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new 40ae851 [MXNET-617] - Improve Clojure styles with cljfmt tools revise
(#11537)
40ae851 is described below
commit 40ae851bf64386d26bc49d42ff6da9a11d337606
Author: Burin Choomnuan <agilecreativ...@users.noreply.github.com>
AuthorDate: Tue Jul 3 16:53:47 2018 -0400
[MXNET-617] - Improve Clojure styles with cljfmt tools revise (#11537)
* Remove 'vi ci-test.sh' file
* Add the scripts to reformat the style with cljfmt
- Add lein-cljfmt-check to each project
- Add lein-cljfmt-fix to each project
* Add lein-cljfmt to the plugins vector
* Add steps to keep style consistent to README.md
* Run lein-cljfmt-fix on the main src/test codes
- Run $MXROOT/contrib/clojure-package/lein-cljfmt-fix
* Run lein cljfmt fix on the example projects
- Run $MXNET_ROOT/contrib/clojure-package/examples/lein-cljfmt-fix
* Use only one script in the base directory.
- Thanks to @marcoabreu for the suggestion/review
* Minor update to kick off the new build
---
contrib/clojure-package/README.md | 10 ++
.../examples/cnn-text-classification/project.clj | 5 +-
.../src/cnn_text_classification/classifier.clj | 6 +-
.../src/cnn_text_classification/data_helper.clj | 40 +++---
contrib/clojure-package/examples/gan/project.clj | 1 +
.../examples/gan/src/gan/gan_mnist.clj | 98 +++++++--------
.../clojure-package/examples/gan/src/gan/viz.clj | 3 +-
.../examples/imclassification/project.clj | 5 +-
.../src/imclassification/train_mnist.clj | 3 +-
.../clojure-package/examples/module/project.clj | 5 +-
.../examples/module/src/mnist_mlp.clj | 63 +++++-----
.../examples/multi-label/project.clj | 1 +
.../examples/multi-label/src/multi_label/core.clj | 8 +-
.../examples/neural-style/project.clj | 4 +-
.../neural-style/src/neural_style/core.clj | 48 +++----
.../neural-style/src/neural_style/model_vgg_19.clj | 13 +-
.../examples/pre-trained-models/project.clj | 1 +
.../src/pre_trained_models/fine_tune.clj | 21 ++--
.../src/pre_trained_models/predict_image.clj | 8 +-
.../clojure-package/examples/profiler/project.clj | 1 +
contrib/clojure-package/examples/rnn/project.clj | 5 +-
.../clojure-package/examples/rnn/src/rnn/lstm.clj | 30 ++---
.../examples/rnn/src/rnn/test_char_rnn.clj | 13 +-
.../examples/rnn/src/rnn/train_char_rnn.clj | 35 +++---
.../clojure-package/examples/rnn/src/rnn/util.clj | 17 ++-
.../clojure-package/examples/tutorial/project.clj | 1 +
.../examples/tutorial/src/tutorial/kvstore.clj | 6 +-
.../examples/tutorial/src/tutorial/module.clj | 53 ++------
.../examples/visualization/project.clj | 5 +-
.../visualization/src/visualization/core.clj | 10 +-
.../{vi ci-test.sh => lein-cljfmt-check} | 10 +-
.../{vi ci-test.sh => lein-cljfmt-fix} | 8 +-
contrib/clojure-package/project.clj | 3 +-
.../src/org/apache/clojure_mxnet/callback.clj | 1 -
.../src/org/apache/clojure_mxnet/context.clj | 1 -
.../src/org/apache/clojure_mxnet/dtype.clj | 1 -
.../src/org/apache/clojure_mxnet/eval_metric.clj | 1 -
.../src/org/apache/clojure_mxnet/executor.clj | 3 +-
.../src/org/apache/clojure_mxnet/initializer.clj | 8 +-
.../src/org/apache/clojure_mxnet/io.clj | 138 ++++++++++-----------
.../src/org/apache/clojure_mxnet/kvstore.clj | 18 ++-
.../org/apache/clojure_mxnet/kvstore_server.clj | 2 -
.../src/org/apache/clojure_mxnet/lr_scheduler.clj | 1 -
.../src/org/apache/clojure_mxnet/module.clj | 116 ++++++++---------
.../src/org/apache/clojure_mxnet/monitor.clj | 1 -
.../src/org/apache/clojure_mxnet/ndarray.clj | 9 +-
.../src/org/apache/clojure_mxnet/optimizer.clj | 31 +++--
.../src/org/apache/clojure_mxnet/profiler.clj | 2 +-
.../src/org/apache/clojure_mxnet/random.clj | 3 +-
.../src/org/apache/clojure_mxnet/shape.clj | 1 -
.../src/org/apache/clojure_mxnet/symbol.clj | 134 ++++++++++----------
.../src/org/apache/clojure_mxnet/util.clj | 10 +-
.../src/org/apache/clojure_mxnet/visualization.clj | 3 -
.../clojure-package/test/dev/generator_test.clj | 61 +++++----
.../test/org/apache/clojure_mxnet/conv_test.clj | 12 +-
.../org/apache/clojure_mxnet/executor_test.clj | 1 -
.../test/org/apache/clojure_mxnet/io_test.clj | 20 ++-
.../test/org/apache/clojure_mxnet/module_test.clj | 80 ++++++------
.../test/org/apache/clojure_mxnet/ndarray_test.clj | 18 +--
.../org/apache/clojure_mxnet/operator_test.clj | 138 +++++++++------------
.../org/apache/clojure_mxnet/optimizer_test.clj | 1 -
.../test/org/apache/clojure_mxnet/symbol_test.clj | 5 +-
62 files changed, 611 insertions(+), 749 deletions(-)
diff --git a/contrib/clojure-package/README.md
b/contrib/clojure-package/README.md
index bd226e0..6912f91 100644
--- a/contrib/clojure-package/README.md
+++ b/contrib/clojure-package/README.md
@@ -168,6 +168,16 @@ _Note: There is an error thrown in the generated code due
to some loading issues
To run the Code Coverage tool. Run `lein cloverage`.
+## Tools to keep style consistent
+
+To keep the style consistent for the project we include the script that make
it easier.
+There are two script in the base of the project and in each examples.
+
+To run it just see the following file. `lein-cljfmt-check` and
`lein-cljfmt-fix`.
+The first command will run and check and confirm if the code needed to be
updated to reflect the community style guide.
+The second command will apply the change and fix any inconsistent indentation
in place. This is recommendd to be done
+before the submit a new pull request so we can keep the style consistent
throughout the project.
+
## FAQ
diff --git
a/contrib/clojure-package/examples/cnn-text-classification/project.clj
b/contrib/clojure-package/examples/cnn-text-classification/project.clj
index f3eb21a..c592dcd 100644
--- a/contrib/clojure-package/examples/cnn-text-classification/project.clj
+++ b/contrib/clojure-package/examples/cnn-text-classification/project.clj
@@ -17,7 +17,8 @@
(defproject cnn-text-classification "0.1.0-SNAPSHOT"
:description "CNN text classification with MXNet"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]]
- :main cnn-text-classification.classifier
- :pedantic? :skip)
+ :pedantic? :skip
+ :main cnn-text-classification.classifier)
diff --git
a/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/classifier.clj
b/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/classifier.clj
index 756328c..29ff36f 100644
---
a/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/classifier.clj
+++
b/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/classifier.clj
@@ -85,7 +85,7 @@
:data-batch-size batch-size
:last-batch-handle "pad"})
test-data (mx-io/ndarray-iter [(get-in shuffled [:test :data])]
- {:label[(get-in shuffled [:test
:label])]
+ {:label [(get-in shuffled [:test
:label])]
:label-name "softmax_label"
:data-batch-size batch-size
:last-batch-handle "pad"})]
@@ -107,8 +107,6 @@
;; runs all the examples
#_(train-convnet {:embedding-size 50 :batch-size 100 :test-size 1000
:num-epoch 10})))
-
(comment
- (train-convnet {:devs [(context/cpu)] :embedding-size 50 :batch-size 10
:test-size 100 :num-epoch 10 :max-examples 1000})
- )
+ (train-convnet {:devs [(context/cpu)] :embedding-size 50 :batch-size 10
:test-size 100 :num-epoch 10 :max-examples 1000}))
diff --git
a/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/data_helper.clj
b/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/data_helper.clj
index e7a706f..7966521 100644
---
a/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/data_helper.clj
+++
b/contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/data_helper.clj
@@ -42,7 +42,6 @@
(.append sb (new String bs 0 i))))
(.toString sb)))
-
(defn get-float [b]
(-> 0
(bit-or (bit-shift-left (bit-and (aget b 0) 0xff) 0))
@@ -70,31 +69,27 @@
(println "Finished")
{:num-embed dim :word2vec word2vec})))
-
(defn clean-str [s]
(-> s
- (string/replace #"^A-Za-z0-9(),!?'`]" " ")
- (string/replace #"'s" " 's")
- (string/replace #"'ve" " 've")
- (string/replace #"n't" " n't")
- (string/replace #"'re" " 're")
- (string/replace #"'d" " 'd")
- (string/replace #"'ll" " 'll")
- (string/replace #"," " , ")
- (string/replace #"!" " ! ")
- (string/replace #"\(" " ( ")
- (string/replace #"\)" " ) ")
- (string/replace #"\?" " ? ")
- (string/replace #" {2,}" " ")
- (string/trim)))
-
-
- ;; Loads MR polarity data from files, splits the data into words and
generates labels.
+ (string/replace #"^A-Za-z0-9(),!?'`]" " ")
+ (string/replace #"'s" " 's")
+ (string/replace #"'ve" " 've")
+ (string/replace #"n't" " n't")
+ (string/replace #"'re" " 're")
+ (string/replace #"'d" " 'd")
+ (string/replace #"'ll" " 'll")
+ (string/replace #"," " , ")
+ (string/replace #"!" " ! ")
+ (string/replace #"\(" " ( ")
+ (string/replace #"\)" " ) ")
+ (string/replace #"\?" " ? ")
+ (string/replace #" {2,}" " ")
+ (string/trim)));; Loads MR polarity data from files, splits the data
into words and generates labels.
;; Returns split sentences and labels.
(defn load-mr-data-and-labels [path max-examples]
(println "Loading all the movie reviews from " path)
(let [positive-examples (mapv #(string/trim %) (-> (slurp (str path
"/rt-polarity.pos"))
- (string/split #"\n")))
+ (string/split #"\n")))
negative-examples (mapv #(string/trim %) (-> (slurp (str path
"/rt-polarity.neg"))
(string/split #"\n")))
positive-examples (into [] (if max-examples (take max-examples
positive-examples) positive-examples))
@@ -118,10 +113,7 @@
(if (pos? diff)
(into s (repeat diff padding-word))
s)))
- sentences)))
-
-
- ;; Map sentences and labels to vectors based on a pretrained embeddings
+ sentences)));; Map sentences and labels to vectors based on a
pretrained embeddings
(defn build-input-data-with-embeddings [sentences embedding-size embeddings]
(mapv (fn [sent]
(mapv (fn [word] (or (get embeddings word)
diff --git a/contrib/clojure-package/examples/gan/project.clj
b/contrib/clojure-package/examples/gan/project.clj
index 1469f9f..bebbc20 100644
--- a/contrib/clojure-package/examples/gan/project.clj
+++ b/contrib/clojure-package/examples/gan/project.clj
@@ -17,6 +17,7 @@
(defproject gan "0.1.0-SNAPSHOT"
:description "GAN MNIST with MXNet"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]
[nu.pattern/opencv "2.4.9-7"]]
diff --git a/contrib/clojure-package/examples/gan/src/gan/gan_mnist.clj
b/contrib/clojure-package/examples/gan/src/gan/gan_mnist.clj
index 42c116a..14dd2c5 100644
--- a/contrib/clojure-package/examples/gan/src/gan/gan_mnist.clj
+++ b/contrib/clojure-package/examples/gan/src/gan/gan_mnist.clj
@@ -32,7 +32,6 @@
[org.apache.clojure-mxnet.context :as context])
(:gen-class))
-
;; based off of
https://medium.com/@julsimon/generative-adversarial-networks-on-apache-mxnet-part-1-b6d39e6b5df1
@@ -57,7 +56,7 @@
(comment
;;This is for figuring out the convolution and deconvolution layers to
convert the image sizes
-
+
(defn conv-output-size [input-size kernel-size padding stride]
(float (inc (/ (- (+ input-size (* 2 padding)) kernel-size) stride))))
@@ -86,7 +85,6 @@
(def lr 0.0005) ;; learning rate
(def beta1 0.5)
-
(def label (sym/variable "label"))
(defn discriminator []
@@ -130,26 +128,24 @@
label [(ndarray/ones [batch-size 100 1 1])]]
(def my-iter (mx-io/ndarray-iter data)))
-
(defn save-img-gout [i n x]
(do
(viz/im-sav {:title (str "gout-" i "-" n)
- :output-path output-path
- :x x
- :flip false})))
+ :output-path output-path
+ :x x
+ :flip false})))
(defn save-img-diff [i n x]
(do (viz/im-sav {:title (str "diff-" i "-" n)
- :output-path output-path
- :x x
- :flip false})))
+ :output-path output-path
+ :x x
+ :flip false})))
(defn save-img-data [i n batch]
(do (viz/im-sav {:title (str "data-" i "-" n)
- :output-path output-path
- :x (first (mx-io/batch-data batch))
- :flip false})))
-
+ :output-path output-path
+ :x (first (mx-io/batch-data batch))
+ :flip false})))
(defn calc-diff [i n diff-d]
(let [diff (ndarray/copy diff-d)
@@ -161,8 +157,6 @@
(save-img-diff i n calc-diff))))
-
-
(defn train [devs]
(let [mod-d (-> (m/module (discriminator) {:contexts devs :data-names
["data"] :label-names ["label"]})
(m/bind {:data-shapes (mx-io/provide-data mnist-iter)
@@ -171,55 +165,53 @@
(m/init-params {:initializer (init/normal 0.02)})
(m/init-optimizer {:optimizer (opt/adam {:learning-rate lr
:wd 0.0 :beta1 beta1})}))
mod-g (-> (m/module (generator) {:contexts devs :data-names ["rand"]
:label-names nil})
- (m/bind {:data-shapes (mx-io/provide-data rand-noise-iter)})
- (m/init-params {:initializer (init/normal 0.02)})
- (m/init-optimizer {:optimizer (opt/adam {:learning-rate lr
:wd 0.0 :beta1 beta1})}))]
+ (m/bind {:data-shapes (mx-io/provide-data rand-noise-iter)})
+ (m/init-params {:initializer (init/normal 0.02)})
+ (m/init-optimizer {:optimizer (opt/adam {:learning-rate lr
:wd 0.0 :beta1 beta1})}))]
(println "Training for " num-epoch " epochs...")
