




'''simple docstring'''





import matplotlib.pyplot as plt
import numpy as np





def 			__a			(     _UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					float					)		->				np.ndarray:

     """simple docstring"""




     _snake_case							=   len(_UpperCamelCase					)  # Number of training samples
     _snake_case							=   np.eye(_UpperCamelCase					)  # Initialize weights as identity matrix
     for j in range(_UpperCamelCase					):
          _snake_case							=   point - x_train[j]
          _snake_case							=   np.exp(diff @ diff.T / (-2.0 * tau**2)					)

     return weights





def 			__a			(     _UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					float					)		->				np.ndarray:

     """simple docstring"""




     _snake_case							=   weight_matrix(_UpperCamelCase      ,		_UpperCamelCase      ,		_UpperCamelCase					)
     _snake_case							=   np.linalg.inv(x_train.T @ weight_mat @ x_train					) @ (
         x_train.T @ weight_mat @ y_train.T
     )

     return weight





def 			__a			(     _UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					float					)		->				np.ndarray:

     """simple docstring"""




     _snake_case							=   np.zeros(len(_UpperCamelCase					)					)  # Initialize array of predictions
     for i, item in enumerate(_UpperCamelCase					):
          _snake_case							=   item @ local_weight(_UpperCamelCase      ,		_UpperCamelCase      ,		_UpperCamelCase      ,		_UpperCamelCase					)

     return y_pred





def 			__a			(     _UpperCamelCase:					str      ,		_UpperCamelCase:					str      ,		_UpperCamelCase:					str					)		->				tuple[np.ndarray, np.ndarray, np.ndarray]:

     """simple docstring"""




     import seaborn as sns

     _snake_case							=   sns.load_dataset(_UpperCamelCase					)
     _snake_case							=   np.array(data[x_name]					)
     _snake_case							=   np.array(data[y_name]					)

     _snake_case							=   np.ones(len(_UpperCamelCase					)					)

     # pairing elements of one and x_data
     _snake_case							=   np.column_stack((one, x_data)					)

     return x_train, x_data, y_data





def 			__a			(     _UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					np.ndarray      ,		_UpperCamelCase:					str      ,		_UpperCamelCase:					str      ,		)		->				None:

     """simple docstring"""




     _snake_case							=   np.sort(_UpperCamelCase      ,		axis=0					)
     plt.scatter(_UpperCamelCase      ,		_UpperCamelCase      ,		color="blue"					)
     plt.plot(
         x_train_sorted[:, 1]      ,		preds[x_train[:, 1].argsort(0					)]      ,		color="yellow"      ,		linewidth=5      ,		)
     plt.title("Local Weighted Regression"					)
     plt.xlabel(_UpperCamelCase					)
     plt.ylabel(_UpperCamelCase					)
     plt.show()


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   # Demo with a dataset from the seaborn module
   UpperCamelCase_			,			UpperCamelCase_			,			UpperCamelCase_		:    Tuple									=		load_data('''tips''', '''total_bill''', '''tip''')
   UpperCamelCase_		:    Tuple									=		local_weight_regression(training_data_x, tip, 5)
   plot_preds(training_data_x, predictions, total_bill, tip, '''total_bill''', '''tip''')








'''simple docstring'''





import argparse
import os


UpperCamelCase_		:    Union[str, Any]									=		{
    '''pytorch''': {
        '''1.13''': {
            '''torch''': '''1.13.1''',
            '''torchvision''': '''0.14.1''',
            '''torchaudio''': '''0.13.1''',
            '''python''': 3.9,
            '''cuda''': '''cu116''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu116'''
            ),
            '''base_image''': '''nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.12''': {
            '''torch''': '''1.12.1''',
            '''torchvision''': '''0.13.1''',
            '''torchaudio''': '''0.12.1''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.11''': {
            '''torch''': '''1.11.0''',
            '''torchvision''': '''0.12.0''',
            '''torchaudio''': '''0.11.0''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.10''': {
            '''torch''': '''1.10.2''',
            '''torchvision''': '''0.11.3''',
            '''torchaudio''': '''0.10.2''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        '''1.9''': {
            '''torch''': '''1.9.1''',
            '''torchvision''': '''0.10.1''',
            '''torchaudio''': '''0.9.1''',
            '''python''': 3.9,
            '''cuda''': '''cu111''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu111'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
    },
    '''tensorflow''': {
        '''2.11''': {
            '''tensorflow''': '''2.11.1''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.11.1''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.10''': {
            '''tensorflow''': '''2.10.1''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.10.1''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.9''': {
            '''tensorflow''': '''2.9.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.9.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.8''': {
            '''tensorflow''': '''2.8.2''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.8.2''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.7''': {
            '''tensorflow''': '''2.7.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.7.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.6''': {
            '''tensorflow''': '''2.6.5''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.6.5''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.5''': {
            '''tensorflow''': '''2.5.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.5.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
    },
}


if __name__ == "__main__":
   UpperCamelCase_		:    Optional[Any]									=		argparse.ArgumentParser('''Choose the framework and version to install''')
   parser.add_argument(
       '''--framework''', help='''The framework to install. Should be `torch` or `tensorflow`''', type=str, required=True
   )
   parser.add_argument('''--version''', help='''The version of the framework to install.''', type=str, required=True)
   UpperCamelCase_		:    Tuple									=		parser.parse_args()

   UpperCamelCase_		:    Optional[int]									=		past_versions_testing[args.framework][args.version]

   os.system(F'echo "export INSTALL_CMD=\'{info["install"]}\'" >> ~/.profile')
   print(F'echo "export INSTALL_CMD=\'{info["install"]}\'" >> ~/.profile')

   UpperCamelCase_		:    List[Any]									=		''''''
   if args.framework == "pytorch":
      UpperCamelCase_		:    str									=		info['''cuda''']
   os.system(F'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')
   print(F'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')


