

'''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 CLIPImageProcessor, CLIPProcessor





@require_vision
class 							_snake_case (       unittest.TestCase						):
   def     __UpperCamelCase						( self			:      Union[str, Any]							):
     SCREAMING_SNAKE_CASE:Tuple						      =					tempfile.mkdtemp()

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

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

     SCREAMING_SNAKE_CASE:Optional[Any]						      =					{
         "do_resize": True,
         "size": 20,
         "do_center_crop": True,
         "crop_size": 18,
         "do_normalize": True,
         "image_mean": [0.48_145_466, 0.4_578_275, 0.40_821_073],
         "image_std": [0.26_862_954, 0.26_130_258, 0.27_577_711],
     }
     SCREAMING_SNAKE_CASE:int						      =					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			:      int     ,**SCREAMING_SNAKE_CASE__			:      List[str]							):
     return CLIPTokenizer.from_pretrained(self.tmpdirname     ,**SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      Tuple     ,**SCREAMING_SNAKE_CASE__			:      Any							):
     return CLIPTokenizerFast.from_pretrained(self.tmpdirname     ,**SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      Union[str, Any]     ,**SCREAMING_SNAKE_CASE__			:      Any							):
     return CLIPImageProcessor.from_pretrained(self.tmpdirname     ,**SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      Optional[int]							):
     shutil.rmtree(self.tmpdirname							)
   def     __UpperCamelCase						( self			:      List[Any]							):
     SCREAMING_SNAKE_CASE:Optional[int]						      =					[np.random.randint(255     ,size=(3, 30, 400)     ,dtype=np.uinta							)]

     SCREAMING_SNAKE_CASE:Optional[int]						      =					[Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE__     ,0     ,-1							)							) for x in image_inputs]

     return image_inputs
   def     __UpperCamelCase						( self			:      int							):
     SCREAMING_SNAKE_CASE:str						      =					self.get_tokenizer()
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					self.get_rust_tokenizer()
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					self.get_image_processor()

     SCREAMING_SNAKE_CASE:Any						      =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__     ,image_processor=SCREAMING_SNAKE_CASE__							)
     processor_slow.save_pretrained(self.tmpdirname							)
     SCREAMING_SNAKE_CASE:Optional[int]						      =					CLIPProcessor.from_pretrained(self.tmpdirname     ,use_fast=SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:Optional[int]						      =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__     ,image_processor=SCREAMING_SNAKE_CASE__							)
     processor_fast.save_pretrained(self.tmpdirname							)
     SCREAMING_SNAKE_CASE:str						      =					CLIPProcessor.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			:      List[Any]							):
     SCREAMING_SNAKE_CASE:Optional[int]						      =					CLIPProcessor(tokenizer=self.get_tokenizer()     ,image_processor=self.get_image_processor()							)
     processor.save_pretrained(self.tmpdirname							)

     SCREAMING_SNAKE_CASE:Dict						      =					self.get_tokenizer(bos_token="(BOS)"     ,eos_token="(EOS)"							)
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE__     ,padding_value=1.0							)

     SCREAMING_SNAKE_CASE:Any						      =					CLIPProcessor.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			:      Union[str, Any]							):
     SCREAMING_SNAKE_CASE:Any						      =					self.get_image_processor()
     SCREAMING_SNAKE_CASE:Dict						      =					self.get_tokenizer()

     SCREAMING_SNAKE_CASE:List[str]						      =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__     ,image_processor=SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:List[Any]						      =					self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE:Optional[Any]						      =					image_processor(SCREAMING_SNAKE_CASE__     ,return_tensors="np"							)
     SCREAMING_SNAKE_CASE:Dict						      =					processor(images=SCREAMING_SNAKE_CASE__     ,return_tensors="np"							)

     for key in input_image_proc.keys():
       self.assertAlmostEqual(input_image_proc[key].sum()     ,input_processor[key].sum()     ,delta=1e-2							)
   def     __UpperCamelCase						( self			:      Dict							):
     SCREAMING_SNAKE_CASE:Tuple						      =					self.get_image_processor()
     SCREAMING_SNAKE_CASE:int						      =					self.get_tokenizer()

     SCREAMING_SNAKE_CASE:Dict						      =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__     ,image_processor=SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:Optional[int]						      =					"lower newer"

     SCREAMING_SNAKE_CASE:List[str]						      =					processor(text=SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:Optional[Any]						      =					tokenizer(SCREAMING_SNAKE_CASE__							)

     for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key]     ,encoded_processor[key]							)
   def     __UpperCamelCase						( self			:      List[Any]							):
     SCREAMING_SNAKE_CASE:Tuple						      =					self.get_image_processor()
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					self.get_tokenizer()

     SCREAMING_SNAKE_CASE:List[Any]						      =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__     ,image_processor=SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:str						      =					"lower newer"
     SCREAMING_SNAKE_CASE:Dict						      =					self.prepare_image_inputs()

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

     SCREAMING_SNAKE_CASE:Any						      =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__     ,image_processor=SCREAMING_SNAKE_CASE__							)

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

     SCREAMING_SNAKE_CASE:Any						      =					processor.batch_decode(SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE:Dict						      =					tokenizer.batch_decode(SCREAMING_SNAKE_CASE__							)

     self.assertListEqual(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)







   def     __UpperCamelCase						( self			:      Any							):
     SCREAMING_SNAKE_CASE:Any						      =					self.get_image_processor()
     SCREAMING_SNAKE_CASE:Any						      =					self.get_tokenizer()

     SCREAMING_SNAKE_CASE:Dict						      =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__     ,image_processor=SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:Dict						      =					"lower newer"
     SCREAMING_SNAKE_CASE:Any						      =					self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE:str						      =					processor(text=SCREAMING_SNAKE_CASE__     ,images=SCREAMING_SNAKE_CASE__							)

     self.assertListEqual(list(inputs.keys()							)     ,processor.model_input_names							)









'''simple docstring'''

from math import factorial





def    A_  ( snake_case      ,       snake_case ):

  # If either of the conditions are true, the function is being asked
  # to calculate a factorial of a negative number, which is not possible
  if n < k or k < 0:
    raise ValueError("Please enter positive integers for n and k where n >= k" )
  return factorial(snake_case ) // (factorial(snake_case ) * factorial(n - k ))


if __name__ == "__main__":
    print(
        "The number of five-card hands possible from a standard",
        f'''fifty-two card deck is: {combinations(52, 5)}\n''',
    )

    print(
        "If a class of 40 students must be arranged into groups of",
        f'''4 for group projects, there are {combinations(40, 4)} ways''',
        "to arrange them.\n",
    )

    print(
        "If 10 teams are competing in a Formula One race, there",
        f'''are {combinations(10, 3)} ways that first, second and''',
        "third place can be awarded.",
    )