(doseq [i (range num-epoch)]
- (mx-io/reduce-batches mnist-iter
- (fn [n batch]
- (let [rbatch (mx-io/next rand-noise-iter)
- out-g (-> mod-g
- (m/forward rbatch)
- (m/outputs))
+ (mx-io/reduce-batches mnist-iter
+ (fn [n batch]
+ (let [rbatch (mx-io/next rand-noise-iter)
+ out-g (-> mod-g
+ (m/forward rbatch)
+ (m/outputs))
;; update the discriminiator on the fake
- grads-f (mapv #(ndarray/copy (first %))
(-> mod-d
-
(m/forward {:data (first out-g) :label [(ndarray/zeros [batch-size])]})
-
(m/backward)
-
(m/grad-arrays)))
+ grads-f (mapv #(ndarray/copy (first %))
(-> mod-d
+
(m/forward {:data (first out-g) :label [(ndarray/zeros [batch-size])]})
+
(m/backward)
+
(m/grad-arrays)))
;; update the discrimintator on the real
- grads-r (-> mod-d
- (m/forward {:data
(mx-io/batch-data batch) :label [(ndarray/ones [batch-size])]})
- (m/backward)
- (m/grad-arrays))
- _ (mapv (fn [real fake] (let [r (first
real)]
- (ndarray/set r
(ndarray/+ r fake)))) grads-r grads-f)
- _ (m/update mod-d)
+ grads-r (-> mod-d
+ (m/forward {:data
(mx-io/batch-data batch) :label [(ndarray/ones [batch-size])]})
+ (m/backward)
+ (m/grad-arrays))
+ _ (mapv (fn [real fake] (let [r (first
real)]
+ (ndarray/set r
(ndarray/+ r fake)))) grads-r grads-f)
+ _ (m/update mod-d)
;; update the generator
- diff-d (-> mod-d
- (m/forward {:data (first out-g)
:label [(ndarray/ones [batch-size])]})
- (m/backward)
- (m/input-grads))
- _ (-> mod-g
- (m/backward (first diff-d))
- (m/update))]
- (when (zero? (mod n 100))
- (println "iteration = " i "number = " n)
- (save-img-gout i n (ndarray/copy (ffirst
out-g)))
- (save-img-data i n batch)
- (calc-diff i n (ffirst diff-d)))
- (inc n)))))))
+ diff-d (-> mod-d
+ (m/forward {:data (first out-g)
:label [(ndarray/ones [batch-size])]})
+ (m/backward)
+ (m/input-grads))
+ _ (-> mod-g
+ (m/backward (first diff-d))
+ (m/update))]
+ (when (zero? (mod n 100))
+ (println "iteration = " i "number = " n)
+ (save-img-gout i n (ndarray/copy (ffirst
out-g)))
+ (save-img-data i n batch)
+ (calc-diff i n (ffirst diff-d)))
+ (inc n)))))))
(defn -main [& args]
(let [[dev dev-num] args
devs (if (= dev ":gpu")
(mapv #(context/gpu %) (range (Integer/parseInt (or dev-num
"1"))))
(mapv #(context/cpu %) (range (Integer/parseInt (or dev-num
"1")))))]
- (println "Running with context devices of" devs)
+ (println "Running with context devices of" devs)
(train devs)))
(comment
- (train [(context/cpu)])
-
- )
+ (train [(context/cpu)]))
diff --git a/contrib/clojure-package/examples/gan/src/gan/viz.clj
b/contrib/clojure-package/examples/gan/src/gan/viz.clj
index 7fab13e..8b57b94 100644
--- a/contrib/clojure-package/examples/gan/src/gan/viz.clj
+++ b/contrib/clojure-package/examples/gan/src/gan/viz.clj
@@ -27,7 +27,6 @@
;;; Viz stuff
(OpenCV/loadShared)
-
(defn clip [x]
(->> x
(mapv #(* 255 %))
@@ -69,7 +68,7 @@
[n c h w] shape
totals (* h w)
raw-data (byte-array (clip (ndarray/to-array x)))
- row (.intValue(Math/sqrt n))
+ row (.intValue (Math/sqrt n))
col row
line-arrs (into [] (partition (* col c totals) raw-data))
line-mats (mapv (fn [line]
diff --git a/contrib/clojure-package/examples/imclassification/project.clj
b/contrib/clojure-package/examples/imclassification/project.clj
index 5c22d86..e4c34e7 100644
--- a/contrib/clojure-package/examples/imclassification/project.clj
+++ b/contrib/clojure-package/examples/imclassification/project.clj
@@ -17,7 +17,8 @@
(defproject imclassification "0.1.0-SNAPSHOT"
:description "Clojure examples for image classification"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]]
- :main imclassification.train-mnist
- :pedantic? :skip)
+ :pedantic? :skip
+ :main imclassification.train-mnist)
diff --git
a/contrib/clojure-package/examples/imclassification/src/imclassification/train_mnist.clj
b/contrib/clojure-package/examples/imclassification/src/imclassification/train_mnist.clj
index 44d3364..a43dc3b 100644
---
a/contrib/clojure-package/examples/imclassification/src/imclassification/train_mnist.clj
+++
b/contrib/clojure-package/examples/imclassification/src/imclassification/train_mnist.clj
@@ -111,5 +111,4 @@
(start devs)))
(comment
- (start [(context/cpu)])
- )
+ (start [(context/cpu)]))
diff --git a/contrib/clojure-package/examples/module/project.clj
b/contrib/clojure-package/examples/module/project.clj
index 2cd9796..7b32f32 100644
--- a/contrib/clojure-package/examples/module/project.clj
+++ b/contrib/clojure-package/examples/module/project.clj
@@ -17,8 +17,9 @@
(defproject module-examples "0.1.0-SNAPSHOT"
:description "Clojure examples for module"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]]
- :main mnist-mlp
- :pedantic? :skip)
+ :pedantic? :skip
+ :main mnist-mlp)
diff --git a/contrib/clojure-package/examples/module/src/mnist_mlp.clj
b/contrib/clojure-package/examples/module/src/mnist_mlp.clj
index 039a6eb..74edf71 100644
--- a/contrib/clojure-package/examples/module/src/mnist_mlp.clj
+++ b/contrib/clojure-package/examples/module/src/mnist_mlp.clj
@@ -116,7 +116,6 @@
(let [score (m/score mod {:eval-data test-data :eval-metric
(eval-metric/accuracy)})]
(println "High level predict score is " score))))
-
(defn run-predication-and-calc-accuracy-manually [devs]
;;; Gathers all the predictions at once with `predict-every-batch`
;;; then cycles thorugh the batches and manually calculates the accuracy
stats
@@ -128,23 +127,23 @@
(m/fit mod {:train-data train-data :eval-data test-data :num-epoch
num-epoch})
(let [preds (m/predict-every-batch mod {:eval-data test-data})
stats (mx-io/reduce-batches test-data
- (fn [r b]
- (let [pred-label (->> (ndarray/argmax-channel
(first (get preds (:index r))))
- (ndarray/->vec)
- (mapv int))
- label (->> (mx-io/batch-label b)
- (first)
- (ndarray/->vec)
- (mapv int))
- acc-sum (apply + (mapv (fn [pl l] (if (= pl
l) 1 0))
- pred-label label))]
- (-> r
- (update :index inc)
- (update :acc-cnt (fn [v] (+ v (count
pred-label))))
- (update :acc-sum (fn [v] (+ v
- (apply + (mapv
(fn [pl l] (if (= pl l) 1 0))
-
pred-label label))))))))
- {:acc-sum 0 :acc-cnt 0 :index 0})]
+ (fn [r b]
+ (let [pred-label (->>
(ndarray/argmax-channel (first (get preds (:index r))))
+ (ndarray/->vec)
+ (mapv int))
+ label (->> (mx-io/batch-label b)
+ (first)
+ (ndarray/->vec)
+ (mapv int))
+ acc-sum (apply + (mapv (fn [pl
l] (if (= pl l) 1 0))
+
pred-label label))]
+ (-> r
+ (update :index inc)
+ (update :acc-cnt (fn [v] (+ v
(count pred-label))))
+ (update :acc-sum (fn [v] (+ v
+
(apply + (mapv (fn [pl l] (if (= pl l) 1 0))
+
pred-label label))))))))
+ {:acc-sum 0 :acc-cnt 0 :index 0})]
(println "Stats: " stats)
(println "Accuracy: " (/ (:acc-sum stats)
(* 1.0 (:acc-cnt stats)))))))
@@ -159,19 +158,19 @@
;;; note only one function for training
(m/fit mod {:train-data train-data :eval-data test-data :num-epoch
num-epoch})
(mx-io/reduce-batches test-data
- (fn [r b]
- (let [preds (m/predict-batch mod b)
- pred-label (->> (ndarray/argmax-channel (first
preds))
- (ndarray/->vec)
- (mapv int))
- label (->> (mx-io/batch-label b)
- (first)
- (ndarray/->vec)
- (mapv int))
- acc (/ (apply + (mapv (fn [pl l] (if (= pl l)
1 0)) pred-label label))
- (* 1.0 (count pred-label)))]
- (println "Batch " r " acc: " acc)
- (inc r))))))
+ (fn [r b]
+ (let [preds (m/predict-batch mod b)
+ pred-label (->> (ndarray/argmax-channel
(first preds))
+ (ndarray/->vec)
+ (mapv int))
+ label (->> (mx-io/batch-label b)
+ (first)
+ (ndarray/->vec)
+ (mapv int))
+ acc (/ (apply + (mapv (fn [pl l] (if (= pl
l) 1 0)) pred-label label))
+ (* 1.0 (count pred-label)))]
+ (println "Batch " r " acc: " acc)
+ (inc r))))))
(defn run-all [devs]
(run-intermediate-level-api :devs devs)
@@ -190,7 +189,6 @@
(println "Running with context devices of" devs)
(run-all devs)))
-
(comment
;;; run all the example functions
@@ -237,4 +235,3 @@
;;=> Accuracy: 0.9494
)
-
diff --git a/contrib/clojure-package/examples/multi-label/project.clj
b/contrib/clojure-package/examples/multi-label/project.clj
index b67178b..88e3cff 100644
--- a/contrib/clojure-package/examples/multi-label/project.clj
+++ b/contrib/clojure-package/examples/multi-label/project.clj
@@ -17,6 +17,7 @@
(defproject multi-label "0.1.0-SNAPSHOT"
:description "Example of multi-label classification"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]]
:main multi-label.core)
diff --git
a/contrib/clojure-package/examples/multi-label/src/multi_label/core.clj
b/contrib/clojure-package/examples/multi-label/src/multi_label/core.clj
index 0707d42..e96783d 100644
--- a/contrib/clojure-package/examples/multi-label/src/multi_label/core.clj
+++ b/contrib/clojure-package/examples/multi-label/src/multi_label/core.clj
@@ -30,7 +30,6 @@
(java.util NoSuchElementException))
(:gen-class))
-
(def data-dir "data/")
(def batch-size 100)
(def num-epoch 1)
@@ -101,8 +100,8 @@
(vals)
last)]
(util/list-map
- {"softmax1_label" (mx-shape/->shape
shape)
- "softmax2_label" (mx-shape/->shape
shape)})))
+ {"softmax1_label" (mx-shape/->shape shape)
+ "softmax2_label" (mx-shape/->shape shape)})))
(provideData []
(.provideData data-iter)))))
@@ -153,7 +152,7 @@
(update :batch-num inc))))
{:sum [0 0] :batch-num 0})]
(println "Multi-accuracy " acc)
- (println "Multi-accuracy "(mapv #(/ % (:batch-num acc)) (:sum
acc)))))))
+ (println "Multi-accuracy " (mapv #(/ % (:batch-num acc)) (:sum
acc)))))))
(defn -main [& args]
(let [[dev dev-num] args
@@ -164,6 +163,5 @@
(println "Running with context devices of" devs)
(train devs)))
-
(comment
(train [(context/cpu)]))
diff --git a/contrib/clojure-package/examples/neural-style/project.clj
b/contrib/clojure-package/examples/neural-style/project.clj
index 4daf20f..f179618 100644
--- a/contrib/clojure-package/examples/neural-style/project.clj
+++ b/contrib/clojure-package/examples/neural-style/project.clj
@@ -17,9 +17,9 @@
(defproject neural-style "0.1.0-SNAPSHOT"
:description "Neural Style Transfer with MXNet"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]
[net.mikera/imagez "0.12.0"]
[thinktopic/think.image "0.4.16"]]
- :main neural-style.core
-)
+ :main neural-style.core)
diff --git
a/contrib/clojure-package/examples/neural-style/src/neural_style/core.clj
b/contrib/clojure-package/examples/neural-style/src/neural_style/core.clj
index 07b0a29..50f95c9 100644
--- a/contrib/clojure-package/examples/neural-style/src/neural_style/core.clj
+++ b/contrib/clojure-package/examples/neural-style/src/neural_style/core.clj
@@ -28,13 +28,10 @@
[mikera.image.filters :as img-filter]
[think.image.pixel :as pixel]
[neural-style.model-vgg-19 :as model-vgg-19])
- (:gen-class))
-
-
- ;; An Implementation of the paper A Neural Algorithm of Artistic Style
+ (:gen-class));; An Implementation of the paper A Neural Algorithm of
Artistic Style
;;by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge
-(def content-image "input/IMG_4343.jpg" )
+(def content-image "input/IMG_4343.jpg")
(def style-image "input/starry_night.jpg")
(def model-path "model/vgg19.params")
(def max-long-edge 600) ;; resize the content image
@@ -69,7 +66,7 @@
(let [simg (img/load-image path)
_ (println "The content image is size " {:height (img/height simg)
:width (img/width simg)})
factor (/ short-edge (img/width simg))
- resized-img (img/resize simg (* (img/width simg) factor) (*
(img/height simg) factor) )
+ resized-img (img/resize simg (* (img/width simg) factor) (*
(img/height simg) factor))
new-height (img/height resized-img)
new-width (img/width resized-img)]
(image->ndarray resized-img)))
@@ -97,29 +94,28 @@
_ (img/set-pixels new-image (int-array pixels))]
new-image))
-
(defn style-gram-symbol [input-size style]
(let [[_ output-shape _] (sym/infer-shape style {:data [1 3 (first
input-size) (second input-size)]})
output-shapes (mx-shape/->vec output-shape)
{:keys [gram-list grad-scale]} (doall (reduce
- (fn [result i]
- (let [shape (get
output-shapes i)
- [s0 s1 s2 s3] shape
- x (sym/reshape {:data
(sym/get style i) :target-shape [s1 (* s2 s3)] })
+ (fn [result i]
+ (let [shape (get
output-shapes i)
+ [s0 s1 s2 s3] shape
+ x (sym/reshape {:data
(sym/get style i) :target-shape [s1 (* s2 s3)]})
;; use fully
connected to quickly do dot(x x^T)
- gram
(sym/fully-connected {:data x :weight x :no-bias true :num-hidden s1})]
- (-> result
- (update :gram-list
conj gram)
- (update :grad-scale
conj (* s1 s2 s3 s1)))))
- {:gram-list [] :grad-scale []}
- (range (count
(sym/list-outputs style)))))]
+ gram
(sym/fully-connected {:data x :weight x :no-bias true :num-hidden s1})]
+ (-> result
+ (update :gram-list conj
gram)
+ (update :grad-scale
conj (* s1 s2 s3 s1)))))
+ {:gram-list [] :grad-scale []}
+ (range (count (sym/list-outputs
style)))))]
{:gram (sym/group (into [] gram-list)) :g-scale grad-scale}))
(defn get-loss [gram content]
(let [gram-loss (doall (mapv (fn [i]
- (let [gvar (sym/variable (str "target_gram_" i))]
- (sym/sum (sym/square (sym/- gvar (sym/get gram
i))))))
- (range (count (sym/list-outputs gram)))))
+ (let [gvar (sym/variable (str "target_gram_"
i))]
+ (sym/sum (sym/square (sym/- gvar (sym/get
gram i))))))
+ (range (count (sym/list-outputs gram)))))
cvar (sym/variable "target_content")
content-loss (sym/sum (sym/square (sym/- cvar content)))]
{:style-loss (sym/group gram-loss) :content-loss content-loss}))
@@ -137,7 +133,6 @@
(> a 255) 255
:else a))
-
(defn save-image [img filename radius blur?]
(let [filtered-image (if blur?
