Merge pull request #47 from dirvine/master

style/travis: Allow travis to build on container based system

.travis.yml

@@ -1,3 +1,4 @@
+sudo: false
 language: rust
 rust:
 - nightly
@@ -23,20 +24,22 @@ script:
   travis-cargo build &&
   travis-cargo test  &&
   travis-cargo bench &&
-  travis-cargo doc
+  travis-cargo --only stable doc
 addons:
   apt:
     packages:
     - libcurl4-openssl-dev
     - libelf-dev
     - libdw-dev
     - libblas-dev
-install:
-  - sudo apt-get update
-  - sudo apt-get install fglrx opencl-headers
+    - fglrx
+    - opencl-headers
+    - binutils-dev
+    - nvidia-opencl-dev
+
 after_success:
 - travis-cargo doc-upload
-- travis-cargo coveralls --no-sudo
+- travis-cargo coveralls --no-sudo --verify
 notifications:
   email:
     on_success: never

Cargo.toml

@@ -16,10 +16,8 @@ license = "MIT"
 [dependencies]
 phloem = "~0.3.0"
 collenchyma = "= 0.0.3"
-
-log = "0.3.2"
-
-clippy = { version = "0.0.23", optional = true }
+log = "~0.3.2"
+clippy = { version = "0.0.41", optional = true }
 
 [features]
 default = []

src/lib.rs

@@ -18,7 +18,7 @@
 //! The Network defines the entire model, by defining the hirarchical structure of layers from
 //! bottom to top. At execution time, the Network passes the data, flowing through the Network,
 //! from one layer to the next. The output of one layer is the input for the layer on top. On a
-//! backward pass, the Network passes the deriviates inverted through the Network.
+//! backward pass, the Network passes the derivatives inverted through the Network.
 //!
 //! Layers, the building block of a Leaf Network, are small units, describing computation over
 //! numerical input data. Generally speaking Layers take input and produce an output, but
@@ -37,8 +37,8 @@
 //! memory management and synchronization.
 //!
 //! The learning and optimization of the Network happens at the [Solver][solver] and is decoupled
-//! from the Network making the setup clean and flexibel. One of the four layer types is a Loss
-//! Layer, which is used for the interaction of Network and Solver. The Network procudes the loss
+//! from the Network making the setup clean and flexible. One of the four layer types is a Loss
+//! Layer, which is used for the interaction of Network and Solver. The Network produces the loss
 //! and gradients, which the Solver uses to optimize the Network through parameter updates. Beside
 //! that, the Solver provides housekeeping and other evaluations of the Network. All operation
 //! on the Solver happen through Collenchyma, therefore can be executed on Cuda, OpenCL or native
@@ -116,6 +116,12 @@
         unsafe_code,
         unused_import_braces, unused_qualifications)]
 
+// used when run with  cargo test --no-run --features clippy
+// or cargo build --features clippy
+#![cfg_attr(feature="clippy", feature(plugin))]
+#![cfg_attr(feature="clippy", plugin(clippy))]
+#![cfg_attr(feature="clippy", deny(clippy, clippy_pedantic))]
+
 #[macro_use]
 extern crate log;
 extern crate phloem;