AbstractConv
Abstract Convolutional layer is a base block for building base types of convolutional layers of any dimensionality. It should simplify the internal calculations needed in most convolutional layers and abstract the naming weights for these layers. It keeps the actual implementation of convolutional layers, i.e., the kernel and bias learnable variables that should be used in child classes in actual implementations of these layers.
Parameters
name
of the layer to name its variables
Constructors
AbstractConv
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Creates AbstractConv object
Functions
buildFromInboundLayers
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Extend this function to define variables in layer.
computeOutputShape
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Computes output shape, based on inputShape and Layer type.
computeOutputShapeFromInboundLayers
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Computes output shape, based on input shapes of inbound layers.
forward
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Properties
hasActivation
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inboundLayers
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outboundLayers
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outputShape
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paramCount
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parentModel
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Inheritors
Conv1D
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Conv2D
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Conv3D
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ConvTranspose
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DepthwiseConv2D
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