((img-filter/box-blur blur-radius blur-radius)
(postprocess-image img))
@@ -149,7 +144,7 @@
(defn get-tv-grad-executor [img ctx tv-weight]
(when (pos? tv-weight)
(let [img-shape (mx-shape/->vec (ndarray/shape img))
- n-channel(get img-shape 1)
+ n-channel (get img-shape 1)
s-img (sym/variable "img")
s-kernel (sym/variable "kernel")
channels (sym/split {:data s-img :axis 1 :num-outputs n-channel})
@@ -162,7 +157,6 @@
out (ndarray/* out tv-weight)]
(sym/bind out ctx {"img" img "kernel" kernel}))))
-
(defn train [devs]
(let [dev (first devs)
@@ -217,7 +211,7 @@
clip-norm (apply * (mx-shape/->vec (ndarray/shape img)))
tv-grad-executor (get-tv-grad-executor img dev tv-weight)
eps 0.0
- e 0 ]
+ e 0]
(doseq [i (range 20)]
(ndarray/set (:data model-executor) img)
(-> (:executor model-executor)
@@ -255,10 +249,6 @@
(println "Running with context devices of" devs)
(train devs)))
-
-
(comment
- (train [(context/cpu)])
-
- )
+ (train [(context/cpu)]))
diff --git
a/contrib/clojure-package/examples/neural-style/src/neural_style/model_vgg_19.clj
b/contrib/clojure-package/examples/neural-style/src/neural_style/model_vgg_19.clj
index 5fa11be..e7efa8c 100644
---
a/contrib/clojure-package/examples/neural-style/src/neural_style/model_vgg_19.clj
+++
b/contrib/clojure-package/examples/neural-style/src/neural_style/model_vgg_19.clj
@@ -71,7 +71,6 @@
content (sym/group [relu1-1])]
{:style style :content content}))
-
(defn get-executor [style content model-path input-size ctx]
(let [out (sym/group [style content])
;; make executor
@@ -83,12 +82,12 @@
;;; I'm not sure this is being set properly
pretrained (do (ndarray/load model-path))
arg-map (into {} (mapv (fn [[k v]]
- (let [pretrained-key (str "arg:" k)]
- (if (and (get pretrained pretrained-key) (not=
"data" k))
- (do (ndarray/set v (get pretrained
pretrained-key))
- [k v])
- [k v])))
- arg-map))
+ (let [pretrained-key (str "arg:" k)]
+ (if (and (get pretrained pretrained-key)
(not= "data" k))
+ (do (ndarray/set v (get pretrained
pretrained-key))
+ [k v])
+ [k v])))
+ arg-map))
exec (sym/bind out ctx arg-map grad-map)
outs (executor/outputs exec)]
{:executor exec
diff --git a/contrib/clojure-package/examples/pre-trained-models/project.clj
b/contrib/clojure-package/examples/pre-trained-models/project.clj
index 254f34a..e689e9a 100644
--- a/contrib/clojure-package/examples/pre-trained-models/project.clj
+++ b/contrib/clojure-package/examples/pre-trained-models/project.clj
@@ -17,6 +17,7 @@
(defproject pre-trained-models "0.1.0-SNAPSHOT"
:description "Example of using pre-trained models with MXNet"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]
[net.mikera/imagez "0.12.0"]
diff --git
a/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/fine_tune.clj
b/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/fine_tune.clj
index a73aa30..f2b9edd 100644
---
a/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/fine_tune.clj
+++
b/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/fine_tune.clj
@@ -34,7 +34,6 @@
(def model-dir "model")
(def batch-size 16)
-
;;; image set is http://www.vision.caltech.edu/Image_Datasets/Caltech101/
;; Pictures of objects belonging to 101 categories. About 40 to 800 images per
category. Most categories have about 50 images
@@ -49,13 +48,13 @@
:rand-mirror true}))
(def val-iter (mx-io/image-record-iter
- {:path-imgrec "caltech-256/caltech-256-60-val.rec"
- :data-name "data"
- :label-name "softmax_label"
- :batch-size batch-size
- :data-shape [3 224 224]
- :rand-crop false
- :rand-mirror false}))
+ {:path-imgrec "caltech-256/caltech-256-60-val.rec"
+ :data-name "data"
+ :label-name "softmax_label"
+ :batch-size batch-size
+ :data-shape [3 224 224]
+ :rand-crop false
+ :rand-mirror false}))
(defn get-model []
(let [mod (m/load-checkpoint {:prefix (str model-dir "/resnet-50") :epoch
0})]
@@ -104,9 +103,7 @@
(mapv #(context/gpu %) (range (Integer/parseInt (or dev-num
"1"))))
(mapv #(context/cpu %) (range (Integer/parseInt (or dev-num
"1")))))]
(println "Running with context devices of" devs)
- (fine-tune! devs))
- )
-
+ (fine-tune! devs)))
(comment
@@ -126,7 +123,5 @@
;; INFO ml.dmlc.mxnet.Callback$Speedometer: Epoch[0] Batch [120] Speed:
3.44 samples/sec Train-accuracy=0.040806
;; INFO ml.dmlc.mxnet.Callback$Speedometer: Epoch[0] Batch [130] Speed:
3.41 samples/sec Train-accuracy=0.043893
;; INFO ml.dmlc.mxnet.Callback$Speedometer: Epoch[0] Batch [140] Speed:
3.42 samples/sec Train-accuracy=0.045213
-
)
-
diff --git
a/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/predict_image.clj
b/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/predict_image.clj
index ee25e4c..12bdb12 100644
---
a/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/predict_image.clj
+++
b/contrib/clojure-package/examples/pre-trained-models/src/pre_trained_models/predict_image.clj
@@ -39,7 +39,6 @@
out (io/output-stream file)]
(io/copy in out)))
-
(defn get-image [url show?]
(let [fname "test-image.jpg"
_ (download url fname)
@@ -54,8 +53,8 @@
pixels)]
(when show? (img/show image))
(-> rgb-pixels
- (flatten)
- (ndarray/array [1 num-channels h w]))))
+ (flatten)
+ (ndarray/array [1 num-channels h w]))))
(defn predict [img-url show?]
(let [mod (m/load-checkpoint {:prefix (str model-dir "/resnet-152") :epoch
0})
@@ -110,6 +109,5 @@
;; {:prob 0.023329297, :label "n02083346 canine, canid"})
(feature-extraction) ;=> [1 2048]
-
- )
+)
diff --git a/contrib/clojure-package/examples/profiler/project.clj
b/contrib/clojure-package/examples/profiler/project.clj
index ca2fad2..6ea2dfe 100644
--- a/contrib/clojure-package/examples/profiler/project.clj
+++ b/contrib/clojure-package/examples/profiler/project.clj
@@ -16,6 +16,7 @@
;;
(defproject profiler "0.1.0-SNAPSHOT"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]]
:main profiler.core)
diff --git a/contrib/clojure-package/examples/rnn/project.clj
b/contrib/clojure-package/examples/rnn/project.clj
index ff00a10..0175591 100644
--- a/contrib/clojure-package/examples/rnn/project.clj
+++ b/contrib/clojure-package/examples/rnn/project.clj
@@ -17,6 +17,7 @@
(defproject rnn "0.1.0-SNAPSHOT"
:description "RNN example"
- :main rnn.train-char-rnn
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
- [org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]])
+ [org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]]
+ :main rnn.train-char-rnn)
diff --git a/contrib/clojure-package/examples/rnn/src/rnn/lstm.clj
b/contrib/clojure-package/examples/rnn/src/rnn/lstm.clj
index ec8e9e8..fb3a8f3 100644
--- a/contrib/clojure-package/examples/rnn/src/rnn/lstm.clj
+++ b/contrib/clojure-package/examples/rnn/src/rnn/lstm.clj
@@ -56,14 +56,14 @@
cls-weight (sym/variable "cls_weight")
cls-bias (sym/variable "cls_bias")
param-cells (mapv (fn [i]
- (lstm-param (sym/variable (str "l" i
"_i2h_weight"))
- (sym/variable (str "l" i "_i2h_bias"))
- (sym/variable (str "l" i
"_h2h_weight"))
- (sym/variable (str "l" i
"_h2h_bias"))))
- (range 0 num-lstm-layer))
+ (lstm-param (sym/variable (str "l" i
"_i2h_weight"))
+ (sym/variable (str "l" i "_i2h_bias"))
+ (sym/variable (str "l" i
"_h2h_weight"))
+ (sym/variable (str "l" i
"_h2h_bias"))))
+ (range 0 num-lstm-layer))
last-states (mapv (fn [i]
- (lstm-state (sym/variable (str "l" i
"_init_c_beta"))
- (sym/variable (str "l" i
"_init_h_beta"))))
+ (lstm-state (sym/variable (str "l" i
"_init_c_beta"))
+ (sym/variable (str "l" i
"_init_h_beta"))))
(range 0 num-lstm-layer))
;; embedding layer
data (sym/variable "data")
@@ -76,7 +76,7 @@
hidden-all (doall (for [seq-idx (range seq-len)]
(let [hidden (:h (last (loop [i 0
hidden (sym/get
wordvec seq-idx)
- next-states []]
+ next-states []]
(if (= i num-lstm-layer)
next-states
(let [dp-ratio (if
(zero? i) 0 dropout)
@@ -108,14 +108,14 @@
cls-weight (sym/variable "cls_weight")
cls-bias (sym/variable "cls_bias")
param-cells (mapv (fn [i]
- (lstm-param (sym/variable (str "l" i
"_i2h_weight"))
- (sym/variable (str "l" i "_i2h_bias"))
- (sym/variable (str "l" i
"_h2h_weight"))
- (sym/variable (str "l" i
"_h2h_bias"))))
- (range 0 num-lstm-layer))
+ (lstm-param (sym/variable (str "l" i
"_i2h_weight"))
+ (sym/variable (str "l" i "_i2h_bias"))
+ (sym/variable (str "l" i
"_h2h_weight"))
+ (sym/variable (str "l" i
"_h2h_bias"))))
+ (range 0 num-lstm-layer))
last-states (mapv (fn [i]
- (lstm-state (sym/variable (str "l" i
"_init_c_beta"))
- (sym/variable (str "l" i
"_init_h_beta"))))
+ (lstm-state (sym/variable (str "l" i
"_init_c_beta"))
+ (sym/variable (str "l" i
"_init_h_beta"))))
(range 0 num-lstm-layer))
data (sym/variable "data")
dp-ratio 0
diff --git a/contrib/clojure-package/examples/rnn/src/rnn/test_char_rnn.clj
b/contrib/clojure-package/examples/rnn/src/rnn/test_char_rnn.clj
index 35e1a18..d03b1a6 100644
--- a/contrib/clojure-package/examples/rnn/src/rnn/test_char_rnn.clj
+++ b/contrib/clojure-package/examples/rnn/src/rnn/test_char_rnn.clj
@@ -37,11 +37,11 @@
(let [trained-mod (m/load-checkpoint {:prefix model-prefix :epoch epoch-num})
trained-arg-params (m/arg-params trained-mod)
model (lstm/lstm-inference-model {:num-lstm-layer 3
- :input-size (inc (count vocab))
- :num-label (inc (count vocab))
- :num-hidden num-hidden
- :num-embed num-embed
- :arg-params trained-arg-params})
+ :input-size (inc (count vocab))
+ :num-label (inc (count vocab))
+ :num-hidden num-hidden
+ :num-embed num-embed
+ :arg-params trained-arg-params})
input-ndarray (ndarray/zeros [1])
revert-vocab (util/make-revert-vocab vocab)
fix-dict (into [""]
@@ -68,7 +68,6 @@
output
(str output next-char)))))))))
-
(comment
(rnn-test "data/obama" 75 200 false)
@@ -76,4 +75,4 @@
(rnn-test "data/obama" 75 200 true)
;=>"The joke before them prepared for five years ago, we only hear a chance
to lose our efforts and they made striggling procedural deficit at the city
between a politics in the efforts on the Edmund Pett"
- )
+)
diff --git a/contrib/clojure-package/examples/rnn/src/rnn/train_char_rnn.clj
b/contrib/clojure-package/examples/rnn/src/rnn/train_char_rnn.clj
index d246760..29aba26 100644
--- a/contrib/clojure-package/examples/rnn/src/rnn/train_char_rnn.clj
+++ b/contrib/clojure-package/examples/rnn/src/rnn/train_char_rnn.clj
@@ -69,15 +69,15 @@
(defn build-training-data [path]
- (let [content (slurp path)
- sentences (string/split content #"\n")
- max-length (first buckets)
- padding-int 0]
- (doall (for [sentence sentences]
- (let [ids (mapv #(get vocab %) sentence)]
- (if (>= (count ids) max-length)
- (into [] (take max-length ids))
- (into ids (repeat (- max-length (count ids)) 0))))))))
+ (let [content (slurp path)
+ sentences (string/split content #"\n")
+ max-length (first buckets)
+ padding-int 0]
+ (doall (for [sentence sentences]
+ (let [ids (mapv #(get vocab %) sentence)]
+ (if (>= (count ids) max-length)
+ (into [] (take max-length ids))
+ (into ids (repeat (- max-length (count ids)) 0))))))))
(defn build-labels [train-data]
;; want to learn the next char some rotate by 1
@@ -90,7 +90,6 @@
(first)
(apply hash-map)))
-
(defn train [devs]
(let [;; initialize the states for the lstm
init-c (into {} (map (fn [l]
@@ -118,7 +117,7 @@
rnn-mod (-> (m/module rnn-sym {:contexts devs})
(m/bind {:data-shapes (into (mx-io/provide-data train-iter)
- (mapv (fn [[k v]] {:name k :shape
v}) init-states))
+ (mapv (fn [[k v]] {:name k
:shape v}) init-states))
:label-shapes (mx-io/provide-label train-iter)})
(m/init-params {:initializer (init/xavier {:factor-type
"in" :magnitude 2.34})})
(m/init-optimizer {:optimizer (optimizer/adam
{:learning-rate learning-rate :wd 0.0001})}))
@@ -138,8 +137,7 @@
(mapv #(Math/log %))
(mapv #(* -1.0 %))
(apply +))]
- (float (Math/exp (/ result (count labels)))))
- )
+ (float (Math/exp (/ result (count labels))))))
"perplexity")]
@@ -151,11 +149,11 @@
(fn [batch-num batch]
(let [batch (mx-io/next train-iter)]
(-> rnn-mod
- (m/forward (mx-io/data-batch {:data (into (mx-io/batch-data batch)
init-states-data)
- :label (mx-io/batch-label batch)}))
- (m/update-metric metric (mx-io/batch-label batch))
- (m/backward)
- (m/update))
+ (m/forward (mx-io/data-batch {:data (into (mx-io/batch-data
batch) init-states-data)
+ :label (mx-io/batch-label
batch)}))
+ (m/update-metric metric (mx-io/batch-label batch))
+ (m/backward)
+ (m/update))
(when (zero? (mod batch-num 10))
(println "Eval metric for batch-num " batch-num " is "
(eval-metric/get metric)))
(inc batch-num))))
@@ -171,7 +169,6 @@
(println (test-rnn/rnn-test "data/obama" 75 200 true))
(println "=====")))
-
(defn -main [& args]
(let [[dev dev-num] args
devs (if (= dev ":gpu")
diff --git a/contrib/clojure-package/examples/rnn/src/rnn/util.clj
b/contrib/clojure-package/examples/rnn/src/rnn/util.clj
index 27e2132..bce5bb7 100644
--- a/contrib/clojure-package/examples/rnn/src/rnn/util.clj
+++ b/contrib/clojure-package/examples/rnn/src/rnn/util.clj
@@ -21,13 +21,13 @@
(defn build-vocab [path]
(let [content (slurp path)
vocab-map (reduce (fn [{:keys [vocab idx] :as result} c]
- (if (get vocab c)
- result
- (-> result
- (update :vocab assoc c (inc idx))
- (update :idx inc))))
- {:vocab {} :idx 0} ;; 0 is used for padding
- content)]
+ (if (get vocab c)
+ result
+ (-> result
+ (update :vocab assoc c (inc idx))
+ (update :idx inc))))
+ {:vocab {} :idx 0} ;; 0 is used for padding
+ content)]
(:vocab vocab-map)))
(defn make-revert-vocab [vmap]
@@ -42,10 +42,9 @@
(defn cdf [weights]
(let [total (* 1.0 (apply + weights))
- csums (reduce (fn [cumsum w] (conj cumsum (+ (or (last cumsum) 0) w))
) [] weights)]
+ csums (reduce (fn [cumsum w] (conj cumsum (+ (or (last cumsum) 0) w)))
[] weights)]
(mapv #(/ % total) csums)))
-
(defn choice [population weights]
(assert (= (count population) (count weights)))
(let [cdf-vals (cdf weights)
diff --git a/contrib/clojure-package/examples/tutorial/project.clj
b/contrib/clojure-package/examples/tutorial/project.clj
index 027c1d3..ab7606e 100644
--- a/contrib/clojure-package/examples/tutorial/project.clj
+++ b/contrib/clojure-package/examples/tutorial/project.clj
@@ -17,5 +17,6 @@
(defproject tutorial "0.1.0-SNAPSHOT"
:description "MXNET tutorials"
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
[org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]])
diff --git a/contrib/clojure-package/examples/tutorial/src/tutorial/kvstore.clj
b/contrib/clojure-package/examples/tutorial/src/tutorial/kvstore.clj
index 5780ac2..558b21f 100644
--- a/contrib/clojure-package/examples/tutorial/src/tutorial/kvstore.clj
+++ b/contrib/clojure-package/examples/tutorial/src/tutorial/kvstore.clj
@@ -48,7 +48,7 @@
(def cpus [(context/cpu 0) (context/cpu 1) (context/cpu 2)])
(def b [(ndarray/ones shape {:ctx (nth cpus 0)})
(ndarray/ones shape {:ctx (nth cpus 1)})
- (ndarray/ones shape {:ctx (nth cpus 2)}) ])
+ (ndarray/ones shape {:ctx (nth cpus 2)})])
(kvstore/push kv ["3" "3" "3"] b)
(kvstore/pull kv "3" a)
(ndarray/->vec a) ;=> [3.0 3.0 3.0 3.0 3.0 3.0]
@@ -57,7 +57,7 @@
;;Pull
;;You’ve already seen how to pull a single key-value pair. Similar to the way
that you use the push command, you can pull the value into several devices with
a single call.
