'''simple docstring'''






import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
    import torch


if is_vision_available():
    from PIL import Image

    from transformers import MgpstrProcessor, ViTImageProcessor




@require_torch
@require_vision
class    a (       unittest.TestCase				):



  """simple docstring"""
  __lowerCAmelCase				      =					ViTImageProcessor if is_vision_available() else None







  @property
  def    lowercase_  (							self					):

    '''simple docstring'''







    return self.image_processor_tester.prepare_image_processor_dict()







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					Optional[int]		= (3, 32, 128)
    __UpperCAmelCase:					Union[str, Any]		= tempfile.mkdtemp()

    # fmt: off
    __UpperCAmelCase:					List[Any]		= ["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
    # fmt: on
    __UpperCAmelCase:					Optional[int]		= dict(zip(snake_case_   ,    range(len(snake_case_					)					)					)					)

    __UpperCAmelCase:					int		= os.path.join(self.tmpdirname   ,    VOCAB_FILES_NAMES["""vocab_file"""]					)
    with open(self.vocab_file   ,    """w"""   ,    encoding="""utf-8"""					) as fp:
      fp.write(json.dumps(snake_case_					) + """\n"""					)

    __UpperCAmelCase:					List[str]		= {
        """do_normalize""": False,
        """do_resize""": True,
        """image_processor_type""": """ViTImageProcessor""",
        """resample""": 3,
        """size""": {"""height""": 32, """width""": 128},
    }
    __UpperCAmelCase:					List[str]		= os.path.join(self.tmpdirname   ,    snake_case_					)
    with open(self.image_processor_file   ,    """w"""   ,    encoding="""utf-8"""					) as fp:
      json.dump(snake_case_   ,    snake_case_					)







  def    lowercase_  (							self   ,    **snake_case_					):

    '''simple docstring'''







    return MgpstrTokenizer.from_pretrained(self.tmpdirname   ,    **snake_case_					)







  def    lowercase_  (							self   ,    **snake_case_					):

    '''simple docstring'''







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







  def    lowercase_  (							self					):

    '''simple docstring'''







    shutil.rmtree(self.tmpdirname					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					List[Any]		= np.random.randint(255   ,    size=(3, 30, 400)   ,    dtype=np.uinta					)

    __UpperCAmelCase:					Union[str, Any]		= Image.fromarray(np.moveaxis(snake_case_   ,    0   ,    -1					)					)

    return image_input







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					Dict		= self.get_tokenizer()
    __UpperCAmelCase:					str		= self.get_image_processor()

    __UpperCAmelCase:					List[Any]		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)
    processor.save_pretrained(self.tmpdirname					)
    __UpperCAmelCase:					Tuple		= MgpstrProcessor.from_pretrained(self.tmpdirname   ,    use_fast=snake_case_					)

    self.assertEqual(processor.char_tokenizer.get_vocab()   ,    tokenizer.get_vocab()					)
    self.assertIsInstance(processor.char_tokenizer   ,    snake_case_					)

    self.assertEqual(processor.image_processor.to_json_string()   ,    image_processor.to_json_string()					)
    self.assertIsInstance(processor.image_processor   ,    snake_case_					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					str		= self.get_tokenizer()
    __UpperCAmelCase:					int		= self.get_image_processor()

    __UpperCAmelCase:					List[Any]		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)
    processor.save_pretrained(self.tmpdirname					)

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

    __UpperCAmelCase:					Dict		= MgpstrProcessor.from_pretrained(
        self.tmpdirname   ,    bos_token="""(BOS)"""   ,    eos_token="""(EOS)"""   ,    do_normalize=snake_case_   ,    padding_value=1.0					)

    self.assertEqual(processor.char_tokenizer.get_vocab()   ,    tokenizer_add_kwargs.get_vocab()					)
    self.assertIsInstance(processor.char_tokenizer   ,    snake_case_					)

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







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					List[Any]		= self.get_image_processor()
    __UpperCAmelCase:					Any		= self.get_tokenizer()

