Upgrade ngraph to v0.24.0 (#176)

Author: kanvi-nervana

CMakeLists.txt

@@ -234,7 +234,7 @@ if (NOT USE_PRE_BUILT_NGRAPH)
     ExternalProject_Add(
         ext_ngraph
         GIT_REPOSITORY https://github.com/NervanaSystems/ngraph
-        GIT_TAG v0.24.0-rc.3
+        GIT_TAG v0.24.0
         CMAKE_ARGS 
             -DNGRAPH_DISTRIBUTED_ENABLE=${NGRAPH_DISTRIBUTED_ENABLE}
             -DNGRAPH_INSTALL_PREFIX=${NGRAPH_ARTIFACTS_DIR}

README.md

@@ -61,7 +61,7 @@ environment.
 
 The requirements for building nGraph bridge are identical to the requirements for building TensorFlow from source. For more information, review the [TensorFlow configuration] details. 
 
-##### Prepare you build environment
+##### Prepare your build environment
 
 Install the following requirements before building
  `nGraph-bridge`. 
@@ -88,7 +88,7 @@ Once TensorFlow's dependencies are installed, clone the `ngraph-bridge` repo:
 
         git clone https://github.com/tensorflow/ngraph-bridge.git
         cd ngraph-bridge
-        git checkout v0.16.0-rc5
+        git checkout v0.16.0
 
 Run the following Python script to build TensorFlow, nGraph, and the bridge. Use Python 3.5:
 
@@ -115,7 +115,7 @@ To use the `ngraph-tensorflow-bridge`, activate the following `virtualenv` to st
 
         source build_cmake/venv-tf-py3/bin/activate
 
-Alternatively, you can also install the TensorFlow and nGraph bridge outside of a `virtualenv`. The Python `whl` files are located in the `build_cmake/artifacts/` and `build_cmake/artifats/tensorflow` directories, respectively. 
+Alternatively, you can also install the TensorFlow and nGraph bridge outside of a `virtualenv`. The Python `whl` files are located in the `build_cmake/artifacts/` and `build_cmake/artifacts/tensorflow` directories, respectively.
 
 Select the help option of `build_ngtf.py` script to learn more about various build options and how to build other backends. 
 
@@ -219,7 +219,7 @@ results = sess.run(output_operation.outputs[0], {
 elapsed = time.time() - start
 print('Time elapsed: %f seconds' % elapsed)
 ```
-Observe that the ouput time runs faster than TensorFlow native (i.e., without nGraph).
+Observe that the output time runs faster than TensorFlow native (i.e., without nGraph).
 
 #### Add additional backends
 

bazel/WORKSPACE

@@ -25,11 +25,11 @@ tf_configure(
 http_archive(
     name = "ngraph",
     build_file = "//:bazel/ngraph.BUILD",
-    sha256 = "1667a98fac76f2677d7f46ee5352a3e0b0573522f76787056470d8a44cb37a77",
-    strip_prefix = "ngraph-0.24.0-rc.3",
+    sha256 = "19788f421416a74659d7b38ef9d777baf4d935881b11cb1598629bc0ea16d99b",
+    strip_prefix = "ngraph-0.24.0",
     urls = [
-        "https://mirror.bazel.build/github.com/NervanaSystems/ngraph/archive/v0.24.0-rc.3.tar.gz",
-        "https://github.com/NervanaSystems/ngraph/archive/v0.24.0-rc.3.tar.gz"
+        "https://mirror.bazel.build/github.com/NervanaSystems/ngraph/archive/v0.24.0.tar.gz",
+        "https://github.com/NervanaSystems/ngraph/archive/v0.24.0.tar.gz"
     ],
 )
 

build_ngtf.py

@@ -53,7 +53,7 @@ def main():
     '''
 
     # Component versions
-    ngraph_version = "v0.24.0-rc.3"
+    ngraph_version = "v0.24.0"
     tf_version = "v1.14.0"
 
     # Command line parser options

python/setup.in.py

@@ -59,7 +59,7 @@ def get_tag(self):
 
 setup( 
     name='ngraph_tensorflow_bridge',
-    version='0.16.0rc6',
+    version='0.16.0',
     description='Intel nGraph compiler and runtime for TensorFlow',
     long_description=long_description,
     long_description_content_type="text/markdown",

src/version.cc

@@ -30,7 +30,7 @@
 // candidate such as v0.7.0-rc0
 // The code in master will always have the last released version number
 // with a suffix of '-master'
-#define NG_TF_VERSION_SUFFIX "-rc6"
+#define NG_TF_VERSION_SUFFIX ""
 
 #define VERSION_STR_HELPER(x) #x
 #define VERSION_STR(x) VERSION_STR_HELPER(x)