# A
import numpy as np

height, width = map(int, input().split())

ans = np.array([[255 if (i + j) % 2 else 0 for j in range(width)] for i in range(height)])
print(ans)

#B (это лучше сделать иначе, а то слишком неочевидное решение)
import numpy as np
import sys

k = int(input())
mt = [[int(x) for x in row.split()] for row in sys.stdin]

rows = len(mt)
cols = len(mt[0]) if rows > 0 else 0

ans_rows = (rows + k - 1) // k
ans_cols = (cols + k - 1) // k
ans = [[0 for _ in range(ans_cols)] for _ in range(ans_rows)]

for i in range(len(mt)):
    for j in range(len(mt[i])):
        ni = i // k
        nj = j // k
        ans[ni][nj] += mt[i][j]

for row in ans:
    print(" ".join(map(str, row)))

#C
import sys
import numpy as np


def get_cos_dist(a: np.array, b: np.array) -> float:
    if np.linalg.norm(a) == 0 or np.linalg.norm(b) == 0:
        return np.inf
    return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))


def main():
    vectors = [np.array(list(map(float, row.split()))) for row in sys.stdin]
    if len(vectors) < 2:
        print("No solution")
        return

    ans = np.inf
    for i in range(len(vectors)):
        for j in range(i + 1, len(vectors)):
            if vectors[i].shape != vectors[j].shape:
                # print(vectors[i].shape)
                continue
            cos_dist = get_cos_dist(vectors[i], vectors[j])
            ans = min(ans, cos_dist)

    if ans != np.inf:
        print(f'{ans:.2}')
    else:
        print("No solution")


main()


#D (норм решает гпт)
import numpy as np

height, width = map(int, input().split())
r, g, b = map(int, input().split())
rb, gb, bb, = map(int, input().split())

image = np.zeros((height, width, 3), dtype=np.uint8)

image[2:-2, 2:-2] = (r, g, b)

image[:2, :] = (rb, gb, bb)
image[-2:, :] = (rb, gb, bb)
image[:, :2] = (rb, gb, bb)
image[:, -2:] = (rb, gb, bb)

print(image)

#E
import numpy as np
import sys

mt = np.array([line.strip() for line in sys.stdin])
# print(mt)

print(len(np.unique(mt)))


#F
import sys
import numpy as np

mt = np.array([list(map(float, row.split())) for row in sys.stdin])

mean_values = np.mean(mt, axis=1)
# print(mean_values, 'a')
ans = mt - mean_values[:, np.newaxis]

print(str(ans))



#G
import sys
import numpy as np

mt = np.array([list(map(float, row.split())) for row in sys.stdin])
# b = np.array([0 for i in range(len(mt))])

ans = np.sum(np.all(mt==0, axis=0))
# print(np.all(mt == 0, axis=0))
print(ans)