



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       _SCREAMING_SNAKE_CASE	(unittest.TestCase ):
     lowerCAmelCase					=			ViTImageProcessor if is_vision_available() else None





     @property
     def 	__snake_case    (       self :							Any				)->Optional[Any]:
      return self.image_processor_tester.prepare_image_processor_dict()





     def 	__snake_case    (       self :							Tuple				)->Optional[Any]:
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	(3, 3_2, 1_2_8)
      __SCREAMING_SNAKE_CASE       :    Tuple       =	tempfile.mkdtemp()

      # fmt: off
      __SCREAMING_SNAKE_CASE       :    Union[str, 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
      __SCREAMING_SNAKE_CASE       :    Tuple       =	dict(zip(UpperCamelCase     ,  range(len(UpperCamelCase				)				)				)				)

      __SCREAMING_SNAKE_CASE       :    List[str]       =	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(UpperCamelCase				) + "\n"				)

      __SCREAMING_SNAKE_CASE       :    str       =	{
          "do_normalize": False,
          "do_resize": True,
          "image_processor_type": "ViTImageProcessor",
          "resample": 3,
          "size": {"height": 3_2, "width": 1_2_8},
      }
      __SCREAMING_SNAKE_CASE       :    Tuple       =	os.path.join(self.tmpdirname     ,  UpperCamelCase				)
      with open(self.image_processor_file     ,  "w"     ,  encoding="utf-8"				) as fp:
       json.dump(UpperCamelCase     ,  UpperCamelCase				)





     def 	__snake_case    (       self :							Any     ,  **UpperCamelCase :							Any				)->List[str]:
      return MgpstrTokenizer.from_pretrained(self.tmpdirname     ,  **UpperCamelCase				)





     def 	__snake_case    (       self :							Any     ,  **UpperCamelCase :							List[str]				)->Union[str, Any]:
      return ViTImageProcessor.from_pretrained(self.tmpdirname     ,  **UpperCamelCase				)





     def 	__snake_case    (       self :							List[str]				)->int:
      shutil.rmtree(self.tmpdirname				)





     def 	__snake_case    (       self :							List[Any]				)->Tuple:
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	np.random.randint(2_5_5     ,  size=(3, 3_0, 4_0_0)     ,  dtype=np.uinta				)

      __SCREAMING_SNAKE_CASE       :    Any       =	Image.fromarray(np.moveaxis(UpperCamelCase     ,  0     ,  -1				)				)

      return image_input





     def 	__snake_case    (       self :							List[str]				)->Dict:
      __SCREAMING_SNAKE_CASE       :    Tuple       =	self.get_tokenizer()
      __SCREAMING_SNAKE_CASE       :    Tuple       =	self.get_image_processor()

      __SCREAMING_SNAKE_CASE       :    Dict       =	MgpstrProcessor(tokenizer=UpperCamelCase     ,  image_processor=UpperCamelCase				)
      processor.save_pretrained(self.tmpdirname				)
      __SCREAMING_SNAKE_CASE       :    Dict       =	MgpstrProcessor.from_pretrained(self.tmpdirname     ,  use_fast=UpperCamelCase				)

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

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





     def 	__snake_case    (       self :							Union[str, Any]				)->Optional[Any]:
      __SCREAMING_SNAKE_CASE       :    str       =	self.get_tokenizer()
      __SCREAMING_SNAKE_CASE       :    Dict       =	self.get_image_processor()

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

      __SCREAMING_SNAKE_CASE       :    Any       =	self.get_tokenizer(bos_token="(BOS)"     ,  eos_token="(EOS)"				)
      __SCREAMING_SNAKE_CASE       :    List[str]       =	self.get_image_processor(do_normalize=UpperCamelCase     ,  padding_value=1.0				)

      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	MgpstrProcessor.from_pretrained(
          self.tmpdirname     ,  bos_token="(BOS)"     ,  eos_token="(EOS)"     ,  do_normalize=UpperCamelCase     ,  padding_value=1.0				)

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

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





     def 	__snake_case    (       self :							List[Any]				)->Dict:
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	self.get_image_processor()
      __SCREAMING_SNAKE_CASE       :    Any       =	self.get_tokenizer()

      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	MgpstrProcessor(tokenizer=UpperCamelCase     ,  image_processor=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	self.prepare_image_inputs()

      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	image_processor(UpperCamelCase     ,  return_tensors="np"				)
      __SCREAMING_SNAKE_CASE       :    Any       =	processor(images=UpperCamelCase     ,  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 	__snake_case    (       self :							Any				)->Optional[Any]:
      __SCREAMING_SNAKE_CASE       :    Dict       =	self.get_image_processor()
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	self.get_tokenizer()

      __SCREAMING_SNAKE_CASE       :    int       =	MgpstrProcessor(tokenizer=UpperCamelCase     ,  image_processor=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	"test"