(def b [(ndarray/ones shape {:ctx (context/cpu 0)})
- (ndarray/ones shape {:ctx (context/cpu 1)}) ])
+ (ndarray/ones shape {:ctx (context/cpu 1)})])
(kvstore/pull kv ["3" "3"] b)
(map ndarray/->vec b) ;=> ([3.0 3.0 3.0 3.0 3.0 3.0] [3.0 3.0 3.0 3.0 3.0 3.0])
@@ -67,7 +67,7 @@
(def ks ["5" "7" "9"])
(kvstore/init kv ks [(ndarray/ones shape) (ndarray/ones shape) (ndarray/ones
shape)])
(kvstore/push kv ks [(ndarray/ones shape) (ndarray/ones shape) (ndarray/ones
shape)])
-(def b [(ndarray/zeros shape) (ndarray/zeros shape)(ndarray/zeros shape)])
+(def b [(ndarray/zeros shape) (ndarray/zeros shape) (ndarray/zeros shape)])
(kvstore/pull kv ks b)
(map ndarray/->vec b);=> ([1.0 1.0 1.0 1.0 1.0 1.0] [1.0 1.0 1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0 1.0 1.0])
diff --git a/contrib/clojure-package/examples/tutorial/src/tutorial/module.clj
b/contrib/clojure-package/examples/tutorial/src/tutorial/module.clj
index ad5ff13..0009a01 100644
--- a/contrib/clojure-package/examples/tutorial/src/tutorial/module.clj
+++ b/contrib/clojure-package/examples/tutorial/src/tutorial/module.clj
@@ -31,14 +31,14 @@
;;; Load the MNIST datasets
(def train-data (mx-io/mnist-iter {:image (str data-dir
"train-images-idx3-ubyte")
- :label (str data-dir
"train-labels-idx1-ubyte")
- :label-name "softmax_label"
- :input-shape [784]
- :batch-size 10
- :shuffle true
- :flat true
- :silent false
- :seed 10}))
+ :label (str data-dir
"train-labels-idx1-ubyte")
+ :label-name "softmax_label"
+ :input-shape [784]
+ :batch-size 10
+ :shuffle true
+ :flat true
+ :silent false
+ :seed 10}))
(def test-data (mx-io/mnist-iter {:image (str data-dir
"t10k-images-idx3-ubyte")
:label (str data-dir
"t10k-labels-idx1-ubyte")
@@ -131,10 +131,10 @@
(let [save-prefix "my-model"]
(doseq [epoch-num (range 3)]
- (mx-io/do-batches train-data (fn [batch
+ (mx-io/do-batches train-data (fn [batch
;; do something
- ]))
- (m/save-checkpoint mod {:prefix save-prefix :epoch epoch-num
:save-opt-states true})))
+]))
+ (m/save-checkpoint mod {:prefix save-prefix :epoch epoch-num
:save-opt-states true})))
;; INFO ml.dmlc.mxnet.module.Module: Saved checkpoint to my-model-0000.params
;; INFO ml.dmlc.mxnet.module.Module: Saved optimizer state to
my-model-0000.states
@@ -155,8 +155,8 @@
;;To get current parameters, use `params`
(let [[arg-params aux-params] (m/params new-mod)]
- {:arg-params arg-params
- :aux-params aux-params})
+ {:arg-params arg-params
+ :aux-params aux-params})
;; {:arg-params
;; {"fc3_bias"
@@ -190,30 +190,3 @@
;;Create fit-params, and then use it to set `begin-epoch` so that fit() knows
to resume from a saved epoch.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/contrib/clojure-package/examples/visualization/project.clj
b/contrib/clojure-package/examples/visualization/project.clj
index 6dc7c49..99d0e40 100644
--- a/contrib/clojure-package/examples/visualization/project.clj
+++ b/contrib/clojure-package/examples/visualization/project.clj
@@ -17,6 +17,7 @@
(defproject visualization "0.1.0-SNAPSHOT"
:description "Visualization example"
- :main visualization.core
+ :plugins [[lein-cljfmt "0.5.7"]]
:dependencies [[org.clojure/clojure "1.9.0"]
- [org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]])
+ [org.apache.mxnet.contrib.clojure/clojure-mxnet
"1.3.0-SNAPSHOT"]]
+ :main visualization.core)
diff --git
a/contrib/clojure-package/examples/visualization/src/visualization/core.clj
b/contrib/clojure-package/examples/visualization/src/visualization/core.clj
index 58980a0..31cce92 100644
--- a/contrib/clojure-package/examples/visualization/src/visualization/core.clj
+++ b/contrib/clojure-package/examples/visualization/src/visualization/core.clj
@@ -25,10 +25,7 @@
#_(sym/convolution "conv1" {:data data :kernel [3 3] :num-filter 32
:stride [2 2]})
#_(sym/batch-norm "bn1" {:data data})
#_(sym/activation "relu1" {:data data :act-type "relu"})
- #_(sym/pooling "mp1" {:data data :kernel [2 2] :pool-type "max" :stride [2
2]})
-
-
- #_(sym/convolution "conv2" {:data data :kernel [3 3] :num-filter 32
:stride [2 2]})
+ #_(sym/pooling "mp1" {:data data :kernel [2 2] :pool-type "max" :stride [2
2]}) #_(sym/convolution "conv2" {:data data :kernel [3 3] :num-filter 32
:stride [2 2]})
#_(sym/batch-norm "bn2" {:data data})
#_(sym/activation "relu2" {:data data :act-type "relu"})
#_(sym/pooling "mp2" {:data data :kernel [2 2] :pool-type "max" :stride [2
2]})
@@ -39,12 +36,11 @@
(defn test-viz []
(let [dot (viz/plot-network (get-symbol)
- {"data" [1 1 28 28]}
- {:title "foo" :node-attrs {:shape "oval" :fixedsize
"false"}})]
+ {"data" [1 1 28 28]}
+ {:title "foo" :node-attrs {:shape "oval"
:fixedsize "false"}})]
(viz/render dot "testviz" "./")))
(defn -main [& args]
(do (test-viz)
(println "Check for the testviz.pdf file in the project directory")))
-
diff --git a/contrib/clojure-package/vi ci-test.sh
b/contrib/clojure-package/lein-cljfmt-check
old mode 100644
new mode 100755
similarity index 73%
copy from contrib/clojure-package/vi ci-test.sh
copy to contrib/clojure-package/lein-cljfmt-check
index dc12f13..93f2d3c
--- a/contrib/clojure-package/vi ci-test.sh
+++ b/contrib/clojure-package/lein-cljfmt-check
@@ -1,4 +1,4 @@
-#!/bin/bash
+#!/usr/bin/env sh
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
@@ -17,8 +17,8 @@
# specific language governing permissions and limitations
# under the License.
+set -vx
-set -evx
-
-cd contrib/clojure-package
-lein test
+lein cljfmt check `find ./src/org/apache/clojure_mxnet -depth 1 -type f -iname
"*.clj" | grep -v /gen/`
+lein cljfmt check `find ./test -type f -iname "*.clj" | grep -v
/test/good-test`
+lein cljfmt check `find ./examples -type f -iname "*.clj" | grep -v /scripts/`
diff --git a/contrib/clojure-package/vi ci-test.sh
b/contrib/clojure-package/lein-cljfmt-fix
old mode 100644
new mode 100755
similarity index 74%
rename from contrib/clojure-package/vi ci-test.sh
rename to contrib/clojure-package/lein-cljfmt-fix
index dc12f13..8c35892
--- a/contrib/clojure-package/vi ci-test.sh
+++ b/contrib/clojure-package/lein-cljfmt-fix
@@ -1,4 +1,4 @@
-#!/bin/bash
+#!/usr/bin/env sh
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
@@ -17,8 +17,8 @@
# specific language governing permissions and limitations
# under the License.
-
set -evx
-cd contrib/clojure-package
-lein test
+lein cljfmt fix `find ./src/org/apache/clojure_mxnet -type f -iname "*.clj" |
grep -v /gen/`
+lein cljfmt fix `find ./test -type f -iname "*.clj" | grep -v /test/good-test`
+lein cljfmt fix `find ./examples -type f -iname "*.clj" | grep -v /scripts/`
diff --git a/contrib/clojure-package/project.clj
b/contrib/clojure-package/project.clj
index 42da163..5d94fa7 100644
--- a/contrib/clojure-package/project.clj
+++ b/contrib/clojure-package/project.clj
@@ -34,7 +34,8 @@
[org.slf4j/slf4j-log4j12 "1.7.25" :exclusions
[org.slf4j/slf4j-api]]]
:pedantic? :skip
:plugins [[lein-codox "0.10.3" :exclusions [org.clojure/clojure]]
- [lein-cloverage "1.0.10" :exclusions [org.clojure/clojure]]]
+ [lein-cloverage "1.0.10" :exclusions [org.clojure/clojure]]
+ [lein-cljfmt "0.5.7"]]
:codox {:namespaces [#"^org\.apache\.clojure-mxnet\.(?!gen).*"]}
:aot [dev.generator]
:repositories [["staging" {:url
"https://repository.apache.org/content/repositories/staging";
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/callback.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/callback.clj
index d1c6d88..c007720 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/callback.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/callback.clj
@@ -18,7 +18,6 @@
(ns org.apache.clojure-mxnet.callback
(:import (org.apache.mxnet Callback$Speedometer)))
-
;;; used to track status during epoch
(defn speedometer
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/context.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/context.clj
index f89fd58..126838c 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/context.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/context.clj
@@ -18,7 +18,6 @@
(ns org.apache.clojure-mxnet.context
(:import (org.apache.mxnet Context)))
-
(defn cpu
([device-id]
(new Context "cpu" device-id))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/dtype.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/dtype.clj
index d21fe7f..1d96c22 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/dtype.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/dtype.clj
@@ -18,7 +18,6 @@
(ns org.apache.clojure-mxnet.dtype
(:import (org.apache.mxnet DType)))
-
(def UINT8 (DType/UInt8))
(def INT32 (DType/Int32))
(def FLOAT16 (DType/Float16))
diff --git
a/contrib/clojure-package/src/org/apache/clojure_mxnet/eval_metric.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/eval_metric.clj
index 3cddb1f..1946103 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/eval_metric.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/eval_metric.clj
@@ -20,7 +20,6 @@
(:require [org.apache.clojure-mxnet.util :as util])
(:import (org.apache.mxnet Accuracy TopKAccuracy F1 Perplexity MAE MSE RMSE
CustomMetric)))
-
(defn accuracy
"Basic Accuracy Metric"
[]
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/executor.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/executor.clj
index d1f8df9..4f4155e 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/executor.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/executor.clj
@@ -21,7 +21,6 @@
[org.apache.clojure-mxnet.ndarray :as ndarray]
[org.apache.clojure-mxnet.shape :as mx-shape]))
-
;; need to revisit to get all functions
(defn ->vec [nd-array]
@@ -96,7 +95,7 @@
(do
(let [kwargs-shapes (zipmap (keys kwargs)
(mapv (fn [v] (if (vector? v)
(mx-shape/->shape v) v)) (vals kwargs)))]
- (.reshape executor partial-shaping allow-up-sizing (util/convert-map
kwargs-shapes)))
+ (.reshape executor partial-shaping allow-up-sizing (util/convert-map
kwargs-shapes)))
executor))
([executor kwargs]
(reshape executor kwargs {})))
diff --git
a/contrib/clojure-package/src/org/apache/clojure_mxnet/initializer.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/initializer.clj
index 58413c8..a161759 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/initializer.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/initializer.clj
@@ -20,7 +20,7 @@
(:import (org.apache.mxnet Uniform Normal Xavier)))
(defn uniform
- "Initialize the weight with uniform [-scale, scale]
+ "Initialize the weight with uniform [-scale, scale]
scale - The scale of uniform distribution"
([scale]
(new Uniform (float scale)))
@@ -41,9 +41,9 @@
factor-type - 'avg' 'in' or 'out'
magnitude - scale of random number range "
([{:keys [rand-type factor-type magnitude :as opts]
- :or {rand-type "uniform"
- factor-type "avg"
- magnitude 3}}]
+ :or {rand-type "uniform"
+ factor-type "avg"
+ magnitude 3}}]
(new Xavier rand-type factor-type (float magnitude)))
([]
(xavier {})))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/io.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/io.clj
index 2f73beb..d6f1499 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/io.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/io.clj
@@ -27,7 +27,6 @@
(:import (org.apache.mxnet IO DataDesc DataBatch NDArray)
(org.apache.mxnet.io ResizeIter PrefetchingIter NDArrayIter
MXDataIter)))
-
(defn batches
"Convert the data-pack to a batch seq"
[data-pack]
@@ -56,19 +55,19 @@
(defn iterator [data-pack]
(.iterator data-pack))
-(defn resize-iter [iter nbatch ])
+(defn resize-iter [iter nbatch])
(defn provide-data [pack-iterator]
- (->> pack-iterator
- (.provideData)
- (util/scala-map->map)
- (mapv (fn [[k v]] {:name k :shape (mx-shape/->vec v)}))))
+ (->> pack-iterator
+ (.provideData)
+ (util/scala-map->map)
+ (mapv (fn [[k v]] {:name k :shape (mx-shape/->vec v)}))))
(defn provide-label [pack-iterator]
- (->> pack-iterator
- (.provideLabel)
- (util/scala-map->map)
- (mapv (fn [[k v]] {:name k :shape (mx-shape/->vec v)}))))
+ (->> pack-iterator
+ (.provideLabel)
+ (util/scala-map->map)
+ (mapv (fn [[k v]] {:name k :shape (mx-shape/->vec v)}))))
(defn reset [iterator]
(.reset iterator))
@@ -89,7 +88,7 @@
(util/scala-vector->vec (.initLabel iterator)))
(defmacro do-batches [iter f]
- "Takes an iterator and a function of one argument. The iterator will be
reset and run thhrough all the batches with the batch passed to the function
argument. nil is returned"
+ "Takes an iterator and a function of one argument. The iterator will be
reset and run thhrough all the batches with the batch passed to the function
argument. nil is returned"
`(do
(reset ~iter)
(loop [it# ~iter]
@@ -126,48 +125,48 @@
`(reduce-batches ~iter ~f 0)))
(defn
- csv-iter
- ([kwargs]
- (util/apply-scala-fn (IO/CSVIter) (util/convert-io-map kwargs))))
+ csv-iter
+ ([kwargs]
+ (util/apply-scala-fn (IO/CSVIter) (util/convert-io-map kwargs))))
(defn
- csv-pack
- ([kwargs]
- (util/apply-scala-fn (IO/CSVPack) (util/convert-io-map kwargs))))
+ csv-pack
+ ([kwargs]
+ (util/apply-scala-fn (IO/CSVPack) (util/convert-io-map kwargs))))
(defn
- image-recode-pack
- ([kwargs]
- (util/apply-scala-fn
- (IO/ImageRecodePack)
- (util/convert-io-map kwargs))))
+ image-recode-pack
+ ([kwargs]
+ (util/apply-scala-fn
+ (IO/ImageRecodePack)
+ (util/convert-io-map kwargs))))
(defn
- image-record-iter
- ([kwargs]
- (util/apply-scala-fn
- (IO/ImageRecordIter)
- (util/convert-io-map kwargs))))
+ image-record-iter
+ ([kwargs]
+ (util/apply-scala-fn
+ (IO/ImageRecordIter)
+ (util/convert-io-map kwargs))))
(defn
- mnist-iter
- ([kwargs]
- (util/apply-scala-fn (IO/MNISTIter) (util/convert-io-map kwargs))))
+ mnist-iter
+ ([kwargs]
+ (util/apply-scala-fn (IO/MNISTIter) (util/convert-io-map kwargs))))
(defn
- mnist-pack
- ([kwargs]
- (util/apply-scala-fn (IO/MNISTPack) (util/convert-io-map kwargs))))
+ mnist-pack
+ ([kwargs]
+ (util/apply-scala-fn (IO/MNISTPack) (util/convert-io-map kwargs))))
(defn
- create-iterator
- ([iter-name kwargs-map]
- (util/coerce-return (IO/createIterator iter-name (util/convert-io-map
kwargs-map)))))
+ create-iterator
+ ([iter-name kwargs-map]
+ (util/coerce-return (IO/createIterator iter-name (util/convert-io-map
kwargs-map)))))
(defn
- create-mx-data-pack
- ([pack-name kwargs-map]
- (util/coerce-return (IO/createMXDataPack pack-name (util/convert-io-map
kwargs-map)))))
+ create-mx-data-pack
+ ([pack-name kwargs-map]
+ (util/coerce-return (IO/createMXDataPack pack-name (util/convert-io-map
kwargs-map)))))
(defn resize-iter
"* Resize a data iterator to given number of batches per epoch.
@@ -233,7 +232,6 @@
(s/def ::dtype #{dtype/UINT8 dtype/INT32 dtype/FLOAT16 dtype/FLOAT32
dtype/FLOAT64})
(s/def ::data-desc (s/keys :req-un [::name ::shape] :opt-un [::dtype
::layout]))
-
;; NCHW is N:batch size C: channel H: height W: width
;;; other layouts are
;; NT, TNC, nad N
@@ -249,7 +247,7 @@
(= 3 sc) "TNC"
(= 4 sc) "NCHW"
:else (apply str (repeat sc "?"))))]
