def feedforward(x):
h1 = f(tf.matmul(x, W['1']) + b['1'])
h1 = tf.cond(is_training, lambda: tf.nn.dropout(h1, p), lambda: h1)
h2 = f(tf.matmul(h1, W['2']) + b['2'])
h2 = tf.cond(is_training, lambda: tf.nn.dropout(h2, p), lambda: h2)
h3 = f(tf.matmul(h2, W['3']) + b['3'])
h3 = tf.cond(is_training, lambda: tf.nn.dropout(h3, p), lambda: h3)
h4 = f(tf.matmul(h3, W['4']) + b['4'])
h4 = tf.cond(is_training, lambda: tf.nn.dropout(h4, p), lambda: h4)
h5 = f(tf.matmul(h4, W['5']) + b['5'])
h5 = tf.cond(is_training, lambda: tf.nn.dropout(h5, p), lambda: h5)
return tf.matmul(h5, W['6']) + b['6']
评论列表
文章目录