I'm trying the new grouped convolutions feature in the latest Theano version, so I ran a simple convnet with CIFAR-10: 32x32 RGB input images (batch size = 128), and the first convolutional layer has 9 feature maps. I want to have 3 feature maps per color, so if I understand it correctly, I should use num_groups=3 argument in conv2d op.
Again: I want the first conv. layer to process input images with 3 filters per color, so that each color channel is connected to 3 feature maps. Filters are 8x8 with stride 8 (non-overlapping) so the output feature maps should be 4x4 pixels. After adding the num_groups arg I got the following error: ValueError: images and kernel must have the same stack size Apply node that caused the error: GpuDnnConv{algo='time_on_shape_change', inplace=True, num_groups=3}(GpuContiguous.0, GpuContiguous.0, GpuAllocEmpty{ dtype='float32', context_name=None}.0, GpuDnnConvDesc{border_mode='valid', subsample=(8, 8), dilation=(1, 1), conv_mode='conv', precision='float32'}.0, Constant{1.0}, Constant{0.0}) Toposort index: 62 Inputs types: [GpuArrayType<None>(float32, 4D), GpuArrayType<None>(float32, 4D), GpuArrayType<None>(float32, 4D), <theano.gof.type.CDataType object at 0x7fa3900bc910>, Scalar(float32), Scalar(float32)] Inputs shapes: [(128, 3, 32, 32), (9, 3, 8, 8), (128, 9, 4, 4), 'No shapes', (), ()] Inputs strides: [(12288, 4096, 128, 4), (768, 256, 32, 4), (576, 64, 16, 4), 'No strides', (), ()] Inputs values: ['not shown', 'not shown', 'not shown', <capsule object NULL at 0x7fa372027f30>, 1.0, 0.0] Outputs clients: [[GpuElemwise{Add}[(0, 0)]<gpuarray>(GpuDnnConv{algo= 'time_on_shape_change', inplace=True, num_groups=3}.0, InplaceGpuDimShuffle{ x,0,x,x}.0)]] Thanks, Michael -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.