- (new DataDesc name (mx-shape/->shape shape) dtype layout)))
+ (new DataDesc name (mx-shape/->shape shape) dtype layout)))
([name shape]
(data-desc {:name name :shape shape})))
@@ -276,40 +274,40 @@
;; provided-data and provided label is a map of name to shape to indicate
the order of the data/label loading
(util/validate! ::data-batch info "Invalid data batch")
(new DataBatch
- (util/vec->indexed-seq data)
- (util/vec->indexed-seq label)
- (util/vec->indexed-seq index)
- (int pad)
- bucket-key
- (when provided-data (util/list-map provided-data))
- (when provided-label(util/list-map provided-label))))
+ (util/vec->indexed-seq data)
+ (util/vec->indexed-seq label)
+ (util/vec->indexed-seq index)
+ (int pad)
+ bucket-key
+ (when provided-data (util/list-map provided-data))
+ (when provided-label (util/list-map provided-label))))
(defn rand-iter
"A implementation of a random noise iterator
Instead of data pass in the shape vector of the noise shape"
([shape-vec {:keys [label data-batch-size shuffle last-batch-handle
data-name label-name] :as opts
- :or {label nil
- data-batch-size 1
- shuffle false
- last-batch-handle "pad"
- data-name "rand"
- label-name "label"}}]
+ :or {label nil
+ data-batch-size 1
+ shuffle false
+ last-batch-handle "pad"
+ data-name "rand"
+ label-name "label"}}]
(let [data [(ndarray/ones shape-vec)]]
- (proxy [NDArrayIter]
- [(util/vec->indexed-seq data)
- (if label (util/vec->indexed-seq label) (util/empty-indexed-seq))
- (int data-batch-size)
- shuffle
- last-batch-handle
- data-name
- label-name]
- (provideData []
- (util/list-map {data-name (mx-shape/->vec (ndarray/shape (first
data)))}))
- (provideLabel [] (util/empty-list-map))
- (hasNext [] true)
- (getData
- ([] (util/vec->indexed-seq [(random/normal 0 1 (mx-shape/->vec
(ndarray/shape (first data))))])))
- (getLabel
- ([] (util/vec->indexed-seq []))))))
+ (proxy [NDArrayIter]
+ [(util/vec->indexed-seq data)
+ (if label (util/vec->indexed-seq label) (util/empty-indexed-seq))
+ (int data-batch-size)
+ shuffle
+ last-batch-handle
+ data-name
+ label-name]
+ (provideData []
+ (util/list-map {data-name (mx-shape/->vec (ndarray/shape (first
data)))}))
+ (provideLabel [] (util/empty-list-map))
+ (hasNext [] true)
+ (getData
+ ([] (util/vec->indexed-seq [(random/normal 0 1 (mx-shape/->vec
(ndarray/shape (first data))))])))
+ (getLabel
+ ([] (util/vec->indexed-seq []))))))
([shape-vec]
(rand-iter shape-vec {})))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore.clj
index 574bd77..ea7e7f9 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore.clj
@@ -40,7 +40,6 @@
[kvstore]
(.dispose kvstore))
-
(s/def ::ks (s/or :string string?
:vec-of-string (s/coll-of string? :kind vector?)))
(s/def ::ndarray #(instance? NDArray %))
@@ -83,10 +82,10 @@
(util/validate! ::priority priority "Invalid priority")
(let [store-vals (if (vector? vs) vs [vs])
store-keys (if (vector? ks) ks (into [] (repeat (count store-vals)
ks)))]
- (doto kvstore
- (.push (into-array store-keys)
- (into-array store-vals)
- (int priority)))))
+ (doto kvstore
+ (.push (into-array store-keys)
+ (into-array store-vals)
+ (int priority)))))
([kvstore ks vs]
(push kvstore ks vs 0)))
@@ -113,10 +112,10 @@
(util/validate! ::priority priority "Invalid priority")
(let [store-vals (if (vector? outs) outs [outs])
store-keys (if (vector? ks) ks (into [] (repeat (count store-vals)
ks)))]
- (doto kvstore
- (.pull (into-array store-keys)
- (into-array store-vals)
- (int priority)))))
+ (doto kvstore
+ (.pull (into-array store-keys)
+ (into-array store-vals)
+ (int priority)))))
([kvstore ks outs]
(pull kvstore ks outs 0)))
@@ -183,7 +182,6 @@
(doto kvstore
(.sendCommandToServers (int head) body)))
-
(s/def ::fname string?)
(defn save-optimizer-states
diff --git
a/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore_server.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore_server.clj
index 7fa116d..ffce70a 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore_server.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/kvstore_server.clj
@@ -21,14 +21,12 @@
[clojure.spec.alpha :as s])
(:import (org.apache.mxnet KVStoreServer)))
-
(s/def ::env-map (s/map-of string? string?))
(defn init [env-map]
(util/validate! ::env-map env-map "Invalid environment map")
(KVStoreServer/init (util/convert-map env-map)))
-
(s/def ::die-if-others-go-out-timeout int?)
(defn start
diff --git
a/contrib/clojure-package/src/org/apache/clojure_mxnet/lr_scheduler.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/lr_scheduler.clj
index d08c40e..d396540 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/lr_scheduler.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/lr_scheduler.clj
@@ -18,7 +18,6 @@
(ns org.apache.clojure-mxnet.lr-scheduler
(:import (org.apache.mxnet FactorScheduler)))
-
(defn factor-scheduler
"Assume the weight has been updated by n times, then the learning rate will
be base_lr * factor^^(floor(n/step))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/module.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/module.clj
index 42d206a..22ab761 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/module.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/module.clj
@@ -33,7 +33,6 @@
(org.apache.mxnet Initializer Optimizer NDArray DataBatch
Context EvalMetric Monitor Callback$Speedometer
DataDesc)))
-
(defn module
"Module is a basic module that wrap a symbol.
sym : Symbol definition.
@@ -131,7 +130,7 @@
(s/def ::force-init boolean?)
(s/def ::allow-extra boolean?)
(s/def ::init-params-opts (s/keys :opt-un [::initializer ::arg-params
::aux-params
- ::force-init ::allow-extra]))
+ ::force-init ::allow-extra]))
(defn init-params
" Initialize the parameters and auxiliary states.
@@ -190,7 +189,6 @@
([mod]
(init-optimizer mod {})))
-
(defn forward
"Forward computation.
data-batch - input data of form io/data-batch either map or DataBatch
@@ -206,7 +204,6 @@
([mod data-batch-map]
(forward mod data-batch-map nil)))
-
(s/def ::ndarray #(instance? NDArray %))
(s/def ::out-grads (s/nilable (s/coll-of ::ndarray)))
@@ -299,7 +296,6 @@
([mod prefix epoch]
(save-checkpoint mod {:prefix prefix :epoch epoch})))
-
(s/def ::load-optimizer-states boolean?)
(s/def ::data-names (s/coll-of string? :kind vector?))
(s/def ::label-names (s/coll-of string? :kind vector?))
@@ -419,7 +415,6 @@
(doto mod
(.installMonitor monitor)))
-
(defn borrow-optimizer
"Borrow optimizer from a shared module. Used in bucketing, where exactly the
same
optimizer (esp. kvstore) is used.
@@ -446,11 +441,9 @@
(doto mod
(.loadOptimzerStates fname)))
-
(s/def ::eval-metric #(instance? EvalMetric %))
(s/def ::labels (s/coll-of ::ndarray :kind vector?))
-
(defn update-metric
"Evaluate and accumulate evaluation metric on outputs of the last forward
computation.
- mod module
@@ -462,7 +455,6 @@
(doto mod
(.updateMetric eval-metric (util/vec->indexed-seq labels))))
-
(s/def ::begin-epoch int?)
(s/def ::validation-metric ::eval-metric)
(s/def ::monitor #(instance? Monitor %))
@@ -472,7 +464,6 @@
::force-init ::begin-epoch
::validation-metric ::monitor
::batch-end-callback]))
-
;; callbacks are not supported for now
(defn fit-params
"Fit Params"
@@ -490,23 +481,22 @@
begin-epoch 0}}]
(util/validate! ::fit-params-opts opts "Invalid fit param opts")
(doto (new FitParams)
- (.setEvalMetric eval-metric)
- (.setKVStore kvstore)
- (.setOptimizer optimizer)
- (.setInitializer initializer)
- (.setArgParams (some-> arg-params (util/convert-map)))
- (.setAuxParams (some-> aux-params (util/convert-map)))
- (.setAllowMissing allow-missing)
- (.setForceRebind force-rebind)
- (.setForceInit force-init)
- (.setBeginEpoch (int begin-epoch))
- (.setValidationMetric validation-metric)
- (.setMonitor monitor)
- (.setBatchEndCallback batch-end-callback)))
+ (.setEvalMetric eval-metric)
+ (.setKVStore kvstore)
+ (.setOptimizer optimizer)
+ (.setInitializer initializer)
+ (.setArgParams (some-> arg-params (util/convert-map)))
+ (.setAuxParams (some-> aux-params (util/convert-map)))
+ (.setAllowMissing allow-missing)
+ (.setForceRebind force-rebind)
+ (.setForceInit force-init)
+ (.setBeginEpoch (int begin-epoch))
+ (.setValidationMetric validation-metric)
+ (.setMonitor monitor)
+ (.setBatchEndCallback batch-end-callback)))
([]
(new FitParams)))
-
(s/def ::mx-data-iter #(instance? MXDataIter %))
(s/def ::ndarray-iter #(instance? NDArrayIter %))
(s/def ::train-data (s/or :mx-iter ::mx-data-iter :ndarry-iter ::ndarray-iter))
@@ -515,7 +505,6 @@
(s/def ::fit-params #(instance? FitParams %))
(s/def ::fit-options (s/keys :req-un [::train-data] :opt-un [::eval-data
::num-epoch ::fit-params]))
-
;;; High Level API
(defn score
@@ -556,8 +545,8 @@
- num-epoch Number of epochs to run training.
- f-params Extra parameters for training (See fit-params)."
[mod {:keys [train-data eval-data num-epoch fit-params] :as opts
- ` :or {num-epoch 1
- fit-params (new FitParams)}}]
+ `:or {num-epoch 1
+ fit-params (new FitParams)}}]
(util/validate! ::fit-options opts "Invalid options for fit")
(let [fmod (-> mod
(bind {:data-shapes (mx-io/provide-data train-data)
@@ -576,37 +565,37 @@
val-metric (or (util/option->value (.validationMetric fit-params))
(eval-metric/accuracy))]
(doseq [i (range num-epoch)]
(let [tic (System/currentTimeMillis)]
- (mx-io/reduce-batches train-data
- (fn [batch-num batch]
- (-> fmod
- (forward batch)
- (backward)
- (update)
- (update-metric eval-metric (mx-io/batch-label
batch)))
- (when-let [cb (util/option->value
(.batchEndCallback fit-params))]
- (callback/invoke cb i batch-num eval-metric))
- (.dispose batch)
- (inc batch-num)))
- (println "Epoch " i " Train-" (eval-metric/get eval-metric))
- (println "Epoch " i " Time cost-" (- (System/currentTimeMillis) tic))
+ (mx-io/reduce-batches train-data
+ (fn [batch-num batch]
+ (-> fmod
+ (forward batch)
+ (backward)
+ (update)
+ (update-metric eval-metric
(mx-io/batch-label batch)))
+ (when-let [cb (util/option->value
(.batchEndCallback fit-params))]
+ (callback/invoke cb i batch-num eval-metric))
+ (.dispose batch)
+ (inc batch-num)))
+ (println "Epoch " i " Train-" (eval-metric/get eval-metric))
+ (println "Epoch " i " Time cost-" (- (System/currentTimeMillis) tic))
;;sync across kvstores
- (get-params fmod)
- (when-let [cb (util/option->value (.epochEndCallback fit-params))]
- (callback/invoke cb i 0 val-metric))
+ (get-params fmod)
+ (when-let [cb (util/option->value (.epochEndCallback fit-params))]
+ (callback/invoke cb i 0 val-metric))
;; evaluation on the validation set
- (when eval-data
- (let [res (score fmod {:eval-data eval-data :eval-metric eval-metric
:epoch i})]
- (println "Epoch " i " Validation- " res)))))
+ (when eval-data
+ (let [res (score fmod {:eval-data eval-data :eval-metric eval-metric
:epoch i})]
+ (println "Epoch " i " Validation- " res)))))
fmod)
;; old way if the problem with the sizes get resolved in DataDesc
#_(doto mod
- (.fit
- train-data
- (util/->option eval-data)
- (int num-epoch)
- fit-params)))
+ (.fit
+ train-data
+ (util/->option eval-data)
+ (int num-epoch)
+ fit-params)))
(s/def ::eval-data ::train-data)
(s/def ::num-batch integer?)
@@ -621,7 +610,7 @@
(util/validate! ::mx-io/data-batch data-batch "Invalid data batch")
(util/coerce-return (.predict mod (if (map? data-batch)
(mx-io/data-batch data-batch)
- data-batch))))
+ data-batch))))
(defn predict
"Run prediction and collect the outputs.
@@ -639,7 +628,6 @@
(util/validate! ::predict-opts opts "Invalid opts for predict")
(util/scala-vector->vec (.predict mod eval-data (int num-batch) reset)))
-
(s/def ::predict-every-batch-opts (s/keys :req-un [::eval-data] :opt-un
[::num-batch ::reset]))
(defn predict-every-batch
@@ -660,11 +648,8 @@
(util/validate! ::predict-every-batch-opts opts "Invalid opts for
predict-every-batch")
(mapv util/scala-vector->vec (util/scala-vector->vec (.predictEveryBatch mod
eval-data (int num-batch) reset))))
-
-
(s/def ::score-opts (s/keys :req-un [::eval-data ::eval-metric] :opt-un
[::num-batch ::reset ::epoch]))
-
(defn exec-group [mod]
(.execGroup mod))
@@ -676,16 +661,13 @@
(r/reflect DataDesc)
(new DataDesc)
- (.setEpochEndCallback (if epoch-end-callback
- (util/->option epoch-end-callback)
- (util/->option nil)))
- (.setBatchEndCallback (if batch-end-callback
- (util/->option batch-end-callback)
- (util/->option nil)))
-
- (fit-params {:allow-missing true})
- (fit-params {})
-
- )
+ (.setEpochEndCallback (if epoch-end-callback
+ (util/->option epoch-end-callback)
+ (util/->option nil)))
+ (.setBatchEndCallback (if batch-end-callback
+ (util/->option batch-end-callback)
+ (util/->option nil)))
+ (fit-params {:allow-missing true})
+ (fit-params {}))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/monitor.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/monitor.clj
index 0550b4c..cbe0484 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/monitor.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/monitor.clj
@@ -19,7 +19,6 @@
(:require [org.apache.clojure-mxnet.util :as util])
(:import (org.apache.mxnet Monitor)))
-
(defmacro monitor
"Monitor outputs, weights, and gradients for debugging.
- interval Number of batches between printing.
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/ndarray.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/ndarray.clj
index b471055..e37a8bc 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/ndarray.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/ndarray.clj
@@ -26,7 +26,6 @@
[t6.from-scala.core :refer [$] :as $])
(:import (org.apache.mxnet NDArray)))
-
;; loads the generated functions into the namespace
(do (clojure.core/load "gen/ndarray"))
@@ -80,7 +79,6 @@
([source-vec shape-vec]
(array source-vec shape-vec {})))
-
(defn arange
"Returns evenly spaced values within a given interval.
Values are generated within the half-open interval [`start`, `stop`). In
other
@@ -88,14 +86,14 @@
([start stop {:keys [step repeat ctx dtype]
:or {step (float 1) repeat (int 1) ctx
(mx-context/default-context) dtype base/MX_REAL_TYPE}
:as opts}]
- (NDArray/arange (float start) ($/option(float stop)) step repeat ctx dtype))
+ (NDArray/arange (float start) ($/option (float stop)) step repeat ctx
dtype))
([start stop]
(arange start stop {})))
(defn slice
"Return a sliced NDArray that shares memory with current one."
([ndarray i]
- (.slice ndarray (int i)))
+ (.slice ndarray (int i)))
([ndarray start stop]
(.slice ndarray (int start) (int stop))))
@@ -104,7 +102,6 @@
[source-ndarray target-ndarray]
(.copyTo source-ndarray target-ndarray))
-
(defn save
"Save list of NDArray or dict of str->NDArray to binary file
(The name of the file.Can be S3 or HDFS address (remember built with S3
support))
@@ -139,7 +136,7 @@
(.asInContext ndarray ctx))
(defn as-type
- "Return a copied numpy array of current array with specified type."
+ "Return a copied numpy array of current array with specified type."
[ndarray dtype]
(.asType ndarray dtype))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/optimizer.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/optimizer.clj
index 45dcc48..f18ff40 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/optimizer.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/optimizer.clj
@@ -22,10 +22,10 @@
(defn sgd
"A very simple SGD optimizer with momentum and weight regularization."
