In general, a “2d” tensor in CNNs is of size “Batch x Channels x Height x Width.” For the actual input to the network, channels is usually 3 for RGB or 1 if it’s greyscale. For the outputs of layers in the network, “output channels” is analagous to the number of neurons, or the number of hidden units, of a layer. So, the latter–output channels are the number of filters in one layer, while input channels are the number of filters in the incoming layer.