partial code as follows:( please just pay attention to the context of the
code)
rng = T.shared_randomstreams.RandomStreams()
class gen_rand(object):
def init(self, rng, input):
self.input_shape = input.shape
print type(self.input_shape)
self.output = rng.uniform(size=self.input_shape, low=0, high=1)
def return_output(self):
return self.output
I coded a neural network code with one of the weigh W initialized with
T.shared_randomstreams.RandomStreams(), the reason I didn't use
numpy.random is that I don't want to feed input.shape everytime, but to
compute the shape of input in the code.
the code works but just because it's random tensor, It can't be used as a
Weight in neural network, it changes every time.
How can I initialize a weight in NN with random module in theano( just want
to randomly generate value once at the beginning and not to be updated by
itself, i tried 'no_default_updates=True' then it can't be updated through
gradient descent!!, I also tried copy modue in python to shallow copy
rng.uniform, there was an error. I tried numpy.random, but it requires
numerical size of the random value but not tensor)
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