Package | Description |
---|---|
org.deeplearning4j.nn.conf.layers | |
org.deeplearning4j.nn.conf.layers.convolutional | |
org.deeplearning4j.nn.conf.layers.util |
Modifier and Type | Class and Description |
---|---|
class |
ActivationLayer |
class |
BaseUpsamplingLayer
Upsampling base layer
|
class |
GlobalPoolingLayer
Global pooling layer - used to do pooling over time for RNNs, and 2d pooling for CNNs.
Supports the following PoolingType s: SUM, AVG, MAX, PNORMGlobal pooling layer can also handle mask arrays when dealing with variable length inputs. |
class |
Pooling1D
1D Pooling layer.
|
class |
Pooling2D
2D Pooling layer.
|
class |
SpaceToBatchLayer
Space to batch utility layer configuration for convolutional input types.
|
class |
SpaceToDepthLayer
Space to channels utility layer configuration for convolutional input types.
|
class |
Subsampling1DLayer
1D (temporal) subsampling layer.
|
class |
Subsampling3DLayer
3D subsampling / pooling layer for convolutional neural networks
|
class |
SubsamplingLayer
Subsampling layer also referred to as pooling in convolution neural nets
Supports the following pooling types: MAX, AVG, SUM, PNORM, NONE
|
class |
Upsampling1D
Upsampling 1D layer
|
class |
Upsampling2D
Upsampling 2D layer
|
class |
Upsampling3D
Upsampling 3D layer
|
class |
ZeroPadding1DLayer
Zero padding 1D layer for convolutional neural networks.
|
class |
ZeroPadding3DLayer
Zero padding 3D layer for convolutional neural networks.
|
class |
ZeroPaddingLayer
Zero padding layer for convolutional neural networks.
|
Modifier and Type | Class and Description |
---|---|
class |
Cropping1D
Cropping layer for convolutional (1d) neural networks.
|
class |
Cropping2D
Cropping layer for convolutional (2d) neural networks.
|
class |
Cropping3D
Cropping layer for convolutional (3d) neural networks.
|
Modifier and Type | Class and Description |
---|---|
class |
MaskLayer
MaskLayer applies the mask array to the forward pass activations, and backward pass gradients, passing through
this layer.
|
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