      __SCREAMING_SNAKE_CASE       :    str       =	processor(text=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Tuple       =	tokenizer(UpperCamelCase				)
      for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key]     ,  encoded_processor[key]				)





     def 	__snake_case    (       self :							Optional[Any]				)->int:
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	self.get_image_processor()
      __SCREAMING_SNAKE_CASE       :    int       =	self.get_tokenizer()

      __SCREAMING_SNAKE_CASE       :    Dict       =	MgpstrProcessor(tokenizer=UpperCamelCase     ,  image_processor=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	"test"
      __SCREAMING_SNAKE_CASE       :    int       =	self.prepare_image_inputs()

      __SCREAMING_SNAKE_CASE       :    Dict       =	processor(text=UpperCamelCase     ,  images=UpperCamelCase				)

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

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





     def 	__snake_case    (       self :							Dict				)->List[str]:
      __SCREAMING_SNAKE_CASE       :    Tuple       =	self.get_image_processor()
      __SCREAMING_SNAKE_CASE       :    Dict       =	self.get_tokenizer()

      __SCREAMING_SNAKE_CASE       :    List[Any]       =	MgpstrProcessor(tokenizer=UpperCamelCase     ,  image_processor=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Any       =	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

      __SCREAMING_SNAKE_CASE       :    int       =	processor.char_decode(UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    Any       =	tokenizer.batch_decode(UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    Any       =	[seq.replace(" "     ,  ""				) for seq in decoded_tok]

      self.assertListEqual(UpperCamelCase     ,  UpperCamelCase				)





     def 	__snake_case    (       self :							int				)->Dict:
      __SCREAMING_SNAKE_CASE       :    Any       =	self.get_image_processor()
      __SCREAMING_SNAKE_CASE       :    Dict       =	self.get_tokenizer()

      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	MgpstrProcessor(tokenizer=UpperCamelCase     ,  image_processor=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Any       =	None
      __SCREAMING_SNAKE_CASE       :    Tuple       =	self.prepare_image_inputs()

      __SCREAMING_SNAKE_CASE       :    int       =	processor(text=UpperCamelCase     ,  images=UpperCamelCase				)

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






     def 	__snake_case    (       self :							Any				)->Dict:
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	self.get_image_processor()
      __SCREAMING_SNAKE_CASE       :    str       =	self.get_tokenizer()

      __SCREAMING_SNAKE_CASE       :    List[Any]       =	MgpstrProcessor(tokenizer=UpperCamelCase     ,  image_processor=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	torch.randn(1     ,  2_7     ,  3_8				)
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	torch.randn(1     ,  2_7     ,  5_0_2_5_7				)
      __SCREAMING_SNAKE_CASE       :    Any       =	torch.randn(1     ,  2_7     ,  3_0_5_2_2				)

      __SCREAMING_SNAKE_CASE       :    int       =	processor.batch_decode([char_input, bpe_input, wp_input]				)

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











from collections.abc import Generator
from math import sin






def 	_lowerCAmelCase						(				__lowerCamelCase   :     bytes     ):



 """simple docstring"""





 if len(__lowerCamelCase     ) != 32:
  raise ValueError("Input must be of length 32"     )

 __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	b""
 for i in [3, 2, 1, 0]:
  little_endian += string_aa[8 * i : 8 * i + 8]
 return little_endian






def 	_lowerCAmelCase						(				__lowerCamelCase   :     int     ):



 """simple docstring"""





 if i < 0:
  raise ValueError("Input must be non-negative"     )

 __SCREAMING_SNAKE_CASE       :    Any       =	format(__lowerCamelCase		,	"08x"     )[-8:]
 __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	b""
 for i in [3, 2, 1, 0]:
  little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode("utf-8"     )
 return little_endian_hex






def 	_lowerCAmelCase						(				__lowerCamelCase   :     bytes     ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE       :    Any       =	b""
 for char in message:
  bit_string += format(__lowerCamelCase		,	"08b"     ).encode("utf-8"     )
 __SCREAMING_SNAKE_CASE       :    List[str]       =	format(len(__lowerCamelCase     )		,	"064b"     ).encode("utf-8"     )

 # Pad bit_string to a multiple of 512 chars
 bit_string += b"1"
 while len(__lowerCamelCase     ) % 512 != 448:
  bit_string += b"0"
 bit_string += to_little_endian(start_len[32:]     ) + to_little_endian(start_len[:32]     )

 return bit_string






def 	_lowerCAmelCase						(				__lowerCamelCase   :     bytes     ):



 """simple docstring"""





 if len(__lowerCamelCase     ) % 512 != 0:
  raise ValueError("Input must have length that's a multiple of 512"     )

 for pos in range(0		,	len(__lowerCamelCase     )		,	512     ):
  __SCREAMING_SNAKE_CASE       :    int       =	bit_string[pos : pos + 512]
  __SCREAMING_SNAKE_CASE       :    Tuple       =	[]
  for i in range(0		,	512		,	32     ):
   block_words.append(int(to_little_endian(block[i : i + 32]     )		,	2     )     )
  yield block_words






def 	_lowerCAmelCase						(				__lowerCamelCase   :     int     ):



