






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 						lowerCamelCase   (unittest.TestCase    ):







		'''simple docstring'''



		@slow
		@unittest.skip('Model is not available.'     )
		def       __UpperCAmelCase    (							self     )			->							Union[str, Any]:
							UpperCAmelCase_					:   List[str]   =		'nvidia/megatron-gpt2-345m/'
							if "MYDIR" in os.environ:
												UpperCAmelCase_					:   Dict   =		os.path.join(os.environ['MYDIR']       ,	_UpperCamelCase     )
							UpperCAmelCase_					:   List[str]   =		GPTaLMHeadModel.from_pretrained(_UpperCamelCase     )
							model.to(_UpperCamelCase     )
							model.half()

							UpperCAmelCase_					:   Tuple   =		torch.tensor(
							    [[1_0_1, 7_1_1_0, 1_0_0_5, 1_0_5_6, 2_0_2_3, 1_1_3_3_3, 1_7_4_1_3, 1_0_2_9, 1_0_2]]       ,	device=_UpperCamelCase       ,	dtype=torch.long       ,	)

							with torch.no_grad():
												UpperCAmelCase_					:   Tuple   =		model(_UpperCamelCase     ).logits

							UpperCAmelCase_					:   Optional[Any]   =		torch.Size((1, 9, 5_0_2_5_7)     )
							self.assertEqual(output.shape       ,	_UpperCamelCase     )

							UpperCAmelCase_					:   Optional[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=_UpperCamelCase       ,	dtype=torch.half       ,	)

							for i in range(1_9     ):
												UpperCAmelCase_ ,						UpperCAmelCase_					:   Optional[Any]   =		8 * i // 1_7, 2_7_9_2 * i  # along the diagonal
												UpperCAmelCase_ ,						UpperCAmelCase_					:   Optional[Any]   =		output[0, r, c], expected_diag[i]
												UpperCAmelCase_					:   List[Any]   =		f"row={r} col={c} computed={computed} expected={expected}"
												self.assertAlmostEqual(_UpperCamelCase       ,	_UpperCamelCase       ,	delta=1E-4       ,	msg=_UpperCamelCase     )














def   lowercase__   (  __snake_case					:							int  , __snake_case					:							int  , __snake_case					:							int  , __snake_case					:							int						):


					'''simple docstring'''


					return len_board * len_board_column * row + column




def   lowercase__   (  __snake_case					:							list[list[str]]  , __snake_case					:							str  , __snake_case					:							int  , __snake_case					:							int  , __snake_case					:							int  , __snake_case					:							set[int]  , ):


					'''simple docstring'''


					if board[row][column] != word[word_index]:
										return False

					if word_index == len(__snake_case						) - 1:
										return True

					UpperCAmelCase_					:   Dict   =		[(0, 1), (0, -1), (-1, 0), (1, 0)]
					UpperCAmelCase_					:   Union[str, Any]   =		len(__snake_case						)
					UpperCAmelCase_					:   List[Any]   =		len(board[0]						)
					for direction in traverts_directions:
										UpperCAmelCase_					:   Optional[int]   =		row + direction[0]
										UpperCAmelCase_					:   Optional[int]   =		column + direction[1]
										if not (0 <= next_i < len_board and 0 <= next_j < len_board_column):
															continue

										UpperCAmelCase_					:   Tuple   =		get_point_key(__snake_case  , __snake_case  , __snake_case  , __snake_case						)
										if key in visited_points_set:
															continue

										visited_points_set.add(__snake_case						)
										if exits_word(__snake_case  , __snake_case  , __snake_case  , __snake_case  , word_index + 1  , __snake_case						):
															return True

										visited_points_set.remove(__snake_case						)

					return False




def   lowercase__   (  __snake_case					:							list[list[str]]  , __snake_case					:							str						):


					'''simple docstring'''


					UpperCAmelCase_					:   Any   =		(
					    'The board should be a non empty matrix of single chars strings.'
					)

					UpperCAmelCase_					:   Optional[Any]   =		len(__snake_case						)
					if not isinstance(__snake_case  , __snake_case						) or len(__snake_case						) == 0:
										raise ValueError(__snake_case						)

					for row in board:
										if not isinstance(__snake_case  , __snake_case						) or len(__snake_case						) == 0:
															raise ValueError(__snake_case						)

										for item in row:
															if not isinstance(__snake_case  , __snake_case						) or len(__snake_case						) != 1:
																				raise ValueError(__snake_case						)

    # Validate word
					if not isinstance(__snake_case  , __snake_case						) or len(__snake_case						) == 0:
										raise ValueError(
										    'The word parameter should be a string of length greater than 0.'						)

					UpperCAmelCase_					:   Any   =		len(board[0]						)
					for i in range(__snake_case						):
										for j in range(__snake_case						):
															if exits_word(
															    __snake_case  , __snake_case  , __snake_case  , __snake_case  , 0  , {get_point_key(__snake_case  , __snake_case  , __snake_case  , __snake_case						)}						):
																				return True

					return False


if __name__ == "__main__":
		import doctest

		doctest.testmod()






