| #------------------------------------------------------------- |
| # |
| # 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 |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| # |
| #------------------------------------------------------------- |
| |
| /* |
| * Stochastic Gradient Descent (SGD) optimizer. |
| */ |
| |
| update = function(matrix[double] X, matrix[double] dX, double lr) |
| return (matrix[double] X) { |
| /* |
| * Performs a vanilla SGD update. |
| * |
| * Inputs: |
| * - X: Parameters to update, of shape (any, any). |
| * - dX: Gradient wrt `X` of a loss function being optimized, of |
| * same shape as `X`. |
| * - lr: Learning rate. |
| * |
| * Outputs: |
| * - X: Updated parameters `X`, of same shape as input `X`. |
| */ |
| X = X - lr*dX |
| } |
| |