase			:      Any			=			CLIPSegProcessor(tokenizer=_SCREAMING_SNAKE_CASE   ,  image_processor=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      Optional[int]			=			"""lower newer"""
    UpperCAmelCase			:      List[str]			=			self.prepare_image_inputs()

    UpperCAmelCase			:      Dict			=			processor(text=_SCREAMING_SNAKE_CASE   ,  images=_SCREAMING_SNAKE_CASE		)

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

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

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





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			self.get_image_processor()
    UpperCAmelCase			:      Optional[Any]			=			self.get_tokenizer()

    UpperCAmelCase			:      List[Any]			=			CLIPSegProcessor(tokenizer=_SCREAMING_SNAKE_CASE   ,  image_processor=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      Optional[Any]			=			self.prepare_image_inputs()
    UpperCAmelCase			:      Tuple			=			self.prepare_image_inputs()

    UpperCAmelCase			:      int			=			processor(images=_SCREAMING_SNAKE_CASE   ,  visual_prompt=_SCREAMING_SNAKE_CASE		)

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

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




   def 			SCREAMING_SNAKE_CASE  (     self		)						->   str:





    '''simple docstring'''




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

    UpperCAmelCase			:      Any			=			CLIPSegProcessor(tokenizer=_SCREAMING_SNAKE_CASE   ,  image_processor=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      int			=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

    UpperCAmelCase			:      List[Any]			=			processor.batch_decode(_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      Tuple			=			tokenizer.batch_decode(_SCREAMING_SNAKE_CASE		)

    self.assertListEqual(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)





"""simple docstring"""
from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

A:     List[Any]										=	(3, 9, -1_1, 0, 7, 5, 1, -1)
A:     Union[str, Any]										=	(4, 6, 2, 0, 8, 1_0, 3, -2)



@dataclass
class    SCREAMING_SNAKE_CASE__						:
   __lowerCAmelCase						:     int
   __lowerCAmelCase						:     Node | None



class    SCREAMING_SNAKE_CASE__						:

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   None:





    '''simple docstring'''




    UpperCAmelCase			:      Node | None			=			None
    for i in sorted(_SCREAMING_SNAKE_CASE   ,  reverse=_SCREAMING_SNAKE_CASE		):
     UpperCAmelCase			:      Union[str, Any]			=			Node(_SCREAMING_SNAKE_CASE   ,  self.head		)

   def __iter__(     self		)						->   Iterator[int]:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[Any]			=			self.head
    while node:
     yield node.data
     UpperCAmelCase			:      List[str]			=			node.next_node

   def __len__(     self		)						->   int:





    '''simple docstring'''




    return sum(1 for _ in self		)




   def __str__(     self		)						->   str:





    '''simple docstring'''




    return " -> ".join([str(_SCREAMING_SNAKE_CASE		) for node in self]		)

def    _snake_case		(		UpperCamelCase		:	SortedLinkedList    ,	UpperCamelCase		:	SortedLinkedList		):
 return SortedLinkedList(list(UpperCamelCase		) + list(UpperCamelCase		)		)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      A:     Dict										=	SortedLinkedList
      print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))
