(self, N)
return self.layers.set_batch_size(N)
Set the actual minibatch size, so even though the buffers are allocated considering
        excessive padding, the processing for some layers may be shortened.
        Currently most of the neon layers don't use that to control the processing. The
        interface is here only for when someone wants to set that information and experiment.

        Arguments:
            N:

        Returns:
Set the actual minibatch size, so even though the buffers are allocated considering
        excessive padding, the processing for some layers may be shortened.
        Currently most of the neon layers don't use that to control the processing. The
        interface is here only for when someone wants to set that information and experiment.
Set the actual minibatch size so even though the buffers are allocated considering excessive padding the processing for some layers may be shortened . Currently most of the neon layers don t use that to control the processing . The interface is here only for when someone wants to set that information and experiment .
def set_batch_size(self, N):
        """
        Set the actual minibatch size, so even though the buffers are allocated considering
        excessive padding, the processing for some layers may be shortened.
        Currently most of the neon layers don't use that to control the processing. The
        interface is here only for when someone wants to set that information and experiment.

        Arguments:
            N:

        Returns:

        """
        return self.layers.set_batch_size(N)
def set_batch_size ( self , N ) : return self . layers . set_batch_size ( N )