[[https://clojars.org/clj-djl][https://img.shields.io/clojars/v/clj-djl.svg]] [[https://github.com/kimim/clj-djl/actions][https://github.com/scicloj/clj-djl/workflows/Clojure%20CI/badge.svg]]
A Clojure library wrap deep java library(DJL.ai)
[[https://scicloj.github.io/clj-djl][API documents]]
** Usage
clj-djl is available as a Maven artifact from Clojars. Please replace ~"X.Y.Z"~ with the latest version.
With Leiningen/Boot:
[clj-djl "X.Y.Z"]
With Clojure CLI/deps.edn:
clj-djl/clj-djl {:mvn/version "X.Y.Z"}
Latest version please refer to:
[[https://clojars.org/clj-djl][https://clojars.org/clj-djl/latest-version.svg]]
To list all available engine:
git clone https://github.com/kimim/clj-djl cd clj-djl lein run
** Unit testing
lein test
{:deps {clj-djl/clj-djl {:mvn/version "X.Y.Z"} clj-djl/dataframe {:mvn/version "0.1.2"}}}
~project.clj~ (for leiningen)
(defproject clj-d2l/house-prices "0.0.1" :dependencies [[clj-djl "X.Y.Z"] [clj-djl/dataframe "0.1.2"]] :source-paths ["src"])
~house_prices.clj~:
(ns clj-d2l.house-prices (:require [clj-djl.ndarray :as nd] [clj-djl.model :as m] [clj-djl.nn :as nn] [clj-djl.training :as t] [clj-djl.training.dataset :as ds] [clj-djl.training.loss :as loss] [clj-djl.training.optimizer :as optimizer] [clj-djl.training.tracker :as tracker] [clj-djl.training.listener :as listener] [clj-djl.nn.parameter :as param] [clj-djl.dataframe :as df] [clj-djl.dataframe.column-filters :as cf] [clj-djl.dataframe.functional :as dfn]))
(def train-ds-url "http://d2l-data.s3-accelerate.amazonaws.com/kaggle_house_pred_train.csv") (def test-ds-url "http://d2l-data.s3-accelerate.amazonaws.com/kaggle_house_pred_test.csv")
(def train-data (df/->dataframe train-ds-url)) (def test-data (df/->dataframe test-ds-url))
(df/select-by-index train-data (range 4) [0 1 2 -2 -1]) ;; http://d2l-data.s3-accelerate.amazonaws.com/kaggle_house_pred_train.csv [4 5]: ;; | Id | MSSubClass | MSZoning | SaleCondition | SalePrice | ;; |----|------------|----------|---------------|-----------| ;; | 1 | 60 | RL | Normal | 208500 | ;; | 2 | 20 | RL | Normal | 181500 | ;; | 3 | 60 | RL | Normal | 223500 | ;; | 4 | 70 | RL | Abnorml | 140000 |
(def all-features (-> train-data (df/drop-columns ["SalePrice"]) (df/concat test-data) (df/drop-columns ["Id"]) (df/replace-missing cf/numeric 0) (df/replace-missing cf/categorical "None") (df/update-columns cf/numeric
(dfn/standard-deviation %)))
(df/categorical->one-hot cf/categorical)))(def n-train (df/row-count train-data)) (def n-test (df/row-count test-data))
(def train-features (df/head all-features n-train)) (def test-features (df/tail all-features n-test)) (def train-labels (-> train-data (df/select-columns ["SalePrice"]) (df/update-columns cf/numeric
(def ndm (nd/new-base-manager)) (def train-nd (df/->ndarray ndm train-features)) (def test-nd (df/->ndarray ndm test-features)) (def label-nd (df/->ndarray ndm train-labels))
(defn do-train [nepochs learning-rate weight-decay batchsize] (let [train-dataset (ds/array-dataset {:data (nd/to-type train-nd :float32 false) :labels (nd/to-type label-nd :float32 false) :batchsize batchsize :shuffle false}) net (nn/sequential {:blocks (nn/linear {:units 1}) :initializer (nn/normal-initializer) :parameter param/weight}) cfg (t/training-config {:loss (loss/l2-loss) :optimizer (optimizer/sgd {:tracker (tracker/fixed learning-rate)}) :evaluator (t/accuracy) :listeners (listener/logging)})] (with-open [model (m/model {:name "mlp" :block net}) trainer (t/trainer model cfg)] (t/initialize trainer (nd/shape 1 310)) (t/set-metrics trainer (t/metrics)) (t/fit trainer nepochs train-dataset) (t/get-result trainer))))
(do-train 5 0.05 0 64) ;; => {:epochs 5, ;; :train-accuracy 0.87876713, ;; :train-loss 0.017618015, ;; :validate-accuracy ##NaN, ;; :validate-loss ##NaN}
[[https://github.com/scicloj/clj-d2l/blob/master/figure/house-prices.svg]]
Copyright © 2020 kimim
This project is licensed under the [[./LICENSE][Apache-2.0 License]].