convolution

tensor shape depend on both strides and padding type
try strides in (1 1), (2 2), (3 3) and (4 4) combine with twice padding type

import os
import numpy as np
import tensorflow as tf

os.environ["CUDA_VISIBLE_DEVICES"] = "3"

n = tf.convert_to_tensor(np.array(range(16)), np.float32)
i = tf.reshape(n, [-1, 4, 4, 1])
conv = tf.layers.conv2d(inputs=i, filters=32, kernel_size=[1, 1], strides=(3, 3), padding="same", activation=tf.nn.relu)
print(conv)