[Clojure] Add fastText example (#15340)

* Add fastText to CNN text classification examples

* Update repl running instructions

* Complete solution with OOM workaround

* Complete solution with smaller fastText dataset

* Add approx validation accuracy to readme

* Add threading macro

* Use consistent fasttext casing

* Add bangs to io reader functions

* Reference default context setting in readme

* Change fasttext references in readme

* Add data fetching shellscript for fasttext

contrib/clojure-package/examples/cnn-text-classification/README.md

@@ -29,8 +29,7 @@ You also must download the glove word embeddings. The suggested one to use is th
 ## Usage
 
 You can run through the repl with
-`(train-convnet {:embedding-size 50 :batch-size 100 :test-size 100 :num-epoch 10 :max-examples 1000 :pretrained-embedding :glove})`
-
+`(train-convnet {:devs [(context/default-context)] :embedding-size 50 :batch-size 100 :test-size 100 :num-epoch 10 :max-examples 1000 :pretrained-embedding :glove})`
 or
 `JVM_OPTS="-Xmx1g" lein run` (cpu)
 
@@ -49,6 +48,21 @@ and then run
 - `lein uberjar`
 - `java -Xms1024m -Xmx2048m -jar target/cnn-text-classification-0.1.0-SNAPSHOT-standalone.jar`
 
+## Usage with fastText
+
+Using fastText instead of glove is fairly straightforward, as the pretrained embedding format is very similar.
+
+Download the 'Simple English' pretrained wiki word vectors (text) from the fastText
+[site](https://fasttext.cc/docs/en/pretrained-vectors.html) and place them in the
+`data/fasttext` directory. Alternatively just run `./get_fasttext_data.sh`.
+
+Then you can run training on a subset of examples through the repl using:
+```
+(train-convnet {:devs [(context/default-context)] :embedding-size 300 :batch-size 100 :test-size 100 :num-epoch 10 :max-examples 1000 :pretrained-embedding :fasttext})
+```
+
+Expect a validation accuracy of `~0.67` with the above parameters.
+
 ## Usage with word2vec
 
 You can also use word2vec embeddings in order to train the text classification model.
@@ -58,15 +72,15 @@ you'll need to unzip them and place them in the `contrib/clojure-package/data` d
 
 Then you can run training on a subset of examples through the repl using:
 ```
-(train-convnet {:embedding-size 300 :batch-size 100 :test-size 100 :num-epoch 10 :max-examples 1000 :pretrained-embedding :word2vec})
+(train-convnet {:devs [(context/default-context)] :embedding-size 300 :batch-size 100 :test-size 100 :num-epoch 10 :max-examples 1000 :pretrained-embedding :word2vec})
 ```
 Note that loading word2vec embeddings consumes memory and takes some time.
 
 You can also train them using `JVM_OPTS="-Xmx8g" lein run` once you've modified
 the parameters to `train-convnet` (see above) in `src/cnn_text_classification/classifier.clj`.
 In order to run training with word2vec on the complete data set, you will need to run:
 ```
-(train-convnet {:embedding-size 300 :batch-size 100 :test-size 1000 :num-epoch 10 :pretrained-embedding :word2vec})
+(train-convnet {:devs [(context/default-context)] :embedding-size 300 :batch-size 100 :test-size 1000 :num-epoch 10 :pretrained-embedding :word2vec})
 ```
 You should be able to achieve an accuracy of `~0.78` using the parameters above.
 

contrib/clojure-package/examples/cnn-text-classification/get_fasttext_data.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+set -evx
+
+mkdir -p data/fasttext
+cd data/fasttext
+wget https://dl.fbaipublicfiles.com/fasttext/vectors-wiki/wiki.simple.vec

contrib/clojure-package/examples/cnn-text-classification/src/cnn_text_classification/data_helper.clj

@@ -33,6 +33,8 @@
   [embedding-size]
   (format "data/glove/glove.6B.%dd.txt" embedding-size))
 
+(def fasttext-file-path "data/fasttext/wiki.simple.vec")
+
 (defn r-string
   "Reads a string from the given DataInputStream `dis` until a space or newline is reached."
   [dis]
@@ -62,7 +64,7 @@
           vect (mapv (fn [_] (read-float dis)) (range embedding-size))]
       (cons [word vect] (lazy-seq (load-w2v-vectors dis embedding-size (dec num-vectors)))))))
 
-(defn load-word2vec-model
+(defn load-word2vec-model!
   "Loads the word2vec model stored in a binary format from the given `path`.
   By default only the first 100 embeddings are loaded."
   ([path embedding-size opts]
@@ -75,8 +77,8 @@
            _  (println "Processing with " {:dim dim :word-size word-size} " loading max vectors " max-vectors)
            _ (if (not= embedding-size dim)
                (throw (ex-info "Mismatch in embedding size"
-                      {:input-embedding-size embedding-size
-                       :word2vec-embedding-size dim})))
+                       {:input-embedding-size embedding-size
+                        :word2vec-embedding-size dim})))
            vectors (load-w2v-vectors dis dim max-vectors)
            word2vec (if vocab
                       (->> vectors
@@ -88,17 +90,30 @@
        (println "Finished")
        {:num-embed dim :word2vec word2vec})))
   ([path embedding-size]
-   (load-word2vec-model path embedding-size {:max-vectors 100})))
+   (load-word2vec-model! path embedding-size {:max-vectors 100})))
 
-(defn read-text-embedding-pairs [rdr]
-  (for [^String line (line-seq rdr)
+(defn read-text-embedding-pairs [pairs]
+  (for [^String line pairs
         :let [fields (.split line " ")]]
     [(aget fields 0)
      (mapv #(Float/parseFloat ^String %) (rest fields))]))
 
-(defn load-glove [glove-file-path]
+(defn load-glove! [glove-file-path]
   (println "Loading the glove pre-trained word embeddings from " glove-file-path)
-  (into {} (read-text-embedding-pairs (io/reader glove-file-path))))
+  (->> (io/reader glove-file-path)
+       line-seq
+       read-text-embedding-pairs
+       (into {})))
+
+(def remove-fasttext-metadata rest)
+
+(defn load-fasttext! [fasttext-file-path]
+  (println "Loading the fastText pre-trained word embeddings from " fasttext-file-path)
+  (->> (io/reader fasttext-file-path)
+       line-seq
+       remove-fasttext-metadata
+       read-text-embedding-pairs
+       (into {})))
 
 (defn clean-str [s]
   (-> s
@@ -188,9 +203,11 @@
         sentences-padded  (pad-sentences sentences)
         vocab (build-vocab sentences-padded)
         vocab-embeddings (case pretrained-embedding
-                           :glove (->> (load-glove (glove-file-path embedding-size))
+                           :glove (->> (load-glove! (glove-file-path embedding-size))
                                        (build-vocab-embeddings vocab embedding-size))
-                           :word2vec (->> (load-word2vec-model w2v-file-path embedding-size {:vocab vocab})
+                           :fasttext (->> (load-fasttext! fasttext-file-path)
+                                          (build-vocab-embeddings vocab embedding-size))
+                           :word2vec (->> (load-word2vec-model! w2v-file-path embedding-size {:vocab vocab})
                                           (:word2vec)
                                           (build-vocab-embeddings vocab embedding-size))
                            vocab)