




from typing import Any

import numpy as np




def        __SCREAMING_SNAKE_CASE (	lowercase_   )							->						bool:

    """simple docstring"""


    assert np.shape(lowercase_   )[0] == np.shape(lowercase_   )[1]

    # If matrix not symmetric, exit right away.
    if np.allclose(lowercase_       ,  matrix.T   ) is False:
        return False

    # Get eigenvalues and eignevectors for a symmetric matrix.
    __UpperCamelCase		,   __UpperCamelCase			=    np.linalg.eigh(lowercase_   )

    # Check sign of all eigenvalues.
    # np.all returns a value of type np.bool_
    return bool(np.all(eigen_values > 0   )   )




def        __SCREAMING_SNAKE_CASE (	lowercase_   )							->						Any:

    """simple docstring"""


    __UpperCamelCase			=    np.random.randn(lowercase_       ,  lowercase_   )
    __UpperCamelCase			=    np.dot(lowercase_       ,  random_matrix.T   )
    assert _is_matrix_spd(lowercase_   )
    return spd_matrix




def        __SCREAMING_SNAKE_CASE (	lowercase_       ,  lowercase_       ,  lowercase_ = 10_00       ,  lowercase_ = 1E-8       ,  )							->						Any:

    """simple docstring"""


    assert np.shape(lowercase_   )[0] == np.shape(lowercase_   )[1]
    assert np.shape(lowercase_   )[0] == np.shape(lowercase_   )[0]
    assert _is_matrix_spd(lowercase_   )

    # Initialize solution guess, residual, search direction.
    __UpperCamelCase			=    np.zeros((np.shape(lowercase_   )[0], 1)   )
    __UpperCamelCase			=    np.copy(lowercase_   )
    __UpperCamelCase			=    np.copy(lowercase_   )

    # Set initial errors in solution guess and residual.
    __UpperCamelCase			=    1E9
    __UpperCamelCase			=    1E9
    __UpperCamelCase			=    1E9

    # Set iteration counter to threshold number of iterations.
    __UpperCamelCase			=    0

    while error > tol:
        # Save this value so we only calculate the matrix-vector product once.
        __UpperCamelCase			=    np.dot(lowercase_       ,  lowercase_   )

        # The main algorithm.

        # Update search direction magnitude.
        __UpperCamelCase			=    np.dot(ra.T       ,  lowercase_   ) / np.dot(pa.T       ,  lowercase_   )
        # Update solution guess.
        __UpperCamelCase			=    xa + alpha * pa
        # Calculate new residual.
        __UpperCamelCase			=    ra - alpha * w
        # Calculate new Krylov subspace scale.
        __UpperCamelCase			=    np.dot(r.T       ,  lowercase_   ) / np.dot(ra.T       ,  lowercase_   )
        # Calculate new A conjuage search direction.
        __UpperCamelCase			=    r + beta * pa

        # Calculate errors.
        __UpperCamelCase			=    np.linalg.norm(r - ra   )
        __UpperCamelCase			=    np.linalg.norm(x - xa   )
        __UpperCamelCase			=    np.maximum(lowercase_       ,  lowercase_   )

        # Update variables.
        __UpperCamelCase			=    np.copy(lowercase_   )
        __UpperCamelCase			=    np.copy(lowercase_   )
        __UpperCamelCase			=    np.copy(lowercase_   )

        # Update number of iterations.
        iterations += 1
        if iterations > max_iterations:
            break

    return x




def        __SCREAMING_SNAKE_CASE (	)							->						None:

    """simple docstring"""


    __UpperCamelCase			=    3
    __UpperCamelCase			=    _create_spd_matrix(lowercase_   )
    __UpperCamelCase			=    np.random.randn(lowercase_       ,  1   )
    __UpperCamelCase			=    np.dot(lowercase_       ,  lowercase_   )

    # Numpy solution.
    __UpperCamelCase			=    np.linalg.solve(lowercase_       ,  lowercase_   )

    # Our implementation.
    __UpperCamelCase			=    conjugate_gradient(lowercase_       ,  lowercase_   )

    # Ensure both solutions are close to x_true (and therefore one another).
    assert np.linalg.norm(x_numpy - x_true   ) <= 1E-6
    assert np.linalg.norm(x_conjugate_gradient - x_true   ) <= 1E-6


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 test_conjugate_gradient()











from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__       =			logging.get_logger(__name__)

A__       =			{
    """MCG-NJU/videomae-base""": """https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json""",
}





class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''videomae'''




				def __init__(				self		,							_snake_case=224		,							_snake_case=16		,							_snake_case=3		,							_snake_case=16		,							_snake_case=2		,							_snake_case=768		,							_snake_case=12		,							_snake_case=12		,							_snake_case=3072		,							_snake_case="gelu"		,							_snake_case=0.0		,							_snake_case=0.0		,							_snake_case=0.02		,							_snake_case=1e-12		,							_snake_case=True		,							_snake_case=True		,							_snake_case=6		,							_snake_case=384		,							_snake_case=4		,							_snake_case=1536		,							_snake_case=True		,							**_snake_case		,							):



									"""simple docstring"""





									super().__init__(**_snake_case						)

									_lowerCAmelCase         =       image_size
									_lowerCAmelCase         =       patch_size
									_lowerCAmelCase         =       num_channels
									_lowerCAmelCase         =       num_frames
									_lowerCAmelCase         =       tubelet_size

									_lowerCAmelCase         =       hidden_size
									_lowerCAmelCase         =       num_hidden_layers
									_lowerCAmelCase         =       num_attention_heads
									_lowerCAmelCase         =       intermediate_size
									_lowerCAmelCase         =       hidden_act
									_lowerCAmelCase         =       hidden_dropout_prob
									_lowerCAmelCase         =       attention_probs_dropout_prob
									_lowerCAmelCase         =       initializer_range
									_lowerCAmelCase         =       layer_norm_eps
									_lowerCAmelCase         =       qkv_bias
									_lowerCAmelCase         =       use_mean_pooling

									_lowerCAmelCase         =       decoder_num_attention_heads
									_lowerCAmelCase         =       decoder_hidden_size
									_lowerCAmelCase         =       decoder_num_hidden_layers
									_lowerCAmelCase         =       decoder_intermediate_size
									_lowerCAmelCase         =       norm_pix_loss



