Hi,
I want the softmax of the RNN output, to be computed within the step
function, like below:
def step(x_t, h_tm1):
h_t = self.activation(T.dot(x_t, self.W_in) + T.dot(h_tm1, self.W) +
self.bh)
y_t = T.dot(h_t, self.W_out) + self.by
y_t = T.nnet.softmax(y_t)
return h_t, y_t
However I do not get expected results and I am not sure where the problem
is.
Can anybody give me a hint why this method does not work?
This is the scan function:
[self.h, self.y_pred], _ = theano.scan(step,
sequences=self.input,
outputs_info=[T.alloc(self.h0, self.input.shape[1],
n_hidden), None])
and I directly pass self.y_pred to p_y_given_x:
self.p_y_given_x = self.y_pred
Thanks in advance.
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