merge master

examples/trials/ga_squad/README.md

@@ -0,0 +1,52 @@
+# Automatic Model Architecture Search for Reading Comprehension
+This example shows us how to use Genetic Algorithm to find good model architectures for Reading Comprehension task.
+
+## Search Space
+Since attention and recurrent neural network (RNN) module have been proven effective in Reading Comprehension.
+We conclude the search space as follow:
+
+1. IDENTITY (Effectively means keep training).
+2. INSERT-RNN-LAYER (Inserts a LSTM. Comparing the performance of GRU and LSTM in our experiment, we decided to use LSTM here.)
+3. REMOVE-RNN-LAYER
+4. INSERT-ATTENTION-LAYER(Inserts a attention layer.)
+5. REMOVE-ATTENTION-LAYER
+6. ADD-SKIP (Identity between random layers).
+7. REMOVE-SKIP (Removes random skip).
+
+![ga-squad-logo](./ga_squad.png)
+
+## New version
+Also we have another version which time cost is less and performance is better. We will release soon.
+
+# How to run this example?
+
+## Use downloading script to download data
+
+Execute the following command to download needed files
+using the downloading script:
+
+```
+chmod +x ./download.sh
+./download.sh
+```
+
+## Download manually
+
+1. download "dev-v1.1.json" and "train-v1.1.json" in https://rajpurkar.github.io/SQuAD-explorer/
+
+```
+wget https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json
+wget https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v1.1.json
+```
+
+2. download "glove.840B.300d.txt" in https://nlp.stanford.edu/projects/glove/
+
+```
+wget http://nlp.stanford.edu/data/glove.840B.300d.zip
+unzip glove.840B.300d.zip
+```
+
+# submit this job
+```
+nnictl create --config ~/nni/examples/trials/ga_squad/config.yaml
+```

src/nni_manager/common/log.ts

@@ -40,7 +40,7 @@ class BufferSerialEmitter {
     private writable: Writable;
 
     constructor(writable: Writable) {
-        this.buffer = new Buffer(0);
+        this.buffer = Buffer.alloc(0);
         this.emitting = false;
         this.writable = writable;
     }
@@ -61,7 +61,7 @@ class BufferSerialEmitter {
                 this.emit();
             }
         });
-        this.buffer = new Buffer(0);
+        this.buffer = Buffer.alloc(0);
     }
 }