([{:keys [learning-rate momentum wd clip-gradient lr-scheduler] :as opts
- :or {learning-rate 0.01
- momentum 0.0
- wd 0.0001
- clip-gradient 0}}]
+ :or {learning-rate 0.01
+ momentum 0.0
+ wd 0.0001
+ clip-gradient 0}}]
(new SGD (float learning-rate) (float momentum) (float wd) (float
clip-gradient) lr-scheduler))
([]
(sgd {})))
@@ -35,11 +35,11 @@
Implementation of paper 'Asynchronous Stochastic Gradient Descent with
Delay Compensation for Distributed Deep Learning'"
([{:keys [learning-rate momentum lambda wd clip-gradient lr-scheduler] :as
opts
- :or {learning-rate 0.01
- momentum 0.0
- lambda 0.04
- wd 0.0
- clip-gradient 0}}]
+ :or {learning-rate 0.01
+ momentum 0.0
+ lambda 0.04
+ wd 0.0
+ clip-gradient 0}}]
(new DCASGD (float learning-rate) (float lambda) (float momentum) (float
wd) (float clip-gradient) lr-scheduler))
([]
(dcasgd {})))
@@ -49,10 +49,10 @@
It is implemented according to
https://github.com/torch/optim/blob/master/sgd.lua";
([{:keys [learning-rate momentum wd clip-gradient lr-scheduler] :as opts
- :or {learning-rate 0.01
- momentum 0.0
- wd 0.0001
- clip-gradient 0}}]
+ :or {learning-rate 0.01
+ momentum 0.0
+ wd 0.0001
+ clip-gradient 0}}]
(new NAG (float learning-rate) (float momentum) (float wd) (float
clip-gradient) lr-scheduler))
([]
(nag {})))
@@ -106,7 +106,7 @@
rescale-gradient 1.0
epsilon 1e-7
wd 0.0}}]
- (new AdaGrad (float learning-rate) (float rescale-gradient) (float epsilon)
(float wd) ))
+ (new AdaGrad (float learning-rate) (float rescale-gradient) (float epsilon)
(float wd)))
([]
(ada-grad {})))
@@ -139,7 +139,7 @@
(adam {})))
(defn sgld
- "Stochastic Langevin Dynamics Updater to sample from a distribution.
+ "Stochastic Langevin Dynamics Updater to sample from a distribution.
- learning-rate Step size.
- rescale-gradient rescaling factor of gradient.
@@ -169,7 +169,6 @@
(doto optimizer
(.update (int index) weight grad state)))
-
(defn create-state
"Create additional optimizer state such as momentum."
[optimizer index weight]
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/profiler.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/profiler.clj
index 0bc93cc..48fd041 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/profiler.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/profiler.clj
@@ -26,7 +26,7 @@
-fileName, optional The name of output trace file. Default is profile.json."
[kwargs]
(Profiler/profilerSetConfig
- (util/convert-io-map kwargs) ))
+ (util/convert-io-map kwargs)))
(defn profiler-set-state
"Set up the profiler state to record operator.
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/random.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/random.clj
index 99f09aa..d6e3378 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/random.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/random.clj
@@ -34,7 +34,7 @@
(uniform low high shape-vec {})))
(defn normal
- "Generate normal(Gaussian) distribution N(mean, stdvar^^2) with shape.
+ "Generate normal(Gaussian) distribution N(mean, stdvar^^2) with shape.
loc: The standard deviation of the normal distribution
scale: The upper bound of distribution.
shape-vec: vector shape of the ndarray generated.
@@ -47,7 +47,6 @@
([loc scale shape-vec]
(normal loc scale shape-vec {})))
-
(defn seed
" Seed the random number generators in mxnet.
This seed will affect behavior of functions in this module,
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/shape.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/shape.clj
index 684cb0f..01bedef 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/shape.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/shape.clj
@@ -19,7 +19,6 @@
(:require [t6.from-scala.core :refer [$] :as $])
(:import (org.apache.mxnet Shape)))
-
(defn ->shape [v]
(new Shape (apply $/immutable-list (map int v))))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/symbol.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/symbol.clj
index 2dcd847..42ae034 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/symbol.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/symbol.clj
@@ -28,7 +28,6 @@
[org.apache.clojure-mxnet.ndarray :as ndarray])
(:import (org.apache.mxnet Symbol)))
-
;; loads the generated functions into the namespace
(do (clojure.core/load "gen/symbol"))
@@ -44,14 +43,14 @@
kwarg-map: Additional attributes which must start and end with double
underscores"
([var-name]
(variable var-name {}))
- ([var-name {:keys [attrs shape lr-mult wd-mult dtype kwargs]:as opts}]
- (Symbol/Variable var-name
- (when attrs (util/convert-symbol-map attrs))
- (when shape (mx-shape/->shape shape))
- (if lr-mult (float lr-mult)($/option nil))
- (if wd-mult (float wd-mult)($/option nil))
- dtype
- (if kwargs (util/convert-symbol-map kwargs)
(util/empty-map)))))
+ ([var-name {:keys [attrs shape lr-mult wd-mult dtype kwargs] :as opts}]
+ (Symbol/Variable var-name
+ (when attrs (util/convert-symbol-map attrs))
+ (when shape (mx-shape/->shape shape))
+ (if lr-mult (float lr-mult) ($/option nil))
+ (if wd-mult (float wd-mult) ($/option nil))
+ dtype
+ (if kwargs (util/convert-symbol-map kwargs)
(util/empty-map)))))
(defn bind
"Bind the current symbol to get an executor.
@@ -136,80 +135,80 @@
([start stop {:keys [step repeat dtype]
:or {step (float 1) repeat (int 1) dtype base/MX_REAL_TYPE}
:as opts}]
- (Symbol/arange (float start) ($/option(float stop)) step repeat nil dtype))
+ (Symbol/arange (float start) ($/option (float stop)) step repeat nil dtype))
([start stop]
(arange start stop {})))
;;; manually defined because of a conflicting arity of 2 with the auto-gen
(defn min
- ([sym-name kwargs-map symbol-list kwargs-map-1]
- (util/coerce-return
- (Symbol/min
- (util/nil-or-coerce-param sym-name #{"java.lang.String"})
- (util/nil-or-coerce-param
- kwargs-map
- #{"scala.collection.immutable.Map"})
- (util/nil-or-coerce-param symbol-list #{"scala.collection.Seq"})
- (util/nil-or-coerce-param
- kwargs-map-1
- #{"scala.collection.immutable.Map"}))))
- ([sym-name attr-map kwargs-map]
- (min sym-name attr-map (util/empty-list) kwargs-map))
- ([kwargs-map] (min nil nil (util/empty-list) kwargs-map))
- ([sym1 sym2]
- (util/coerce-return
- (Symbol/min
- (util/nil-or-coerce-param
- sym1
- #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"})
- (util/nil-or-coerce-param
- sym2
- #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"})))))
+ ([sym-name kwargs-map symbol-list kwargs-map-1]
+ (util/coerce-return
+ (Symbol/min
+ (util/nil-or-coerce-param sym-name #{"java.lang.String"})
+ (util/nil-or-coerce-param
+ kwargs-map
+ #{"scala.collection.immutable.Map"})
+ (util/nil-or-coerce-param symbol-list #{"scala.collection.Seq"})
+ (util/nil-or-coerce-param
+ kwargs-map-1
+ #{"scala.collection.immutable.Map"}))))
+ ([sym-name attr-map kwargs-map]
+ (min sym-name attr-map (util/empty-list) kwargs-map))
+ ([kwargs-map] (min nil nil (util/empty-list) kwargs-map))
+ ([sym1 sym2]
+ (util/coerce-return
+ (Symbol/min
+ (util/nil-or-coerce-param
+ sym1
+ #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"})
+ (util/nil-or-coerce-param
+ sym2
+ #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"})))))
;;; manually defined because of a conflicting arity of 2 with the auto-gen
(defn max
- ([sym1 sym2]
- (util/coerce-return
- (Symbol/max
- (util/nil-or-coerce-param
- sym1
- #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"})
- (util/nil-or-coerce-param
- sym2
- #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"}))))
- ([sym-name kwargs-map symbol-list kwargs-map-1]
- (util/coerce-return
- (Symbol/max
- (util/nil-or-coerce-param sym-name #{"java.lang.String"})
- (util/nil-or-coerce-param
- kwargs-map
- #{"scala.collection.immutable.Map"})
- (util/nil-or-coerce-param symbol-list #{"scala.collection.Seq"})
- (util/nil-or-coerce-param
- kwargs-map-1
- #{"scala.collection.immutable.Map"}))))
- ([sym-name attr-map kwargs-map]
- (max sym-name attr-map (util/empty-list) kwargs-map))
+ ([sym1 sym2]
+ (util/coerce-return
+ (Symbol/max
+ (util/nil-or-coerce-param
+ sym1
+ #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"})
+ (util/nil-or-coerce-param
+ sym2
+ #{"ml.dmlc.mxnet.Symbol" "java.lang.Object"}))))
+ ([sym-name kwargs-map symbol-list kwargs-map-1]
+ (util/coerce-return
+ (Symbol/max
+ (util/nil-or-coerce-param sym-name #{"java.lang.String"})
+ (util/nil-or-coerce-param
+ kwargs-map
+ #{"scala.collection.immutable.Map"})
+ (util/nil-or-coerce-param symbol-list #{"scala.collection.Seq"})
+ (util/nil-or-coerce-param
+ kwargs-map-1
+ #{"scala.collection.immutable.Map"}))))
+ ([sym-name attr-map kwargs-map]
+ (max sym-name attr-map (util/empty-list) kwargs-map))
([kwargs-map] (max nil nil (util/empty-list) kwargs-map)))
;;; redefining to make it easier to work with
(defn- coerce-infer-shape-return [ret]
(->> ret
- (map util/scala-vector->vec)
- (map (fn [shapes] (map mx-shape/->vec shapes)))))
+ (map util/scala-vector->vec)
+ (map (fn [shapes] (map mx-shape/->vec shapes)))))
(defn
- infer-shape
- ([sym vec-or-strings vec-of-ints vec-of-ints-1]
- (let [ret (util/coerce-return
- (.inferShape
- sym
- (util/nil-or-coerce-param vec-or-strings #{"java.lang.String<>"})
- (util/nil-or-coerce-param vec-of-ints #{"int<>"})
- (util/nil-or-coerce-param vec-of-ints-1 #{"int<>"})))]
- (coerce-infer-shape-return ret)))
+ infer-shape
+ ([sym vec-or-strings vec-of-ints vec-of-ints-1]
+ (let [ret (util/coerce-return
+ (.inferShape
+ sym
+ (util/nil-or-coerce-param vec-or-strings
#{"java.lang.String<>"})
+ (util/nil-or-coerce-param vec-of-ints #{"int<>"})
+ (util/nil-or-coerce-param vec-of-ints-1 #{"int<>"})))]
+ (coerce-infer-shape-return ret)))
([sym symbol-list-or-kwargs-map]
(let [ret (util/coerce-return
(.inferShape
@@ -235,5 +234,4 @@
(into {})))
param-name (format "%s-%04d.params" prefix epoch)]
(ndarray/save param-name save-map)
- (println "Saved checkpoint to " param-name)))
- )
+ (println "Saved checkpoint to " param-name))))
diff --git a/contrib/clojure-package/src/org/apache/clojure_mxnet/util.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/util.clj
index f42a124..8f2bb3b 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/util.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/util.clj
@@ -75,11 +75,10 @@
(defn convert-tuple [param]
(apply $/tuple param))
-
(def tuple-param-names #{"kernel" "stride" "pad" "target-shape" "shape"})
(defn convert-by-shape [param]
- (into {} (mapv (fn [[k v]]
+ (into {} (mapv (fn [[k v]]
[k (if (vector? v) (mx-shape/->shape v) v)])
param)))
@@ -87,8 +86,8 @@
(into {} (mapv (fn [[k v]]
(if (or (get tuple-param-names k)
(get tuple-param-names (name k)))
- [k (str (if (vector? v) (mx-shape/->shape v)
v))]
- [k v]))
+ [k (str (if (vector? v) (mx-shape/->shape v) v))]
+ [k v]))
param)))
(def io-param-names #{"input-shape" "data-shape" "label-shape"})
@@ -110,7 +109,6 @@
flatten
keyword->snake-case))))
-
(defn convert-symbol-map [param]
(convert-map (tuple-convert-by-param-name param)))
@@ -183,7 +181,7 @@
[f]
`($/fn ~@(drop-last (rest f)) ~(last f)))
-(defn translate-keyword-shape[[k v]]
+(defn translate-keyword-shape [[k v]]
[(if (keyword? k) (string/replace (name k) "-" "_") k)
(if (vector? v) (mx-shape/->shape v) v)])
diff --git
a/contrib/clojure-package/src/org/apache/clojure_mxnet/visualization.clj
b/contrib/clojure-package/src/org/apache/clojure_mxnet/visualization.clj
index c7002bf..37d141b 100644
--- a/contrib/clojure-package/src/org/apache/clojure_mxnet/visualization.clj
+++ b/contrib/clojure-package/src/org/apache/clojure_mxnet/visualization.clj
@@ -20,8 +20,6 @@
[org.apache.clojure-mxnet.shape :as mx-shape])
(:import (org.apache.mxnet Visualization)))
-
-
(defn plot-network
"convert symbol to Dot object for visualization
- symbol symbol to be visualized
@@ -47,7 +45,6 @@
([sym shape-map]
(plot-network sym shape-map {})))
-
(defn render
" Render file with Graphviz engine into format.
