Example:
        input: a = [[1,2,3,4],[5,6,7,8]], new_shape = (4, 2)
        output: [[1, 2], [3, 4], [5, 6], [7, 8]]
        reasoning: The given matrix is reshaped from 2x4 to 4x2.

Reshaping a Matrix

Matrix reshaping involves changing the shape of a matrix without altering its data. This is essential in many machine learning tasks where the input data needs to be formatted in a specific way. For example, consider a matrix \(M\): Original Matrix \(M\): \[ M = \begin{pmatrix} 1 & 2 & 3 & 4 \\ 5 & 6 & 7 & 8 \end{pmatrix} \] Reshaped Matrix \(M'\) with shape (4, 2): \[ M' = \begin{pmatrix} 1 & 2 \\ 3 & 4 \\ 5 & 6 \\ 7 & 8 \end{pmatrix} \] Ensure the total number of elements remains constant during reshaping.

import numpy as np

def reshape_matrix(a: list[list[int|float]], new_shape: tuple[int|float]) -> list[list[int|float]]:
    return np.array(a).reshape(new_shape).tolist()