CNNArch is a descriptive language to model architectures of feedforward neural networks with a special focus on convolutional neural networks.
It is being developed for use in the MontiCar language family, along with CNNTrain, which configures the training of the network, and EmbeddedMontiArcDL, which integrates CNNArch into EmbeddedMontiArc.
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@@ -403,4 +410,13 @@ All predefined methods start with a capital letter and all constructed methods h
***size** (integer > 0, optional): The OneHot-vector's size. Can be omitted to automatically use the output size of the architecture.
***padding** ({"valid", "same", "no_loss"}, optional, default="same"): One of "valid", "same" or "no_loss". "valid" means no padding. "same" results in padding the input such that the output has the same length as the original input divided by the stride (rounded up). "no_loss" results in minimal padding such that each input is used by at least one filter (identical to "valid" if *stride* equals 1).
***no_bias** (boolean, optional, default=false): Whether to disable the bias parameter.