    __UpperCAmelCase:					Optional[Any]		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)

    __UpperCAmelCase:					Tuple		= self.prepare_image_inputs()

    __UpperCAmelCase:					Optional[Any]		= image_processor(snake_case_   ,    return_tensors="""np"""					)
    __UpperCAmelCase:					Optional[int]		= processor(images=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    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					Any		= self.get_image_processor()
    __UpperCAmelCase:					Any		= self.get_tokenizer()

    __UpperCAmelCase:					Optional[Any]		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)

    __UpperCAmelCase:					Optional[int]		= """test"""

    __UpperCAmelCase:					Optional[int]		= processor(text=snake_case_					)

    __UpperCAmelCase:					Any		= tokenizer(snake_case_					)
    for key in encoded_tok.keys():
      self.assertListEqual(encoded_tok[key]   ,    encoded_processor[key]					)







  def    lowercase_  (							self					):

    '''simple docstring'''







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

    __UpperCAmelCase:					Optional[int]		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)

    __UpperCAmelCase:					Tuple		= """test"""
    __UpperCAmelCase:					Tuple		= self.prepare_image_inputs()

    __UpperCAmelCase:					Optional[Any]		= processor(text=snake_case_   ,    images=snake_case_					)

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

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







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					Optional[Any]		= self.get_image_processor()
    __UpperCAmelCase:					Tuple		= self.get_tokenizer()

    __UpperCAmelCase:					Union[str, Any]		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)

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

    __UpperCAmelCase:					str		= processor.char_decode(snake_case_					)
    __UpperCAmelCase:					Optional[Any]		= tokenizer.batch_decode(snake_case_					)
    __UpperCAmelCase:					List[Any]		= [seq.replace(""" """   ,    """"""					) for seq in decoded_tok]

    self.assertListEqual(snake_case_   ,    snake_case_					)







  def    lowercase_  (							self					):

    '''simple docstring'''







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

    __UpperCAmelCase:					Tuple		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)

    __UpperCAmelCase:					List[Any]		= None
    __UpperCAmelCase:					List[Any]		= self.prepare_image_inputs()

    __UpperCAmelCase:					List[str]		= processor(text=snake_case_   ,    images=snake_case_					)

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







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					str		= self.get_image_processor()
    __UpperCAmelCase:					Dict		= self.get_tokenizer()

    __UpperCAmelCase:					Dict		= MgpstrProcessor(tokenizer=snake_case_   ,    image_processor=snake_case_					)

    __UpperCAmelCase:					Union[str, Any]		= torch.randn(1   ,    27   ,    38					)
    __UpperCAmelCase:					List[str]		= torch.randn(1   ,    27   ,    5_0257					)
    __UpperCAmelCase:					Union[str, Any]		= torch.randn(1   ,    27   ,    3_0522					)

    __UpperCAmelCase:					Tuple		= processor.batch_decode([char_input, bpe_input, wp_input]					)

    self.assertListEqual(list(results.keys()					)   ,    ["""generated_text""", """scores""", """char_preds""", """bpe_preds""", """wp_preds"""]					)
'''simple docstring'''






def  UpperCamelCase__					(					_lowercase    :				list     )							->	list:
  if len(_lowercase     ) <= 1:
    return lst

  __UpperCAmelCase:					List[str]		= 1

  while i < len(_lowercase     ):
    if lst[i - 1] <= lst[i]:
      i += 1
    else:
      __UpperCAmelCase, __UpperCAmelCase:					Tuple		= lst[i], lst[i - 1]
      i -= 1
      if i == 0:
        __UpperCAmelCase:					List[str]		= 1

  return lst


if __name__ == "__main__":
    SCREAMING_SNAKE_CASE_	   =			input('Enter numbers separated by a comma:\n').strip()
    SCREAMING_SNAKE_CASE_	   =			[int(item) for item in user_input.split(',')]
    print(gnome_sort(unsorted))