CODEWITHSUNDEEP
pythontheano
o17t H1H' S'k
o17t H1H' S'k

Reputation: 2744

Theano set_value for casted shared variable

In the Theano deep learning tutorial, y is a shared variable that is casted:

   y = theano.shared(numpy.asarray(data, dtype=theano.config.floatX))
   y = theano.tensor.cast(y, 'int32')

I later want to set a new value for y.

For GPU this works:

    y.owner.inputs[0].owner.inputs[0].set_value(np.asarray(data2, dtype=theano.config.floatX))

For CPU this works:

    y.owner.inputs[0].set_value(np.asarray(data2, dtype=theano.config.floatX))

Why does this require a different syntax between GPU and CPU? I would like my code to work for both cases, am I doing it wrong?

Upvotes: 1

Views: 2000

Answers (1)

Daniel Renshaw
Daniel Renshaw

Reputation: 34177

This is a very similar problem to that described in another StackOverflow question.

The problem is that you are using a symbolic cast operation which turns the shared variable into a symbolic variable.

The solution is to cast the shared variable's value rather than the shared variable itself.

Instead of

y = theano.shared(numpy.asarray(data, dtype=theano.config.floatX))
y = theano.tensor.cast(y, 'int32')

Use

y = theano.shared(numpy.asarray(data, dtype='int32'))

Navigating the Theano computational graph via the owner attribute is considered bad form. If you want to alter the shared variable's value, maintain a Python reference to the shared variable and set its value directly.

So, with y being just a shared variable, and not a symbolic variable, you can now just do:

y.set_value(np.asarray(data2, dtype='int32'))

Note that the casting is happening in numpy again, instead of Theano.

Upvotes: 4

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