在TensorFlow中手动初始化conv1d

Question

如何将自定义系数设置为tf.layers.conv1d。我发现了如何读取当前系数，但我怎么写它们？

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt

sess = tf.Session()
order = 5
x = np.zeros(30)
x[10] = 1
y = tf.layers.conv1d(inputs=tf.reshape(x,[1, len(x), 1]),
                     filters=1,
                     kernel_size=order,
                     padding='same')
sess.run(tf.global_variables_initializer())
y_out = sess.run(y)

# get coef
coef = sess.run(tf.all_variables()[-2].value())
print(coef.reshape(order))

这是一个链接到笔记本的代码在谷歌colab：https://colab.research.google.com/drive/1YNSzKmtC88b__LqYcfD-tFHFG3jOZIAz

一般来说，我对如何在TensorFlow中制作FIR滤波器感兴趣。

Answer 1

我知道了！有kerner_initializer参数。

这是解决方案

init_coef = np.array([1,2,3,4,5])[::-1]
init_coef = tf.initializers.constant(init_coef)
y = tf.layers.conv1d(inputs=tf.reshape(x,[1, len(x), 1]),
                     filters=1,
                     kernel_size=order,
                     padding='same',
                     kernel_initializer=init_coef)