





'''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 					__snake_case  (					unittest.TestCase							):






   '''simple docstring'''





   def 		__UpperCamelCase						(							self       ):
    snake_case__     :					str    =  tempfile.mkdtemp()

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

    snake_case__     :					List[str]    =  os.path.join(self.tmpdirname	,		VOCAB_FILES_NAMES["""vocab_file"""]       )
    snake_case__     :					List[str]    =  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       )       )

    snake_case__     :					Union[str, Any]    =  {
        """do_resize""": True,
        """size""": 2_0,
        """do_center_crop""": True,
        """crop_size""": 1_8,
        """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],
    }
    snake_case__     :					Tuple    =  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 		__UpperCamelCase						(							self	,		**__SCREAMING_SNAKE_CASE       ):
    return CLIPTokenizer.from_pretrained(self.tmpdirname	,		**__SCREAMING_SNAKE_CASE       )

   def 		__UpperCamelCase						(							self	,		**__SCREAMING_SNAKE_CASE       ):
    return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,		**__SCREAMING_SNAKE_CASE       )

   def 		__UpperCamelCase						(							self	,		**__SCREAMING_SNAKE_CASE       ):
    return ViTImageProcessor.from_pretrained(self.tmpdirname	,		**__SCREAMING_SNAKE_CASE       )

   def 		__UpperCamelCase						(							self       ):
    shutil.rmtree(self.tmpdirname       )

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

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

    return image_inputs

   def 		__UpperCamelCase						(							self       ):
    snake_case__     :					Union[str, Any]    =  self.get_tokenizer()
    snake_case__     :					Any    =  self.get_rust_tokenizer()
    snake_case__     :					Dict    =  self.get_image_processor()

    snake_case__     :					int    =  CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE	,		image_processor=__SCREAMING_SNAKE_CASE       )
    processor_slow.save_pretrained(self.tmpdirname       )
    snake_case__     :					List[Any]    =  CLIPSegProcessor.from_pretrained(self.tmpdirname	,		use_fast=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					Union[str, Any]    =  CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE	,		image_processor=__SCREAMING_SNAKE_CASE       )
    processor_fast.save_pretrained(self.tmpdirname       )
    snake_case__     :					str    =  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 		__UpperCamelCase						(							self       ):
    snake_case__     :					Dict    =  CLIPSegProcessor(tokenizer=self.get_tokenizer()	,		image_processor=self.get_image_processor()       )
    processor.save_pretrained(self.tmpdirname       )

    snake_case__     :					Union[str, Any]    =  self.get_tokenizer(bos_token="""(BOS)"""	,		eos_token="""(EOS)"""       )
    snake_case__     :					Optional[int]    =  self.get_image_processor(do_normalize=__SCREAMING_SNAKE_CASE	,		padding_value=1.0       )

    snake_case__     :					List[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 		__UpperCamelCase						(							self       ):
    snake_case__     :					Optional[int]    =  self.get_image_processor()
    snake_case__     :					str    =  self.get_tokenizer()

    snake_case__     :					str    =  CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE	,		image_processor=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					Optional[int]    =  self.prepare_image_inputs()

    snake_case__     :					Optional[Any]    =  image_processor(__SCREAMING_SNAKE_CASE	,		return_tensors="""np"""       )
    snake_case__     :					Union[str, 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 		__UpperCamelCase						(							self       ):
    snake_case__     :					str    =  self.get_image_processor()
    snake_case__     :					Dict    =  self.get_tokenizer()

    snake_case__     :					int    =  CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE	,		image_processor=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					str    =  """lower newer"""

    snake_case__     :					List[Any]    =  processor(text=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					List[Any]    =  tokenizer(__SCREAMING_SNAKE_CASE       )

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

   def 		__UpperCamelCase						(							self       ):
    snake_case__     :					Dict    =  self.get_image_processor()
    snake_case__     :					Union[str, Any]    =  self.get_tokenizer()

    snake_case__     :					Union[str, Any]    =  CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE	,		image_processor=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					List[str]    =  """lower newer"""
    snake_case__     :					str    =  self.prepare_image_inputs()

    snake_case__     :					Optional[int]    =  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 		__UpperCamelCase						(							self       ):
    snake_case__     :					List[Any]    =  self.get_image_processor()
    snake_case__     :					List[str]    =  self.get_tokenizer()

    snake_case__     :					Dict    =  CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE	,		image_processor=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					int    =  self.prepare_image_inputs()
    snake_case__     :					Optional[int]    =  self.prepare_image_inputs()

    snake_case__     :					Dict    =  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 		__UpperCamelCase						(							self       ):
    snake_case__     :					Dict    =  self.get_image_processor()
    snake_case__     :					Dict    =  self.get_tokenizer()

    snake_case__     :					int    =  CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE	,		image_processor=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					Tuple    =  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

    snake_case__     :					Tuple    =  processor.batch_decode(__SCREAMING_SNAKE_CASE       )
    snake_case__     :					Optional[Any]    =  tokenizer.batch_decode(__SCREAMING_SNAKE_CASE       )

    self.assertListEqual(__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       )






def      UpperCamelCase   (       __lowerCamelCase	:					int = 1							,   __lowerCamelCase	:					int = 1000       ):
       snake_case			:  int     							= 1
       snake_case			:  int     							= 0

       for divide_by_number in range(__lowerCamelCase							,   digit + 1       ):
              snake_case			:  list[int]     							= []
              snake_case			:  Optional[int]     							= numerator
              for _ in range(1							,   digit + 1       ):
                     if now_divide in has_been_divided:
                            if longest_list_length < len(__lowerCamelCase       ):
                                   snake_case			:  List[Any]     							= len(__lowerCamelCase       )
                                   snake_case			:  List[str]     							= divide_by_number
                     else:
                            has_been_divided.append(__lowerCamelCase       )
                            snake_case			:  Any     							= now_divide * 10 % divide_by_number

       return the_digit


# Tests
if __name__ == "__main__":
   import doctest

   doctest.testmod()





