code: 
  
  
  """simple docstring"""
  import os
  import unittest
  
  from transformers import is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  
  
  if is_torch_available():
   import torch
  
   from transformers import GPTaLMHeadModel
  
  
  
  
  @require_torch
  @require_sentencepiece
  @require_tokenizers
  class   lowercase__							(				unittest.TestCase							):
  
  
  
  
  
     @slow
     @unittest.skip("""Model is not available.""")
     def 		UpperCamelCase_     (       self)     ->     Union[str, Any]:
        _lowerCamelCase  :				Tuple      =		"""nvidia/megatron-gpt2-345m/"""
        if "MYDIR" in os.environ:
           _lowerCamelCase  :				Any      =		os.path.join(os.environ["""MYDIR"""]			,      SCREAMING_SNAKE_CASE)
        _lowerCamelCase  :				str      =		GPTaLMHeadModel.from_pretrained(SCREAMING_SNAKE_CASE)
        model.to(SCREAMING_SNAKE_CASE)
        model.half()
  
        _lowerCamelCase  :				Optional[int]      =		torch.tensor(
            [[101, 7110, 1005, 1056, 2023, 1_1333, 1_7413, 1029, 102]]			,      device=SCREAMING_SNAKE_CASE			,      dtype=torch.long			,      )
  
        with torch.no_grad():
           _lowerCamelCase  :				Dict      =		model(SCREAMING_SNAKE_CASE).logits
  
        _lowerCamelCase  :				str      =		torch.Size((1, 9, 5_0257))
        self.assertEqual(output.shape			,      SCREAMING_SNAKE_CASE)
  
        _lowerCamelCase  :				Any      =		torch.tensor(
            [
                4.94_14,
                -0.29_20,
                -1.21_48,
                -4.02_73,
                -0.51_61,
                -5.21_09,
                -1.24_12,
                -1.83_01,
                -1.77_34,
                -4.71_48,
                -0.23_17,
                -1.08_11,
                -2.17_77,
                0.41_41,
                -3.79_69,
                -4.05_86,
                -2.53_32,
                -3.38_09,
                4.38_67,
            ]			,      device=SCREAMING_SNAKE_CASE			,      dtype=torch.half			,      )
  
        for i in range(19):
           _lowerCamelCase      ,						_lowerCamelCase  :				Optional[Any]      =		8 * i // 17, 2792 * i  # along the diagonal
           _lowerCamelCase      ,						_lowerCamelCase  :				Tuple      =		output[0, r, c], expected_diag[i]
           _lowerCamelCase  :				List[Any]      =		F'row={r} col={c} computed={computed} expected={expected}'
           self.assertAlmostEqual(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      delta=1e-4			,      msg=SCREAMING_SNAKE_CASE)
  
  
style_context: 
  
  
  """simple docstring"""
  def 							_snake_case			(      __snake_case       :			str	,   __snake_case       :			str	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				Optional[Any]      =		list(__snake_case      )
     _lowerCamelCase  :				Optional[int]      =		list(__snake_case      )
     _lowerCamelCase  :				Union[str, Any]      =		len(__snake_case      )
     _lowerCamelCase  :				Optional[int]      =		len(__snake_case      )
  
     _lowerCamelCase  :				List[str]      =		[
         [0 for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
     ]
     _lowerCamelCase  :				List[Any]      =		[
         ["""0""" for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
     ]
  
     for i in range(1	,   len_source_seq + 1      ):
        _lowerCamelCase  :				Optional[Any]      =		i * delete_cost
        _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'
  
     for i in range(1	,   len_destination_seq + 1      ):
        _lowerCamelCase  :				Dict      =		i * insert_cost
        _lowerCamelCase  :				List[str]      =		F'I{destination_seq[i - 1]:c}'
  
     for i in range(1	,   len_source_seq + 1      ):
        for j in range(1	,   len_destination_seq + 1      ):
           if source_seq[i - 1] == destination_seq[j - 1]:
              _lowerCamelCase  :				Union[str, Any]      =		costs[i - 1][j - 1] + copy_cost
              _lowerCamelCase  :				Tuple      =		F'C{source_seq[i - 1]:c}'
           else:
              _lowerCamelCase  :				Tuple      =		costs[i - 1][j - 1] + replace_cost
              _lowerCamelCase  :				List[str]      =		F'R{source_seq[i - 1]:c}' + str(destination_seq[j - 1]      )
  
           if costs[i - 1][j] + delete_cost < costs[i][j]:
              _lowerCamelCase  :				Any      =		costs[i - 1][j] + delete_cost
              _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'
  
           if costs[i][j - 1] + insert_cost < costs[i][j]:
              _lowerCamelCase  :				Dict      =		costs[i][j - 1] + insert_cost
              _lowerCamelCase  :				Union[str, Any]      =		F'I{destination_seq[j - 1]:c}'
  
     return costs, ops
  
  def 							_snake_case			(      __snake_case       :			list[list[str]]	,   __snake_case       :			int	,   __snake_case       :			int      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     if i == 0 and j == 0:
        return []
     else:
        if ops[i][j][0] == "C" or ops[i][j][0] == "R":
           _lowerCamelCase  :				List[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   j - 1      )
           seq.append(ops[i][j]      )
           return seq
        elif ops[i][j][0] == "D":
           _lowerCamelCase  :				Optional[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   __snake_case      )
           seq.append(ops[i][j]      )
           return seq
        else:
           _lowerCamelCase  :				str      =		assemble_transformation(__snake_case	,   __snake_case	,   j - 1      )
           seq.append(ops[i][j]      )
           return seq
  
  
  if __name__ == "__main__":
   UpperCAmelCase ,     UpperCAmelCase   =	compute_transform_tables("""Python""", """Algorithms""", -1, 1, 2, 2)
  
   UpperCAmelCase   =	len(operations)
   UpperCAmelCase   =	len(operations[0])
   UpperCAmelCase   =	assemble_transformation(operations, m - 1, n - 1)
  
   UpperCAmelCase   =	list("""Python""")
   UpperCAmelCase   =	0
   UpperCAmelCase   =	0
  
   with open("""min_cost.txt""", """w""") as file:
    for op in sequence:
     print("""""".join(string))
  
     if op[0] == "C":
      file.write("""%-16s""" % """Copy %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost -= 1
     elif op[0] == "R":
      UpperCAmelCase   =	op[2]
  
      file.write("""%-16s""" % ("""Replace %c""" % op[1] + """ with """ + str(op[2])))
      file.write("""\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 1
     elif op[0] == "D":
      string.pop(i)
  
      file.write("""%-16s""" % """Delete %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 2
     else:
      string.insert(i, op[1])
  
      file.write("""%-16s""" % """Insert %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 2
  
     i += 1
  
    print("""""".join(string))
    print("""Cost: """, cost)
  
    file.write("""\r\nMinimum cost: """ + str(cost))
  
  