- dot the dot file from plot-network function
diff --git a/contrib/clojure-package/test/dev/generator_test.clj
b/contrib/clojure-package/test/dev/generator_test.clj
index ed16863..a3ec338 100644
--- a/contrib/clojure-package/test/dev/generator_test.clj
+++ b/contrib/clojure-package/test/dev/generator_test.clj
@@ -30,7 +30,7 @@
(defn ndarray-reflect-info [name]
(->> gen/ndarray-public-no-default
(filter #(= name (str (:name %))))
- first))
+ first))
(defn symbol-reflect-info [name]
(->> gen/symbol-public-no-default
@@ -50,7 +50,6 @@
(is (= transformed-params (gen/symbol-transform-param-name
(:parameter-types (symbol-reflect-info
"floor")))))))
-
(deftest test-ndarray-transform-param-name
(let [params ["scala.collection.immutable.Map"
"scala.collection.Seq"]
@@ -116,13 +115,13 @@
sym-name
nil
(if
- (clojure.core/map? kwargs-map-or-vec-or-sym)
+ (clojure.core/map? kwargs-map-or-vec-or-sym)
(util/empty-list)
(util/coerce-param
kwargs-map-or-vec-or-sym
#{"scala.collection.Seq"}))
(if
- (clojure.core/map? kwargs-map-or-vec-or-sym)
+ (clojure.core/map? kwargs-map-or-vec-or-sym)
(org.apache.clojure-mxnet.util/convert-symbol-map
kwargs-map-or-vec-or-sym)
nil))))
@@ -132,13 +131,13 @@
nil
nil
(if
- (clojure.core/map? kwargs-map-or-vec-or-sym)
+ (clojure.core/map? kwargs-map-or-vec-or-sym)
(util/empty-list)
(util/coerce-param
kwargs-map-or-vec-or-sym
#{"scala.collection.Seq"}))
(if
- (clojure.core/map? kwargs-map-or-vec-or-sym)
+ (clojure.core/map? kwargs-map-or-vec-or-sym)
(org.apache.clojure-mxnet.util/convert-symbol-map
kwargs-map-or-vec-or-sym)
nil))))
@@ -170,17 +169,17 @@
(deftest test-gen-ndarray-function-arity
(let [op-name (symbol "$div")
op-values {1 [{:name (symbol "$div")
- :return-type "org.apache.mxnet.NDArray,"
- :declaring-class "org.apache.mxnet.NDArray,"
- :parameter-types ["float"],
- :exception-types [],
- :flags #{:public}}
- {:name (symbol "$div")
- :return-type "org.apache.mxnet.NDArray,"
- :declaring-class "org.apache.mxnet.NDArray,"
- :parameter-types ["org.apache.mxnet.NDArray"],
- :exception-types [],
- :flags #{:public}}]}]
+ :return-type "org.apache.mxnet.NDArray,"
+ :declaring-class "org.apache.mxnet.NDArray,"
+ :parameter-types ["float"],
+ :exception-types [],
+ :flags #{:public}}
+ {:name (symbol "$div")
+ :return-type "org.apache.mxnet.NDArray,"
+ :declaring-class "org.apache.mxnet.NDArray,"
+ :parameter-types ["org.apache.mxnet.NDArray"],
+ :exception-types [],
+ :flags #{:public}}]}]
(is (= '(([ndarray num-or-ndarray]
(util/coerce-return
(.$div
@@ -192,19 +191,19 @@
(deftest test-write-to-file
(testing "symbol"
- (let [fname "test/test-symbol.clj"
- _ (gen/write-to-file [(first gen/all-symbol-functions)]
- gen/symbol-gen-ns
- fname)
- good-contents (slurp "test/good-test-symbol.clj")
- contents (slurp fname)]
- (is (= good-contents contents))))
+ (let [fname "test/test-symbol.clj"
+ _ (gen/write-to-file [(first gen/all-symbol-functions)]
+ gen/symbol-gen-ns
+ fname)
+ good-contents (slurp "test/good-test-symbol.clj")
+ contents (slurp fname)]
+ (is (= good-contents contents))))
(testing "ndarray"
- (let [fname "test/test-ndarray.clj"
- _ (gen/write-to-file [(first gen/all-ndarray-functions)]
- gen/ndarray-gen-ns
- fname)
- good-contents (slurp "test/good-test-ndarray.clj")
- contents (slurp fname)]
- (is (= good-contents contents)))))
+ (let [fname "test/test-ndarray.clj"
+ _ (gen/write-to-file [(first gen/all-ndarray-functions)]
+ gen/ndarray-gen-ns
+ fname)
+ good-contents (slurp "test/good-test-ndarray.clj")
+ contents (slurp fname)]
+ (is (= good-contents contents)))))
diff --git
a/contrib/clojure-package/test/org/apache/clojure_mxnet/conv_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/conv_test.clj
index 856a9f5..feda45b 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/conv_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/conv_test.clj
@@ -57,10 +57,7 @@
(sym/convolution "conv1" {:data data :kernel [3 3] :num-filter 32 :stride
[2 2]})
(sym/batch-norm "bn1" {:data data})
(sym/activation "relu1" {:data data :act-type "relu"})
- (sym/pooling "mp1" {:data data :kernel [2 2] :pool-type "max" :stride [2
2]})
-
-
- (sym/convolution "conv2" {:data data :kernel [3 3] :num-filter 32 :stride
[2 2]})
+ (sym/pooling "mp1" {:data data :kernel [2 2] :pool-type "max" :stride [2
2]}) (sym/convolution "conv2" {:data data :kernel [3 3] :num-filter 32 :stride
[2 2]})
(sym/batch-norm "bn2" {:data data})
(sym/activation "relu2" {:data data :act-type "relu"})
(sym/pooling "mp2" {:data data :kernel [2 2] :pool-type "max" :stride [2
2]})
@@ -69,10 +66,8 @@
(sym/fully-connected "fc2" {:data data :num-hidden 10})
(sym/softmax-output "softmax" {:data data})))
-
-
(deftest test-conv []
- (let [mod (m/module (get-symbol) )]
+ (let [mod (m/module (get-symbol))]
;;; note only one function for training
(m/fit mod {:train-data train-data :eval-data test-data :num-epoch
num-epoch
:fit-params (m/fit-params {:optimizer (optimizer/sgd
{:learning-rate 0.1
@@ -90,5 +85,4 @@
(comment
(require '[clojure.reflect :as r])
- (r/reflect train-data)
- )
+ (r/reflect train-data))
diff --git
a/contrib/clojure-package/test/org/apache/clojure_mxnet/executor_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/executor_test.clj
index 6c885ce..b2a87d4 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/executor_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/executor_test.clj
@@ -53,7 +53,6 @@
(is (test-util/approx= 1e-6 (ndarray/->vec lhs-grad) (ndarray/->vec
lhs-grad2)))
(is (test-util/approx= 1e-6 (ndarray/->vec rhs-grad) (ndarray/->vec
rhs-grad2)))))))
-
(deftest test-reshape
(let [x (sym/variable "x")
y (sym/fully-connected {:data x :num-hidden 4})
diff --git a/contrib/clojure-package/test/org/apache/clojure_mxnet/io_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/io_test.clj
index 2ccfc1c..ace39ec 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/io_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/io_test.clj
@@ -59,7 +59,6 @@
(is (= label1 label0))
(is (= data1 data0))))))
-
(deftest test-image-record-iter
(let [_ (when-not (.exists (io/file "data/cifar/train.rec"))
(sh "scripts/get_cifar_data.sh"))
@@ -120,7 +119,6 @@
(is (= #{[100]} (into #{} (map :shape provide-label))))
(mx-io/dispose prefetch-iter))))
-
(deftest test-ndarray-iter
(let [shape0 [1000 2 2]
data [(ndarray/ones shape0) (ndarray/zeros shape0)]
@@ -138,17 +136,17 @@
nbatch0 8]
(is (= nbatch0 (count (mx-io/for-batches data-iter0 (fn [batch] 1)))))
(is (every? true? (mx-io/for-batches data-iter0
- (fn [batch]
- (= batch-data0
- (first (mx-io/batch-data
batch)))))))
+ (fn [batch]
+ (= batch-data0
+ (first (mx-io/batch-data
batch)))))))
(is (every? true? (mx-io/for-batches data-iter0
- (fn [batch]
- (= batch-data1
- (second (mx-io/batch-data
batch)))))))
+ (fn [batch]
+ (= batch-data1
+ (second (mx-io/batch-data
batch)))))))
(is (every? true? (mx-io/for-batches data-iter0
- (fn [batch]
- (= batch-label
- (first (mx-io/batch-label
batch))))))))
+ (fn [batch]
+ (= batch-label
+ (first (mx-io/batch-label
batch))))))))
;; test discard
(let [data-iter1 (mx-io/ndarray-iter data {:label label
diff --git
a/contrib/clojure-package/test/org/apache/clojure_mxnet/module_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/module_test.clj
index 5ec918f..f3d4e75 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/module_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/module_test.clj
@@ -32,7 +32,6 @@
[clojure.reflect :as r]
[clojure.string :as string]))
-
(deftest test-model-dtype
(let [dtype dtype/FLOAT32
dshape [3 8 7]
@@ -44,14 +43,14 @@
(m/bind {:data-shapes [{:name "data" :shape dshape :dtype dtype
:layout "TNC"}]})
(m/init-params)
(m/forward {:data [(ndarray/ones dshape {:dtype dtype})]})
- (m/backward[(ndarray/ones dshape {:dtype dtype})]))
+ (m/backward [(ndarray/ones dshape {:dtype dtype})]))
(let [outputs (-> mod (m/outputs) flatten)]
(is (every? #(= dtype/FLOAT32 (ndarray/dtype %)) outputs)))))
(deftest test-module-input-grads
(let [a (sym/variable "a" {:kwargs {"__layout__" "NC"}})
b (sym/variable "b" {:kwargs {"__layout__" "NC"}})
- c (sym/variable "c" {:kwargs {"__layout__" "NC"}} )
+ c (sym/variable "c" {:kwargs {"__layout__" "NC"}})
c (sym/+ a (sym/+ (sym/* b 2) (sym/* c 3)))
mod (m/module c ["b" "c" "a"] nil [(context/cpu 0) (context/cpu 1)])]
(-> mod
@@ -61,11 +60,11 @@
:inputs-need-grad true})
(m/init-params)
(m/forward {:data [(ndarray/ones [5 5])
- (ndarray/ones [5 5])
- (ndarray/ones [5 5])]
- :label nil
- :index nil
- :pad 0})
+ (ndarray/ones [5 5])
+ (ndarray/ones [5 5])]
+ :label nil
+ :index nil
+ :pad 0})
(m/backward [(ndarray/ones [5 5])]))
(let [[a-grad b-grad c-grad] (m/input-grads-merged mod)]
(is (every? #(= 1.0 %) (ndarray/->vec a-grad)))
@@ -74,17 +73,17 @@
(deftest test-module-layout
(let [s (sym/variable "data")
- s (sym/activation "act "{"__layout__" "TNC"} {:data s :act_type
"relu"})
+ s (sym/activation "act " {"__layout__" "TNC"} {:data s :act_type
"relu"})
dshape [3 8 7]
mod (m/module s ["data"] nil [(context/cpu 0) (context/cpu 1)])]
(-> mod
(m/bind {:data-shapes [{:name "data" :shape dshape :dtype
dtype/FLOAT32 :layout "TNC"}]})
(m/init-params)
(m/forward {:data [(ndarray/ones dshape)]
- :label nil
- :index nil
- :pad 0})
- (m/backward[(ndarray/ones dshape)]))
+ :label nil
+ :index nil
+ :pad 0})
+ (m/backward [(ndarray/ones dshape)]))
(let [outputs-merged (m/outputs-merged mod)
outputs (m/outputs mod)
hd-shape [3 4 7]]
@@ -107,7 +106,7 @@
(-> mod2
(m/bind {:data-shapes [{:name "data" :shape [10 10] :layout "NT"}]})
(m/init-optimizer {:optimizer (optimizer/sgd {:learning-rate 0.1
:momentum 0.9})}))
- (is (= (-> mod m/symbol sym/to-json) (-> mod2 m/symbol sym/to-json) ))
+ (is (= (-> mod m/symbol sym/to-json) (-> mod2 m/symbol sym/to-json)))
(is (= (-> mod m/params first) (-> mod2 m/params first))))))
(deftest test-module-save-load-multi-device
@@ -127,7 +126,7 @@
(-> mod2
(m/bind {:data-shapes [{:name "data" :shape [10 10] :layout "NT"}]})
(m/init-optimizer {:optimizer (optimizer/sgd {:learning-rate 0.1
:momentum 0.9})}))
- (is (= (-> mod m/symbol sym/to-json) (-> mod2 m/symbol sym/to-json) ))
+ (is (= (-> mod m/symbol sym/to-json) (-> mod2 m/symbol sym/to-json)))
(is (= (-> mod m/params first) (-> mod2 m/params first))))))
(deftest test-module-reshape
@@ -158,7 +157,7 @@
(let [data (ndarray/array [0.05 0.1] [1 1 1 2])
label (ndarray/array [0.01 0.99] [1 1 1 2])
train-data (mx-io/ndarray-iter [data] {:label [label] :label-name
"softmax_label"})
- x (as-> (sym/variable "data") v
+ x (as-> (sym/variable "data") v
(sym/fully-connected "fc_0" {:data v :num-hidden 2})
(sym/activation "act_0" {:data v :act-type "sigmoid"})
(sym/fully-connected "fc_1" {:data v :num-hidden 2})
@@ -166,7 +165,7 @@
(sym/linear-regression-output "softmax" {:data v :grad-scale 2}))
mod (m/module x)]
- (m/bind mod {:data-shapes (mx-io/provide-data train-data) :label-shapes
(mx-io/provide-label train-data)} )
+ (m/bind mod {:data-shapes (mx-io/provide-data train-data) :label-shapes
(mx-io/provide-label train-data)})
(let [arg-params-correct {"fc_0_weight" (ndarray/array [0.15 0.2 0.25 0.3]
[2 2])
"fc_0_bias" (ndarray/array [0.35 0.35] [2])
@@ -214,14 +213,13 @@
(let [result (monitor/toc mon)
freq (->> result
(map (fn [v] (as-> (second v) ?
- (clojure.string/split ? #"_")
+ (clojure.string/split ? #"_")
(take 2 ?)
(clojure.string/join "_" ?))))
(frequencies))
expected-freq {"act_0" 2 "act_1" 2 "data" 1 "fc_0" 6 "fc_1" 6}]
(is (= expected-freq (select-keys freq (keys expected-freq)))))))
-
(deftest test-forward-reshape
(let [num-class 10
data1 (sym/variable "data1")
@@ -271,9 +269,9 @@
(-> mod
(m/forward data-batch))
(is (= [(first l-shape) num-class]) (-> (m/outputs-merged mod) first
(ndarray/shape) (mx-shape/->vec)))
- (-> mod
- (m/backward)
- (m/update)))
+ (-> mod
+ (m/backward)
+ (m/update)))
(let [d-shape1 [20 3 64 64]
d-shape2 [20 3 32 32]
@@ -286,43 +284,41 @@
(-> mod
(m/forward data-batch))
(is (= [(first l-shape) num-class]) (-> (m/outputs-merged mod) first
(ndarray/shape) (mx-shape/->vec)))
- (-> mod
- (m/backward)
- (m/update)))
+ (-> mod
+ (m/backward)
+ (m/update)))
;; train with both different batch sizes and data shapes
(let [d-shape1 [20 3 120 120]
d-shape2 [20 3 32 64]
l-shape [20]
data-batch {:data [(ndarray/random-uniform 0 9 (str
(mx-shape/->shape d-shape1)))
- (ndarray/random-uniform 15 25 (str
(mx-shape/->shape d-shape2)))]
- :label [(ndarray/ones l-shape)]
- :index nil
- :pad 0}]
+ (ndarray/random-uniform 15 25 (str
(mx-shape/->shape d-shape2)))]
+ :label [(ndarray/ones l-shape)]
+ :index nil
+ :pad 0}]
(-> mod
(m/forward data-batch))
(is (= [(first l-shape) num-class]) (-> (m/outputs-merged mod) first
(ndarray/shape) (mx-shape/->vec)))
- (-> mod
- (m/backward)
- (m/update)))
+ (-> mod
+ (m/backward)
+ (m/update)))
(let [d-shape1 [5 3 28 40]
d-shape2 [5 3 24 16]
l-shape [5]
data-batch {:data [(ndarray/random-uniform 0 9 (str
(mx-shape/->shape d-shape1)))
- (ndarray/random-uniform 15 25 (str
(mx-shape/->shape d-shape2)))]
- :label [(ndarray/ones l-shape)]
- :index nil
- :pad 0}]
+ (ndarray/random-uniform 15 25 (str
(mx-shape/->shape d-shape2)))]
+ :label [(ndarray/ones l-shape)]
+ :index nil
+ :pad 0}]
(-> mod
(m/forward data-batch))
(is (= [(first l-shape) num-class]) (-> (m/outputs-merged mod) first
(ndarray/shape) (mx-shape/->vec)))
- (-> mod
- (m/backward)
- (m/update)))))
-
+ (-> mod
+ (m/backward)
+ (m/update)))))
(comment
- (m/data-shapes x)
- )
+ (m/data-shapes x))
diff --git
a/contrib/clojure-package/test/org/apache/clojure_mxnet/ndarray_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/ndarray_test.clj
index 25d01ec..79e9441 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/ndarray_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/ndarray_test.clj
@@ -46,13 +46,13 @@
(deftest test-set-scalar-value
(is (= [10.0 10.0] (-> (ndarray/empty [2 1])
- (ndarray/set 10)
- (->vec)))))
+ (ndarray/set 10)
+ (->vec)))))
(deftest test-copy-from-vector
(is (= [1.0 2.0 3.0 4.0] (-> (ndarray/empty [4 1])
- (ndarray/set [1 2 3 4])
- (->vec)))))
+ (ndarray/set [1 2 3 4])
+ (->vec)))))
(deftest test-plus
(let [ndzeros (zeros [2 1])
@@ -103,12 +103,12 @@
(deftest test-clip
(let [nda (-> (ndarray/empty [3 2])
- (ndarray/set [1 2 3 4 5 6]))]
+ (ndarray/set [1 2 3 4 5 6]))]
(is (= [2.0 2.0 3.0 4.0 5.0 5.0] (->vec (ndarray/clip nda 2 5))))))
(deftest test-sqrt
(let [nda (-> (ndarray/empty [4 1])
- (ndarray/set [0 1 4 9]))]
+ (ndarray/set [0 1 4 9]))]
(is (= [0.0 1.0 2.0 3.0] (->vec (ndarray/sqrt nda))))))
(deftest test-rsqrt
@@ -138,7 +138,6 @@
(is (= [1 1] (mx-shape/->vec (shape res))))
(is (= [11.0] (->vec res)))))
-
(deftest test-arrange
(let [start 0
stop 5
@@ -179,7 +178,6 @@
(is (= [2 1] (-> nda shape mx-shape/->vec)))
(is (= [27.0 3125.0] (->vec nda))))))
-
(deftest test-equal
(let [nda1 (ndarray/array [1 2 3 5] [2 2])
nda2 (ndarray/array [1 4 3 6] [2 2])]
@@ -190,7 +188,6 @@
(is (= [2 2] (-> (ndarray/equal nda1 3) shape mx-shape/->vec)))
(is (= [0.0 0.0 1.0 0.0] (->vec (ndarray/equal nda1 3))))))
-
(deftest test-not-equal
(let [nda1 (ndarray/array [1 2 3 5] [2 2])
nda2 (ndarray/array [1 4 3 6] [2 2])]
@@ -211,7 +208,6 @@
(is (= [2 2] (-> (ndarray/> nda1 2) shape mx-shape/->vec)))
(is (= [0.0 0.0 1.0 1.0] (->vec (ndarray/> nda1 2))))))
-
(deftest test-greater-equal
(let [nda1 (ndarray/array [1 2 4 5] [2 2])
nda2 (ndarray/array [1 4 3 6] [2 2])]
@@ -242,7 +238,6 @@
(is (= [2 2] (-> (ndarray/< nda1 2) shape mx-shape/->vec)))
(is (= [1.0 1.0 0.0 0.0] (->vec (ndarray/<= nda1 2))))))
-
(deftest test-choose-element-0index
(let [nda (ndarray/array [1 2 3 4 6 5] [2 3])
indices (ndarray/array [0 1] [2])
@@ -331,7 +326,6 @@
(is (= [2] (-> argmax shape mx-shape/->vec)))
(is (= [1.0 0.0] (->vec argmax)))))
-
(deftest test-concatenate-axis-0
(let [nda1 (ndarray/array [1 2 4 3 3 3] [2 3])
nda2 (ndarray/array [8 7 6] [1 3])
diff --git
a/contrib/clojure-package/test/org/apache/clojure_mxnet/operator_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/operator_test.clj
index 1a822d5..a71a312 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/operator_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/operator_test.clj
@@ -50,9 +50,8 @@
(doseq [grad arr-grad]
(is (= out-grad grad))))))
-
(deftest test-concat
- (let [shape-vecs[[2 2] [3 2]]
+ (let [shape-vecs [[2 2] [3 2]]
x (sym/variable "x")
y (sym/variable "y")
out (sym/concat "conc" nil [x y] {:dim 0})
@@ -80,7 +79,6 @@
np-grads arr-np]
(is (= grads (mapv #(ndarray/+ % 1) np-grads))))))
-
(defn check-regression [model forward-fn backward-fn]
(let [shape-vec [3 1]
arr-data (random/uniform -1 1 shape-vec)
@@ -99,7 +97,6 @@
np-out (ndarray/->vec arr-label))]
(is (approx= 1e-6 npout-back arr-grad)))))
-
(deftest test-regression
(check-regression (sym/logistic-regression-output {:data (sym/variable
"data") :label (sym/variable "label")})
(fn [x] (/ 1.0 (+ 1.0 (Math/exp (* -1.0 x)))))
@@ -151,7 +148,6 @@
(let [val (ndarray/->vec (ndarray/slice out i))]
(is (approx= 1e-6 [1 1 1 2 2 2] val)))))))
-
(defn check-symbolic-forward [test-sym location expected tolerance]
(let [arr-data (mapv #(ndarray/copy %) location)
arr-grad (mapv #(ndarray/empty (mx-shape/->vec (ndarray/shape %)))
location)
@@ -184,7 +180,6 @@
expected
grad-arrays)))))
-
(deftest test-scalar-op
(let [data (sym/variable "data")
shape-vec [3 4]
@@ -216,7 +211,6 @@
[0 0 0 0]
(-> exec (executor/forward) (executor/outputs) (first))))))
-
(deftest test-arange
(let [start 1
stop 100
@@ -384,7 +378,6 @@
(executor/backward exec-test (ndarray/* (ndarray/ones shape-vec) 2))
(is (approx= 1e-6 (ndarray/zeros shape-vec) arr-grad))))
-
(deftest test-round-ceil-floor
(let [data (sym/variable "data")
shape-vec [3 4]
@@ -402,7 +395,6 @@
(ndarray/+ (ndarray/floor data-tmp)))
(-> (executor/forward exec-test) (executor/outputs)
(first))))))
-
(deftest test-rsqrt-cos-sin
(let [data (sym/variable "data")
shape-vec [3 4]
@@ -451,8 +443,8 @@
exec-test (sym/bind test (context/default-context) [arr-data1
arr-data2])
out (-> (executor/forward exec-test) (executor/outputs) (first))]
(is (approx= 1e-6
- (mapv min (ndarray/->vec data-tmp1) (ndarray/->vec
data-tmp2))
- out))))
+ (mapv min (ndarray/->vec data-tmp1) (ndarray/->vec data-tmp2))
+ out))))
(deftest test-transpose
(let [data (sym/variable "data")
@@ -513,41 +505,36 @@
(let [out-grad (ndarray/* (ndarray/ones shape-vec) 2)
npout-grad (ndarray/* out-grad (ndarray/sign data-tmp))]
(executor/backward exec-test out-grad)
- (is (approx= 1e-6 npout-grad arr-grad)))))
-
-
- ;; configure A: input --> conv --> deconv --> output.
