Package smile.deep.layer
package smile.deep.layer
Neural network layers.
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ClassDescriptionAn adaptive average pooling that reduces a tensor by combining cells.An average pooling layer that reduces a tensor by combining cells, and assigning the average value of the input cells to the output cell.A batch normalization layer that re-centers and normalizes the output of one layer before feeding it to another.A batch normalization layer that re-centers and normalizes the output of one layer before feeding it to another.A convolutional layer.A dropout layer that randomly zeroes some of the elements of the input tensor with probability p during training.An embedding layer that is a simple lookup table that stores embeddings of a fixed dictionary and size.A fully connected layer with nonlinear activation function.Group normalization.A layer in the neural network.A block is combinations of one or more layers.A max pooling layer that reduces a tensor by combining cells, and assigning the maximum value of the input cells to the output cell.A block of sequential layers.