This is an automated email from the ASF dual-hosted git repository.
cmeier pushed a commit to branch clojure-bert-sentence-pair-classification
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
commit 7295d8c3cc3ed72ff23afc4372719382fb16c0dc
Author: gigasquid <cme...@gigasquidsoftware.com>
AuthorDate: Fri Apr 19 17:43:41 2019 -0400
base working (although slow)
---
.../src/bert_qa/bert_sentence_classification.clj | 69 ++++++++++------------
1 file changed, 30 insertions(+), 39 deletions(-)
diff --git
a/contrib/clojure-package/examples/bert-qa/src/bert_qa/bert_sentence_classification.clj
b/contrib/clojure-package/examples/bert-qa/src/bert_qa/bert_sentence_classification.clj
index 053dade..7f6723e 100644
---
a/contrib/clojure-package/examples/bert-qa/src/bert_qa/bert_sentence_classification.clj
+++
b/contrib/clojure-package/examples/bert-qa/src/bert_qa/bert_sentence_classification.clj
@@ -11,6 +11,7 @@
[org.apache.clojure-mxnet.symbol :as sym]
[org.apache.clojure-mxnet.module :as m]
[org.apache.clojure-mxnet.infer :as infer]
+ [org.apache.clojure-mxnet.eval-metric :as eval-metric]
[org.apache.clojure-mxnet.optimizer :as optimizer]
[clojure.pprint :as pprint]
[clojure-csv.core :as csv]
@@ -115,15 +116,7 @@
:dtype dtype/FLOAT32
:layout layout/NT}])
- ;; now create the module
- (def mod (-> (m/module model-sym {:contexts devs
- :data-names ["data0" "data1" "data2"]})
- (m/bind {:data-shapes input-descs :label-shapes label-descs})
- (m/init-params {:arg-params arg-params :aux-params aux-params
- :allow-missing true})
- (m/init-optimizer {:optimizer (optimizer/sgd {:learning-rate
0.01 :momentum 0.9})})))
-
- (def base-mod (-> bert-base
+ #_(def base-mod (-> bert-base
(m/bind {:data-shapes input-descs})
(m/init-params {:arg-params arg-params :aux-params
aux-params
:allow-missing true})))
@@ -152,8 +145,9 @@
(vals (select-keys (first raw-file) [3 4 0]))
;=> ("#1 String" "#2 String" "Quality")
(def data-train-raw (->> raw-file
- (map #(vals (select-keys % [3 4 0])))
+ (mapv #(vals (select-keys % [3 4 0])))
(rest) ;;drop header
+ (into [])
))
(def sample (first data-train-raw))
(nth sample 0) ;;;sentence a
@@ -174,34 +168,31 @@
;;; our sample item
(def sample-data (pre-processing (context/default-context) idx->token
token->idx sample))
-
-
- ;; with a predictor
- (defn make-predictor [ctx]
- (let [input-descs [{:name "data0"
- :shape [1 seq-length]
- :dtype dtype/FLOAT32
- :layout layout/NT}
- {:name "data1"
- :shape [1 seq-length]
- :dtype dtype/FLOAT32
- :layout layout/NT}
- {:name "data2"
- :shape [1]
- :dtype dtype/FLOAT32
- :layout layout/N}]
- factory (infer/model-factory model-path-prefix input-descs)]
- (infer/create-predictor
- factory
- {:contexts [ctx]
- :epoch 0})))
-
- (def predictor (make-predictor (context/default-context)))
- (def sample-result (first (infer/predict-with-ndarray predictor
(:input-batch sample-data))))
-
-
-
-
-
+ (def train-count (count data-train-raw)) ;=> 389
+
+ ;; now create the module
+ (def model (-> (m/module model-sym {:contexts devs
+ :data-names ["data0" "data1" "data2"]})
+ (m/bind {:data-shapes input-descs :label-shapes label-descs})
+ (m/init-params {:arg-params arg-params :aux-params aux-params
+ :allow-missing true})
+ (m/init-optimizer {:optimizer (optimizer/sgd {:learning-rate
0.01 :momentum 0.9})})))
+
+ (def metric (eval-metric/accuracy))
+ (def num-epoch 3)
+ (def processed-datas (mapv #(pre-processing (context/default-context)
idx->token token->idx %)
+ data-train-raw))
+
+ (doseq [epoch-num (range num-epoch)]
+ (doall (map-indexed (fn [i batch-data]
+ (-> model
+ (m/forward {:data (:input-batch batch-data)})
+ (m/update-metric metric [(:label batch-data)])
+ (m/backward)
+ (m/update))
+ (when (mod i 10)
+ (println "Working on " i " of " train-count " acc:
" (eval-metric/get metric))))
+ processed-datas))
+ (println "result for epoch " epoch-num " is " (eval-metric/get-and-reset
metric)))
)
