Merge master into coverity_scan to invoke scan-build

# Conflicts:
#	.travis.yml

.travis.yml

@@ -61,6 +61,8 @@ branches:
     - master
     - coverity_scan
     - feat/tensor_integration
+    - feat/decouple_activations
+
 env:
   global:
     - USE_TBB=ON

.travis/clang-format.sh

@@ -30,4 +30,4 @@ else
     echo -e "$RED Failed matching files with clang-format.$COLOR_OFF" >&2
 fi
 
-exit $RE
+exit $RE

CMakeLists.txt

@@ -206,6 +206,8 @@ set(CMAKE_CXX_STANDARD 11)
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
 message(STATUS "C++11 support has been enabled by default.")
 
+include(cotire)
+
 # Unix
 if(CMAKE_COMPILER_IS_GNUCXX OR MINGW OR
    CMAKE_CXX_COMPILER_ID MATCHES "Clang")

Dockerfile

@@ -1,4 +1,4 @@
-FROM ubuntu:16.04
+FROM ubuntu:17.04
 
 MAINTAINER Edgar Riba <edgar.riba@gmail.com>
 
@@ -20,20 +20,22 @@ RUN apt-get install -y    \
     libpthread-stubs0-dev \
     libtbb-dev
 
+# Upgrade pip
+RUN pip install --upgrade pip
+
 # Download and configure PeachPy
-RUN cd /software && \
-    git clone https://github.com/Maratyszcza/PeachPy.git && \
-    cd /software/PeachPy && \
-    pip install -r requirements.txt && \
-    python setup.py generate && \
-    pip install .
+RUN pip install --upgrade git+https://github.com/Maratyszcza/PeachPy
+
+# Download and configure confu
+RUN pip install --upgrade git+https://github.com/Maratyszcza/confu
 
 # Download and configure NNPACK
 RUN apt-get install ninja-build && \
     pip install ninja-syntax && \
     cd /software && \
     git clone --recursive https://github.com/Maratyszcza/NNPACK.git && \
     cd /software/NNPACK && \
+    confu setup && \
     python ./configure.py && \
     ninja
 

README.md

@@ -98,7 +98,7 @@ Please see [wiki page](https://github.com/tiny-dnn/tiny-dnn/wiki/Comparison-with
 Nothing. All you need is a C++11 compiler.
 
 ## Build
-tiny-dnn is header-ony, so *there's nothing to build*. If you want to execute sample program or unit tests, you need to install [cmake](https://cmake.org/) and type the following commands:
+tiny-dnn is header-only, so *there's nothing to build*. If you want to execute sample program or unit tests, you need to install [cmake](https://cmake.org/) and type the following commands:
 
 ```
 cmake .
@@ -151,10 +151,10 @@ void construct_cnn() {
     network<sequential> net;
 
     // add layers
-    net << conv<tan_h>(32, 32, 5, 1, 6)  // in:32x32x1, 5x5conv, 6fmaps
-        << ave_pool<tan_h>(28, 28, 6, 2) // in:28x28x6, 2x2pooling
-        << fc<tan_h>(14 * 14 * 6, 120)   // in:14x14x6, out:120
-        << fc<identity>(120, 10);        // in:120,     out:10
+    net << conv(32, 32, 5, 1, 6) << tanh()  // in:32x32x1, 5x5conv, 6fmaps
+        << ave_pool(28, 28, 6, 2) << tanh() // in:28x28x6, 2x2pooling
+        << fc(14 * 14 * 6, 120) << tanh()   // in:14x14x6, out:120
+        << fc(120, 10);                     // in:120,     out:10
 
     assert(net.in_data_size() == 32 * 32);
     assert(net.out_data_size() == 10);
@@ -170,7 +170,7 @@ void construct_cnn() {
     adagrad optimizer;
 
     // train (50-epoch, 30-minibatch)
-    net.train<mse>(optimizer, train_images, train_labels, 30, 50);
+    net.train<mse, adagrad>(optimizer, train_images, train_labels, 30, 50);
 
     // save
     net.save("net");
@@ -191,8 +191,7 @@ using namespace tiny_dnn::layers;
 void construct_mlp() {
     network<sequential> net;
 
-    net << fc<sigmoid>(32 * 32, 300)
-        << fc<identity>(300, 10);
+    net << fc(32 * 32, 300) << sigmoid() << fc(300, 10);
 
     assert(net.in_data_size() == 32 * 32);
     assert(net.out_data_size() == 10);
@@ -207,7 +206,7 @@ using namespace tiny_dnn;
 using namespace tiny_dnn::activation;
 
 void construct_mlp() {
-    auto mynet = make_mlp<tan_h>({ 32 * 32, 300, 10 });
+    auto mynet = make_mlp<tanh>({ 32 * 32, 300, 10 });
 
     assert(mynet.in_data_size() == 32 * 32);
     assert(mynet.out_data_size() == 10);