Variable batch size error

[terryrabinowitz]

Hello.
If I set the batch size to 'None' in the input layer of the model to allow different size batches, then I get the error: "ValueError: elements of reps must be scalars of integer dtype". This error goes away when I directly connect this input layer to an output layer but appears when I try and connect the input layer to the ntm layer.

Thank you for the help and the implementation!
Terry

[tristandeleu]

Hello Terry,
Indeed, as the initializations of the memory and hidden states (for the recurrent controller) heavily rely on the size of the batches, I simply assumed they were given beforehand. Thank you for pointing that out!
This should be fixed in #23
Like the other recurrent layers from Lasagne (eg. LSTMLayer), you can access the Theano variable corresponding to the size of the batches so that you can use ReshapeLayer

l_input = InputLayer((None, None, size), input_var=input_var)
batch_size, seqlen, _ = l_input.input_var.shape

[terryrabinowitz]

Fantastic! Thank you so much for the quick action!!

On Mon, Jun 13, 2016 at 12:08 PM, Tristan Deleu notifications@github.com
wrote:

Hello Terry,
Indeed, as the initializations of the memory and hidden states (for the
recurrent controller) heavily rely on the size of the batches, I simply
assumed they were given beforehand. Thank you for pointing that out!
This should be fixed in #23
#23
Like the other recurrent layers from Lasagne (eg. LSTMLayer), you can
access to the Theano variable corresponding to the size of the batches so
that you can use ReshapeLayer

l_input = InputLayer((None, None, size), input_var=input_var)
batch_size, seqlen, _ = l_input.input_var.shape

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