blob: 7255efe8ebed926fb18dd20668b95d77486e577f [file] [log] [blame]
#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
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# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
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#-------------------------------------------------------------
/*
* L2 regularization.
*/
forward = function(matrix[double] X, double lambda)
return (double reg_loss) {
/*
* Computes the forward pass for an L2 regularization function.
*
* Inputs:
* - X: Inputs, of shape (any, any).
* - lambda: Regularization strength.
* A typical value is 0.01.
*
* Outputs:
* - reg_loss: Total regularization loss.
*/
reg_loss = 0.5 * lambda * sum(X^2)
}
backward = function(matrix[double] X, double lambda)
return (matrix[double] dX) {
/*
* Computes the backward pass for an L2 regularization function.
*
* Inputs:
* - X: Inputs, of shape (any, any).
* - lambda: Regularization strength.
*
* Outputs:
* - dX: Gradient wrt `X`, of same shape as `X`.
*/
dX = lambda * X
}