





from __future__ import annotations


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase					):
       _UpperCamelCase       ,		_UpperCamelCase              =						position
       _UpperCamelCase              =						[
           (y + 1, x + 2),
           (y - 1, x + 2),
           (y + 1, x - 2),
           (y - 1, x - 2),
           (y + 2, x + 1),
           (y + 2, x - 1),
           (y - 2, x + 1),
           (y - 2, x - 1),
       ]
       _UpperCamelCase              =						[]

       for position in positions:
              _UpperCamelCase       ,		_UpperCamelCase              =						position
              if 0 <= y_test < n and 0 <= x_test < n:
                     permissible_positions.append(lowerCAmelCase					)

       return permissible_positions


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       return not any(elem == 0 for row in board for elem in row					)


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase    ,       lowerCAmelCase					):

       if is_complete(lowerCAmelCase					):
              return True

       for position in get_valid_pos(lowerCAmelCase    ,       len(lowerCAmelCase					)					):
              _UpperCamelCase       ,		_UpperCamelCase              =						position

              if board[y][x] == 0:
                     _UpperCamelCase              =						curr + 1
                     if open_knight_tour_helper(lowerCAmelCase    ,       lowerCAmelCase    ,       curr + 1					):
                            return True
                     _UpperCamelCase              =						0

       return False


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						[[0 for i in range(lowerCAmelCase					)] for j in range(lowerCAmelCase					)]

       for i in range(lowerCAmelCase					):
              for j in range(lowerCAmelCase					):
                     _UpperCamelCase              =						1
                     if open_knight_tour_helper(lowerCAmelCase    ,       (i, j)    ,       1					):
                            return board
                     _UpperCamelCase              =						0

       _UpperCamelCase              =						f'''Open Kight Tour cannot be performed on a board of size {n}'''
       raise ValueError(lowerCAmelCase					)


if __name__ == "__main__":
       import doctest

       doctest.testmod()













from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch

@require_torch
@require_tf
class  __A(						__UpperCAmelCase ):

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						SMALL_MODEL_IDENTIFIER
            _UpperCamelCase              =						'''pt'''
            _UpperCamelCase              =						'''tf'''

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						AutoModel.from_pretrained(self.test_model      )
            model_pt.save_pretrained(A      )

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						TFAutoModel.from_pretrained(self.test_model,       from_pt=A      )
            model_tf.save_pretrained(A      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						'''mock_framework'''

            # Framework provided - return whatever the user provides
            _UpperCamelCase              =						FeaturesManager.determine_framework(self.test_model,       A      )
            self.assertEqual(A,       A      )

            # Local checkpoint and framework provided - return provided framework
            # PyTorch checkpoint
            with TemporaryDirectory() as local_pt_ckpt:
                   self._setup_pt_ckpt(A      )
                   _UpperCamelCase              =						FeaturesManager.determine_framework(A,       A      )
                   self.assertEqual(A,       A      )

            # TensorFlow checkpoint
            with TemporaryDirectory() as local_tf_ckpt:
                   self._setup_tf_ckpt(A      )
                   _UpperCamelCase              =						FeaturesManager.determine_framework(A,       A      )
                   self.assertEqual(A,       A      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            with TemporaryDirectory() as local_pt_ckpt:
                   self._setup_pt_ckpt(A      )
                   _UpperCamelCase              =						FeaturesManager.determine_framework(A      )
                   self.assertEqual(A,       self.framework_pt      )

            # TensorFlow checkpoint
            with TemporaryDirectory() as local_tf_ckpt:
                   self._setup_tf_ckpt(A      )
                   _UpperCamelCase              =						FeaturesManager.determine_framework(A      )
                   self.assertEqual(A,       self.framework_tf      )

            # Invalid local checkpoint
            with TemporaryDirectory() as local_invalid_ckpt:
                   with self.assertRaises(A      ):
                          _UpperCamelCase              =						FeaturesManager.determine_framework(A      )



     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						MagicMock(return_value=A      )
            with patch('''transformers.onnx.features.is_tf_available''',       A      ):
                   _UpperCamelCase              =						FeaturesManager.determine_framework(self.test_model      )
                   self.assertEqual(A,       self.framework_pt      )

            # PyTorch not in environment -> use TensorFlow
            _UpperCamelCase              =						MagicMock(return_value=A      )
            with patch('''transformers.onnx.features.is_torch_available''',       A      ):
                   _UpperCamelCase              =						FeaturesManager.determine_framework(self.test_model      )
                   self.assertEqual(A,       self.framework_tf      )

            # Both in environment -> use PyTorch
            _UpperCamelCase              =						MagicMock(return_value=A      )
            _UpperCamelCase              =						MagicMock(return_value=A      )
            with patch('''transformers.onnx.features.is_tf_available''',       A      ), patch(
                '''transformers.onnx.features.is_torch_available''',       A      ):
                   _UpperCamelCase              =						FeaturesManager.determine_framework(self.test_model      )
                   self.assertEqual(A,       self.framework_pt      )

            # Both not in environment -> raise error
            _UpperCamelCase              =						MagicMock(return_value=A      )
            _UpperCamelCase              =						MagicMock(return_value=A      )
            with patch('''transformers.onnx.features.is_tf_available''',       A      ), patch(
                '''transformers.onnx.features.is_torch_available''',       A      ):
                   with self.assertRaises(A      ):
                          _UpperCamelCase              =						FeaturesManager.determine_framework(self.test_model      )






