I want to write my own keras layer with taking as input a tensor with shape (nb_batch, input_dim) and producing a tensor with shape (nb_batch, context_size, output_dim) . I have write a demo below:
class MyLayer(Layer):
def __init__(self, output_dim, context_size, init="uniform", **kwargs):
self.output_dim = output_dim
self.context_size = context_size
self.init = initializations.get(init)
super(MyLayer, self).__init__(**kwargs)
def build(self, input_shape):
input_dim = input_shape[1]
self.W_vec = self.init(
(self.context_size, input_dim, self.output_dim),
name="W_vec")
self.trainable_weights = [self.W_vec]
super(MyLayer, self).build() # be sure you call this somewhere!
def call(self, x, mask=None):
return K.dot(x, self.W_vec)
# return K.dot(x, self.W)
def get_output_shape_for(self, input_shape):
return (input_shape[0], self.context_size, self.output_dim)
when I ran it , got a error "TypeError: build() takes exactly 2 arguments (1 given)"enter code here