+ (is (approx= 1e-6 npout-grad arr-grad)))));; configure A: input --> conv
--> deconv --> output.
;; the convolution and deconvoluiton has similar parameter which ensure
;; the input shape is the same as output, and the same weights between conv
;; and deconv;
;; If the input value of forward() and backwrad() is the same, then
;; the output value of them should also the same;
-(defn check-deconvolution-forward-backward [{:keys[input-shape-vec num-filter
kernel stride pad]}]
+(defn check-deconvolution-forward-backward [{:keys [input-shape-vec num-filter
kernel stride pad]}]
(let [data (sym/variable "data")
- conv (sym/convolution "conv" {:data data :kernel kernel :stride
stride
- :pad pad :num-filter num-filter
:no-bias "true"})
- deconv (sym/deconvolution "deconv" {:data conv :kernel kernel
:stride stride
- :pad pad :num-filter num-filter
:no-bias "true"} )
- arg-names (sym/list-arguments deconv)
- arg-shape-vecs (first (sym/infer-shape deconv {:data
input-shape-vec}))
- input-data (random/uniform -5 5 input-shape-vec)
- out-grad input-data
- conv-weight (random/normal 0 1 [num-filter (second input-shape-vec)
(first kernel) (last kernel)])
- args {:data input-data :conv-weight conv-weight :deconv-weight
conv-weight}
- args-grad (mapv #(ndarray/empty %) arg-shape-vecs)
- exec (sym/bind deconv (context/default-context) args args-grad)
- out (-> (executor/forward exec) (executor/outputs) first)]
- (executor/backward exec out-grad)
- (is (approx= 1e-3 (ndarray/->vec out) (ndarray/->vec (first
args-grad))))))
-
+ conv (sym/convolution "conv" {:data data :kernel kernel :stride stride
+ :pad pad :num-filter num-filter :no-bias
"true"})
+ deconv (sym/deconvolution "deconv" {:data conv :kernel kernel :stride
stride
+ :pad pad :num-filter num-filter
:no-bias "true"})
+ arg-names (sym/list-arguments deconv)
+ arg-shape-vecs (first (sym/infer-shape deconv {:data input-shape-vec}))
+ input-data (random/uniform -5 5 input-shape-vec)
+ out-grad input-data
+ conv-weight (random/normal 0 1 [num-filter (second input-shape-vec)
(first kernel) (last kernel)])
+ args {:data input-data :conv-weight conv-weight :deconv-weight
conv-weight}
+ args-grad (mapv #(ndarray/empty %) arg-shape-vecs)
+ exec (sym/bind deconv (context/default-context) args args-grad)
+ out (-> (executor/forward exec) (executor/outputs) first)]
+ (executor/backward exec out-grad)
+ (is (approx= 1e-3 (ndarray/->vec out) (ndarray/->vec (first args-grad))))))
(deftest test-deconvolution-forward-and-backward
(check-deconvolution-forward-backward {:input-shape-vec [1 1 5 5]
:num-filter 1 :kernel [3 3] :stride [1 1] :pad [1 1]})
(check-deconvolution-forward-backward {:input-shape-vec [32 3 28 28]
:num-filter 3 :kernel [3 3] :stride [1 1] :pad [1 1]})
;; commented out to make the tests fast
- #_(check-deconvolution-forward-backward {:input-shape-vec [10 3 403 403]
:num-filter 3 :kernel [7 7] :stride [5 5] :pad [2 2]})
- )
+ #_(check-deconvolution-forward-backward {:input-shape-vec [10 3 403 403]
:num-filter 3 :kernel [7 7] :stride [5 5] :pad [2 2]}))
;; configure A: input --> conv --> output.
;; configure B: input --> deconv --> output
@@ -558,52 +545,51 @@
(defn check-deconvolution-gradient [{:keys [input-shape-vec num-filter pad]}]
(let [stride [1 1]
- kernel [(inc (* 2 (first pad))) (inc (* 2 (second pad)))]
- data-conv (sym/variable "data_conv")
- conv (sym/convolution "conv" {:data data-conv :kernel kernel :stride
stride
- :pad pad :num-filter num-filter
:no-bias "true"})
- data-deconv (sym/variable "data_deconv")
- deconv (sym/deconvolution "deconv" {:data data-deconv :kernel kernel
:stride stride
- :pad pad :num-filter num-filter
:no-bias true})
- conv-data (random/uniform -5 5 input-shape-vec)
- conv-args {"data_conv" conv-data "conv_weight" (random/normal 0 1
[num-filter (second input-shape-vec) (first kernel) (second kernel)])}
- conv-args-grad [(ndarray/zeros (-> conv-data (ndarray/shape)
(ndarray/->vec)))
- (ndarray/zeros [num-filter (second input-shape-vec)
(first kernel) (second kernel)])]
- exec-conv (sym/bind conv (context/default-context) conv-args
conv-args-grad)
- conv-out-grad (random/normal 0 2 (-> (executor/outputs exec-conv)
(first) (ndarray/shape) (mx-shape/->vec)))]
- (executor/forward exec-conv)
- (executor/backward exec-conv conv-out-grad)
-
- (let [deconv-data conv-out-grad
- deconv-args {"data_deconv" deconv-data "deconv_weight" (get
conv-args "conv_weight")}
- deconv-args-grad [(ndarray/zeros (-> deconv-data (ndarray/shape)
(mx-shape/->vec)))
- (ndarray/zeros [num-filter (second
input-shape-vec) (first kernel) (second kernel)])]
- exec-deconv (sym/bind deconv (context/default-context) deconv-args
deconv-args-grad)
- deconv-out-grad conv-data]
- (executor/forward exec-deconv)
- (executor/backward exec-deconv deconv-out-grad)
-
- (is (approx= 1e-4 (ndarray/->vec (second conv-args-grad))
(ndarray/->vec (second deconv-args-grad)))))))
+ kernel [(inc (* 2 (first pad))) (inc (* 2 (second pad)))]
+ data-conv (sym/variable "data_conv")
+ conv (sym/convolution "conv" {:data data-conv :kernel kernel :stride
stride
+ :pad pad :num-filter num-filter :no-bias
"true"})
+ data-deconv (sym/variable "data_deconv")
+ deconv (sym/deconvolution "deconv" {:data data-deconv :kernel kernel
:stride stride
+ :pad pad :num-filter num-filter
:no-bias true})
+ conv-data (random/uniform -5 5 input-shape-vec)
+ conv-args {"data_conv" conv-data "conv_weight" (random/normal 0 1
[num-filter (second input-shape-vec) (first kernel) (second kernel)])}
+ conv-args-grad [(ndarray/zeros (-> conv-data (ndarray/shape)
(ndarray/->vec)))
+ (ndarray/zeros [num-filter (second input-shape-vec)
(first kernel) (second kernel)])]
+ exec-conv (sym/bind conv (context/default-context) conv-args
conv-args-grad)
+ conv-out-grad (random/normal 0 2 (-> (executor/outputs exec-conv)
(first) (ndarray/shape) (mx-shape/->vec)))]
+ (executor/forward exec-conv)
+ (executor/backward exec-conv conv-out-grad)
+
+ (let [deconv-data conv-out-grad
+ deconv-args {"data_deconv" deconv-data "deconv_weight" (get
conv-args "conv_weight")}
+ deconv-args-grad [(ndarray/zeros (-> deconv-data (ndarray/shape)
(mx-shape/->vec)))
+ (ndarray/zeros [num-filter (second
input-shape-vec) (first kernel) (second kernel)])]
+ exec-deconv (sym/bind deconv (context/default-context) deconv-args
deconv-args-grad)
+ deconv-out-grad conv-data]
+ (executor/forward exec-deconv)
+ (executor/backward exec-deconv deconv-out-grad)
+
+ (is (approx= 1e-4 (ndarray/->vec (second conv-args-grad)) (ndarray/->vec
(second deconv-args-grad)))))))
(deftest test-deconvolution-gradient
(check-deconvolution-gradient {:input-shape-vec [1 3 5 5] :num-filter 3 :pad
[1 1]}))
(defn check-nearest-up-sampling-with-shape [{:keys [shape-vecs scale
root-scale]}]
- (let [arr (zipmap (map #(str "arg_" %) (range 0 (count shape-vecs)))
- (map #(random/uniform -10 10 %) shape-vecs))
- arr-grad (zipmap (map #(str "arg_" %) (range 0 (count shape-vecs)))
- (map #(ndarray/zeros %) shape-vecs))
- up-args (mapv #(sym/variable (str "arg_" %)) (range 0 (count
shape-vecs)))
- up (sym/up-sampling "up-sampling" nil up-args {:sample-type "nearest"
:scale root-scale})
- exec (sym/bind up (context/default-context) arr arr-grad)]
- (executor/forward exec)
- (executor/backward exec (executor/outputs exec))
- (doseq [k (range 0 (count shape-vecs))]
- (let [k-name (str "arg_" k)
- expected (->> (get arr k-name) (ndarray/->vec) (mapv #(* %
(Math/pow root-scale 2) (Math/pow scale (* 2 k)))))
- real (-> (get arr-grad k-name) (ndarray/->vec))]
- (is (approx= 0.1 expected real))))))
-
+ (let [arr (zipmap (map #(str "arg_" %) (range 0 (count shape-vecs)))
+ (map #(random/uniform -10 10 %) shape-vecs))
+ arr-grad (zipmap (map #(str "arg_" %) (range 0 (count shape-vecs)))
+ (map #(ndarray/zeros %) shape-vecs))
+ up-args (mapv #(sym/variable (str "arg_" %)) (range 0 (count
shape-vecs)))
+ up (sym/up-sampling "up-sampling" nil up-args {:sample-type "nearest"
:scale root-scale})
+ exec (sym/bind up (context/default-context) arr arr-grad)]
+ (executor/forward exec)
+ (executor/backward exec (executor/outputs exec))
+ (doseq [k (range 0 (count shape-vecs))]
+ (let [k-name (str "arg_" k)
+ expected (->> (get arr k-name) (ndarray/->vec) (mapv #(* %
(Math/pow root-scale 2) (Math/pow scale (* 2 k)))))
+ real (-> (get arr-grad k-name) (ndarray/->vec))]
+ (is (approx= 0.1 expected real))))))
(deftest test-nearest-upsampling
(doall (for [root-scale (range 1 4)
@@ -611,6 +597,6 @@
num-shape (range 1 4)
base (range 1 4)]
(let [shape-vecs (mapv (fn [i] [1 3 (* base root-scale (int
(Math/pow scale (- (dec num-shape) i))))
- (* base root-scale (int (Math/pow scale
(- (dec num-shape) i))))])
+ (* base root-scale (int (Math/pow
scale (- (dec num-shape) i))))])
(range 0 num-shape))]
(check-nearest-up-sampling-with-shape {:shape-vecs shape-vecs
:scale scale :root-scale root-scale})))))
diff --git
a/contrib/clojure-package/test/org/apache/clojure_mxnet/optimizer_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/optimizer_test.clj
index e90516f..f6461b1 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/optimizer_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/optimizer_test.clj
@@ -33,7 +33,6 @@
(m/init-optimizer {:optimizer (optimizer-fn)})
(m/update))))
-
(deftest test-optimizer-update
(let [opts [["sgd" optimizer/sgd]
["dcasgd" optimizer/dcasgd]
diff --git
a/contrib/clojure-package/test/org/apache/clojure_mxnet/symbol_test.clj
b/contrib/clojure-package/test/org/apache/clojure_mxnet/symbol_test.clj
index 9d37f07..6df2a10 100644
--- a/contrib/clojure-package/test/org/apache/clojure_mxnet/symbol_test.clj
+++ b/contrib/clojure-package/test/org/apache/clojure_mxnet/symbol_test.clj
@@ -21,7 +21,6 @@
[org.apache.clojure-mxnet.util :as util]
[clojure.test :refer :all]))
-
(deftest test-compose
(let [data (sym/variable "data")
net1 (sym/fully-connected "fc1" {:data data :num-hidden 10})
@@ -45,8 +44,8 @@
net1 (sym/fully-connected "fc2" {:data oldfc :num-hidden 100})]
(is (= ["data" "fc1_weight" "fc1_bias" "fc2_weight" "fc2_bias"]
(sym/list-arguments net1)))
(= (sym/list-arguments oldfc) (-> (sym/get-internals net1)
- (sym/get "fc1_output")
- (sym/list-arguments)))))
+ (sym/get "fc1_output")
+ (sym/list-arguments)))))
(deftest test-infer-type
(let [data (sym/variable "data")
