我需要在Keras(1.1)中创建具有可训练权重(与输入相同的形状)的自定义图层.我尝试通过随机值初始化权重.有我的'mylayer.py'文件:
from keras import backend as K
from keras.engine.topology import Layer
import numpy as np
from numpy import random
class MyLayer(Layer):
def __init__(self,**kwargs):
super(MyLayer, self).__init__(**kwargs)
def build(self, input_shape):
# Create a trainable weight variable for this layer.
self.W_init = np.random(input_shape)
self.W = K.variable(self.W_init, name="W")
self.trainable_weights = [self.W]
super(MyLayer, self).build(input_shape) # Be sure to call this somewhere!
def call(self, x):
num, n, m = x.shape
res=np.empty(num,1,1)
for i in range(num):
res[i,0,0]=K.dot(x[i,:,:], self.W[i,:,:])
return res
def compute_output_shape(self, input_shape):
return (input_shape[0], 1,1)
但是当我尝试使用它时: …