 """simple docstring"""





 if i < 0:
  raise ValueError("Input must be non-negative"     )

 __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	format(__lowerCamelCase		,	"032b"     )
 __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	""
 for c in i_str:
  new_str += "1" if c == "0" else "0"
 return int(__lowerCamelCase		,	2     )






def 	_lowerCAmelCase						(				__lowerCamelCase   :     int		,	__lowerCamelCase   :     int     ):



 """simple docstring"""





 return (a + b) % 2**32






def 	_lowerCAmelCase						(				__lowerCamelCase   :     int		,	__lowerCamelCase   :     int     ):



 """simple docstring"""





 if i < 0:
  raise ValueError("Input must be non-negative"     )
 if shift < 0:
  raise ValueError("Shift must be non-negative"     )
 return ((i << shift) ^ (i >> (32 - shift))) % 2**32






def 	_lowerCAmelCase						(				__lowerCamelCase   :     bytes     ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE       :    Tuple       =	preprocess(__lowerCamelCase     )

 __SCREAMING_SNAKE_CASE       :    List[Any]       =	[int(2**32 * abs(sin(i + 1     )     )     ) for i in range(64     )]

 # Starting states
 __SCREAMING_SNAKE_CASE       :    Tuple       =	0X67452301
 __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	0Xefcdab89
 __SCREAMING_SNAKE_CASE       :    Optional[int]       =	0X98badcfe
 __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	0X10325476

 __SCREAMING_SNAKE_CASE       :    List[Any]       =	[
     7,
     12,
     17,
     22,
     7,
     12,
     17,
     22,
     7,
     12,
     17,
     22,
     7,
     12,
     17,
     22,
     5,
     9,
     14,
     20,
     5,
     9,
     14,
     20,
     5,
     9,
     14,
     20,
     5,
     9,
     14,
     20,
     4,
     11,
     16,
     23,
     4,
     11,
     16,
     23,
     4,
     11,
     16,
     23,
     4,
     11,
     16,
     23,
     6,
     10,
     15,
     21,
     6,
     10,
     15,
     21,
     6,
     10,
     15,
     21,
     6,
     10,
     15,
     21,
 ]

 # Process bit string in chunks, each with 16 32-char words
 for block_words in get_block_words(__lowerCamelCase     ):
  __SCREAMING_SNAKE_CASE       :    Any       =	aa
  __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	ba
  __SCREAMING_SNAKE_CASE       :    str       =	ca
  __SCREAMING_SNAKE_CASE       :    Dict       =	da

  # Hash current chunk
  for i in range(64     ):
   if i <= 15:
    # f = (b & c) | (not_32(b) & d)     # Alternate definition for f
    __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	d ^ (b & (c ^ d))
    __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	i
   elif i <= 31:
    # f = (d & b) | (not_32(d) & c)     # Alternate definition for f
    __SCREAMING_SNAKE_CASE       :    int       =	c ^ (d & (b ^ c))
    __SCREAMING_SNAKE_CASE       :    int       =	(5 * i + 1) % 16
   elif i <= 47:
    __SCREAMING_SNAKE_CASE       :    List[str]       =	b ^ c ^ d
    __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	(3 * i + 5) % 16
   else:
    __SCREAMING_SNAKE_CASE       :    Any       =	c ^ (b | not_aa(__lowerCamelCase     ))
    __SCREAMING_SNAKE_CASE       :    str       =	(7 * i) % 16
   __SCREAMING_SNAKE_CASE       :    List[str]       =	(f + a + added_consts[i] + block_words[g]) % 2**32
   __SCREAMING_SNAKE_CASE       :    Dict       =	d
   __SCREAMING_SNAKE_CASE       :    str       =	c
   __SCREAMING_SNAKE_CASE       :    Tuple       =	b
   __SCREAMING_SNAKE_CASE       :    Optional[int]       =	sum_aa(__lowerCamelCase		,	left_rotate_aa(__lowerCamelCase		,	shift_amounts[i]     )     )

  # Add hashed chunk to running total
  __SCREAMING_SNAKE_CASE       :    Dict       =	sum_aa(__lowerCamelCase		,	__lowerCamelCase     )
  __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	sum_aa(__lowerCamelCase		,	__lowerCamelCase     )
  __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	sum_aa(__lowerCamelCase		,	__lowerCamelCase     )
  __SCREAMING_SNAKE_CASE       :    str       =	sum_aa(__lowerCamelCase		,	__lowerCamelCase     )

 __SCREAMING_SNAKE_CASE       :    List[str]       =	reformat_hex(__lowerCamelCase     ) + reformat_hex(__lowerCamelCase     ) + reformat_hex(__lowerCamelCase     ) + reformat_hex(__lowerCamelCase     )
 return digest


if __name__ == "__main__":
      import doctest

      doctest.testmod()






