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 __snake_case				(						unittest.TestCase		):
   lowerCAmelCase_														=							ViTImageProcessor if is_vision_available() else None




   @property
   def 	__a						(    self			:				Tuple      ):



     """simple docstring"""






     return self.image_processor_tester.prepare_image_processor_dict()




   def 	__a						(    self			:				List[str]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      (3, 32, 1_28)
     SCREAMING_SNAKE_CASE__										=      tempfile.mkdtemp()

     # fmt: off
     SCREAMING_SNAKE_CASE__										=      ["""[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
     SCREAMING_SNAKE_CASE__										=      dict(zip(_lowercase       ,	range(len(_lowercase      )      )      )      )

     SCREAMING_SNAKE_CASE__										=      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(_lowercase      ) + """\n"""      )

     SCREAMING_SNAKE_CASE__										=      {
         """do_normalize""": False,
         """do_resize""": True,
         """image_processor_type""": """ViTImageProcessor""",
         """resample""": 3,
         """size""": {"""height""": 32, """width""": 1_28},
     }
     SCREAMING_SNAKE_CASE__										=      os.path.join(self.tmpdirname       ,	_lowercase      )
     with open(self.image_processor_file       ,	"""w"""       ,	encoding="""utf-8"""      ) as fp:
       json.dump(_lowercase       ,	_lowercase      )




   def 	__a						(    self			:				Tuple       ,	**_lowercase			:				Any      ):



     """simple docstring"""






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




   def 	__a						(    self			:				List[Any]       ,	**_lowercase			:				Optional[Any]      ):



     """simple docstring"""






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




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     shutil.rmtree(self.tmpdirname      )




   def 	__a						(    self			:				Any      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      np.random.randint(2_55       ,	size=(3, 30, 4_00)       ,	dtype=np.uinta      )

     SCREAMING_SNAKE_CASE__										=      Image.fromarray(np.moveaxis(_lowercase       ,	0       ,	-1      )      )

     return image_input




   def 	__a						(    self			:				List[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()
     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )
     processor.save_pretrained(self.tmpdirname      )
     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor.from_pretrained(self.tmpdirname       ,	use_fast=_lowercase      )

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

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




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()
     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )
     processor.save_pretrained(self.tmpdirname      )

     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer(bos_token="""(BOS)"""       ,	eos_token="""(EOS)"""      )
     SCREAMING_SNAKE_CASE__										=      self.get_image_processor(do_normalize=_lowercase       ,	padding_value=1.0      )

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor.from_pretrained(
         self.tmpdirname       ,	bos_token="""(BOS)"""       ,	eos_token="""(EOS)"""       ,	do_normalize=_lowercase       ,	padding_value=1.0      )

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

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




   def 	__a						(    self			:				Union[str, Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE__										=      image_processor(_lowercase       ,	return_tensors="""np"""      )
     SCREAMING_SNAKE_CASE__										=      processor(images=_lowercase       ,	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 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      """test"""

     SCREAMING_SNAKE_CASE__										=      processor(text=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      tokenizer(_lowercase      )
     for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key]       ,	encoded_processor[key]      )




   def 	__a						(    self			:				List[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      """test"""
     SCREAMING_SNAKE_CASE__										=      self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE__										=      processor(text=_lowercase       ,	images=_lowercase      )

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

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




   def 	__a						(    self			:				Union[str, Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

     SCREAMING_SNAKE_CASE__										=      processor.char_decode(_lowercase      )
     SCREAMING_SNAKE_CASE__										=      tokenizer.batch_decode(_lowercase      )
     SCREAMING_SNAKE_CASE__										=      [seq.replace(""" """       ,	""""""      ) for seq in decoded_tok]

     self.assertListEqual(_lowercase       ,	_lowercase      )




   def 	__a						(    self			:				Any      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      None
     SCREAMING_SNAKE_CASE__										=      self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE__										=      processor(text=_lowercase       ,	images=_lowercase      )

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




   def 	__a						(    self			:				Any      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__										=      MgpstrProcessor(tokenizer=_lowercase       ,	image_processor=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      torch.randn(1       ,	27       ,	38      )
     SCREAMING_SNAKE_CASE__										=      torch.randn(1       ,	27       ,	5_02_57      )
     SCREAMING_SNAKE_CASE__										=      torch.randn(1       ,	27       ,	3_05_22      )

     SCREAMING_SNAKE_CASE__										=      processor.batch_decode([char_input, bpe_input, wp_input]      )

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

import socket



def 	__SCREAMING_SNAKE_CASE  (					)							->					Optional[int]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      socket.socket(socket.AF_INET ,     socket.SOCK_STREAM	)
  SCREAMING_SNAKE_CASE__										=      socket.gethostname()
  SCREAMING_SNAKE_CASE__										=      1_23_12

  sock.connect((host, port)	)
  sock.send(B"""Hello server!"""	)

  with open("""Received_file""" ,     """wb"""	) as out_file:
    print("""File opened"""	)
    print("""Receiving data..."""	)
    while True:
      SCREAMING_SNAKE_CASE__										=      sock.recv(10_24	)
      if not data:
        break
      out_file.write(__UpperCamelCase	)

  print("""Successfully received the file"""	)
  sock.close()
  print("""Connection closed"""	)


if __name__ == "__main__":
   main()
