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.