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When theano.config.floatX and the default numpy float dtype do not match (as is the case when you want to use the GPU and set floatX to float32 but numpy is on float64) it causes a lot of problems that require manual casting of all the parameters that get passed in. We should automatically cast everything that get's passed to floatX.
Not sure if there is a proper way to do that in theano, @nouiz?
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Do you have that problem in Theano dev version? We did some fix for that
last year from memory, but maybe we didn't cover all cases?
Le 3 janv. 2017 07:44, "Thomas Wiecki" <[email protected]> a écrit :
When theano.config.floatX and the default numpy float dtype do not match
(as is the case when you want to use the GPU and set floatX to float32 but
numpy is on float64) it causes a lot of problems that require manual
casting of all the parameters that get passed in. We should automatically
cast everything that get's passed to floatX.
Not sure if there is a proper way to do that in theano, @nouiz
<https://github.com/nouiz>?
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@nouiz I wouldn't think so. What is supposed to happen when I set a tag.test_value of a theano float32 with a numpy array of dtype float64? Or when I multiply a theano tensor of float32 with a numpy array float 64?
When
theano.config.floatX
and the default numpy float dtype do not match (as is the case when you want to use the GPU and set floatX to float32 but numpy is on float64) it causes a lot of problems that require manual casting of all the parameters that get passed in. We should automatically cast everything that get's passed to floatX.Not sure if there is a proper way to do that in theano, @nouiz?
The text was updated successfully, but these errors were encountered: