check if the square matrix has enough space to fit the Tetris shape in using numpy

has_enough_space.py

def check_space(matrix):
    shape = [
        [1, 1, 0],
        [1, 0, 0],
        [1, 0, 0]
    ]

    shape_height = len(shape)
    shape_width = len(shape[0])
    matrix_height = len(matrix)
    matrix_width = len(matrix[0])

    for i in range(matrix_height - shape_height + 1):
        for j in range(matrix_width - shape_width + 1):
            can_fit = True
            for si in range(shape_height):
                for sj in range(shape_width):
                    if shape[si][sj] == 1 and matrix[i + si][j + sj] == 1:
                        can_fit = False
                        break
                if not can_fit:
                    break
            if can_fit:
                return True

    return False

matrix = [
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 1, 1, 1, 1, 0],
        [1, 0, 1, 0, 0, 1, 0, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0]
]

print(check_space(matrix))

has_enough_space_numpy.py

import numpy as np

def check_space(matrix):
    shape = np.array([[1, 1, 0],
                      [1, 0, 0],
                      [1, 0, 0]]
                    )

    for i in range(matrix.shape[0] - shape.shape[0] + 1):
        for j in range(matrix.shape[1] - shape.shape[1] + 1):
            sub_matrix = matrix[i : i + shape.shape[0], j : j + shape.shape[1]]
            if np.all(sub_matrix + shape <= 1):
                return True

    return False

matrix = np.array(
    [
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 1, 1, 1, 1, 0],
        [1, 0, 1, 0, 0, 1, 0, 0],
        [1, 0, 1, 0, 1, 0, 1, 0],
        [1, 0, 1, 0, 1, 0, 1, 0]
    ]
)

print(check_space(matrix))