tf.nn.conv2d

标签：array   ant   imp   ESS   ali   pad   shape   int   conv2   

import numpy as np
filter_primes = np.array([2., 3., 5., 7., 11., 13.], dtype=np.float32)
x = tf.constant(np.arange(1, 13+1, dtype=np.float32).reshape([1, 1, 13, 1]))
filters = tf.constant(filter_primes.reshape(1, 6, 1, 1))

valid_conv = tf.nn.conv2d(x, filters, strides=[1, 1, 5, 1], padding=‘VALID‘)
same_conv = tf.nn.conv2d(x, filters, strides=[1, 1, 5, 1], padding=‘SAME‘)

with tf.Session() as sess:
       print("VALID:\n", valid_conv.eval())
       print("SAME:\n", same_conv.eval())

tf.nn.conv2d

标签：array   ant   imp   ESS   ali   pad   shape   int   conv2   

原文地址：https://www.cnblogs.com/hapyygril/p/10945183.html