vm.tensorlayer.layers

Classes

class BatchNorm : The layer to apply the batch normalization. [Ioffe & Szegedy, 2015].

class Concat : The layer to concat tensors according to the given axis.

class Conv2d : The 2d convolution layer.

class Dense : The fully connected layer.

class Elementwise : The layer to combine inputs by applying element-wise operation.

class Flatten : The layer to reshape input into a matrix.

class GlobalMaxPool2d : The global max 2d pooling layer.

class GlobalMeanPool2d : The global mean 2d pooling layer.

class MaxPool2d : The max 2d pooling layer.

class MeanPool2d : The mean 2d pooling layer.

class Layer : The base layer class.

class LayerList : The sequential layer to stack a group of layers.

class Relu : The layer to apply the rectified linear unit. [Nair & Hinton, 2010].

class Reshape : The layer to change the dimensions of input.

class Transpose : The layer to permute the dimensions of input.

Functions

Input(…) : Create a placeholder as input.