Merge remote-tracking branch 'origin/master' into r0.10

Author: Adam Procter

CMakeLists.txt

@@ -105,6 +105,7 @@ option(NGRAPH_ONNX_IMPORT_ENABLE "Enable ONNX importer" FALSE)
 option(NGRAPH_DEX_ONLY "Build CPU DEX without codegen" FALSE)
 option(NGRAPH_CODE_COVERAGE_ENABLE "Enable code coverage data collection" FALSE)
 option(NGRAPH_LIB_VERSIONING_ENABLE "Enable shared library versioning" FALSE)
+option(NGRAPH_PYTHON_BUILD_ENABLE   "Enable build nGraph python package wheel" FALSE)
 
 message(STATUS "NGRAPH_UNIT_TEST_ENABLE:      ${NGRAPH_UNIT_TEST_ENABLE}")
 message(STATUS "NGRAPH_TOOLS_ENABLE:          ${NGRAPH_TOOLS_ENABLE}")

python/ngraph/ops.py

@@ -924,9 +924,9 @@ def batch_norm(eps,             # type: float
     # type: (...) -> Node
     """Return batch normalization node."""
     if mean is None and variance is None:
-        return BatchNormTraining(eps, gamma, beta, data)
+        return BatchNormTraining(data, gamma, beta, eps)
     else:
-        return BatchNormInference(eps, gamma, beta, data, mean, variance)
+        return BatchNormInference(data, gamma, beta, mean, variance, eps)
 
 
 @nameable_op

python/pyngraph/ops/batch_norm.cpp

@@ -30,10 +30,10 @@ void regclass_pyngraph_op_BatchNormTraining(py::module m)
         batch_norm_training(m, "BatchNormTraining");
     batch_norm_training.doc() =
         "ngraph.impl.op.BatchNormTraining wraps ngraph::op::BatchNormTraining";
-    batch_norm_training.def(py::init<double,
+    batch_norm_training.def(py::init<const std::shared_ptr<ngraph::Node>&,
                                      const std::shared_ptr<ngraph::Node>&,
                                      const std::shared_ptr<ngraph::Node>&,
-                                     const std::shared_ptr<ngraph::Node>&>());
+                                     double>());
 }
 
 void regclass_pyngraph_op_BatchNormInference(py::module m)
@@ -45,12 +45,12 @@ void regclass_pyngraph_op_BatchNormInference(py::module m)
     batch_norm_inference.doc() =
         "ngraph.impl.op.BatchNormInference wraps ngraph::op::BatchNormInference";
 
-    batch_norm_inference.def(py::init<double,
+    batch_norm_inference.def(py::init<const std::shared_ptr<ngraph::Node>&,
                                       const std::shared_ptr<ngraph::Node>&,
                                       const std::shared_ptr<ngraph::Node>&,
                                       const std::shared_ptr<ngraph::Node>&,
                                       const std::shared_ptr<ngraph::Node>&,
-                                      const std::shared_ptr<ngraph::Node>&>());
+                                      double>());
 }
 
 void regclass_pyngraph_op_BatchNormTrainingBackprop(py::module m)
@@ -61,11 +61,11 @@ void regclass_pyngraph_op_BatchNormTrainingBackprop(py::module m)
         batch_norm_training_backprop(m, "BatchNormTrainingBackprop");
     batch_norm_training_backprop.doc() =
         "ngraph.impl.op.BatchNormTrainingBackprop wraps ngraph::op::BatchNormTrainingBackprop";
-    batch_norm_training_backprop.def(py::init<double,
+    batch_norm_training_backprop.def(py::init<const std::shared_ptr<ngraph::Node>&,
                                               const std::shared_ptr<ngraph::Node>&,
                                               const std::shared_ptr<ngraph::Node>&,
                                               const std::shared_ptr<ngraph::Node>&,
                                               const std::shared_ptr<ngraph::Node>&,
                                               const std::shared_ptr<ngraph::Node>&,
-                                              const std::shared_ptr<ngraph::Node>&>());
+                                              double>());
 }

python/setup.py

@@ -352,7 +352,7 @@ def build_extensions(self):
     requirements = req.read().splitlines()
 
 setup(
-    name='ngraph',
+    name='ngraph-core',
     version=__version__,
     author='Intel',
     author_email='[email protected]',

src/ngraph/descriptor/input.hpp

@@ -60,10 +60,10 @@ namespace ngraph
             void replace_output(Output& output);
 
         protected:
-            /// \return the tensor view for the connected output
+            /// \return the tensor for the connected output
             std::shared_ptr<const Tensor> get_tensor_ptr() const;
 
-            /// \return the tensor view for the connected output
+            /// \return the tensor for the connected output
             std::shared_ptr<Tensor> get_tensor_ptr();
 
         public:

src/ngraph/descriptor/layout/tensor_layout.hpp

@@ -32,7 +32,7 @@ namespace ngraph
     {
         namespace layout
         {
-            /// \brief Interface for describing implementations of tensor views.
+            /// \brief Interface for describing implementations of tensors.
             ///
             /// Kernel selection will need to pay attention to the layout.
             class TensorLayout
@@ -44,7 +44,7 @@ namespace ngraph
 
             public:
                 virtual ~TensorLayout() {}
-                /// Extent of this view in buffer.
+                /// Extent of this tensor in buffer.
                 ///
                 /// When we support non-linear buffers, this will need to be something other than size_t.
                 size_t get_size() const;

src/ngraph/descriptor/output.hpp

@@ -39,7 +39,7 @@ namespace ngraph
         public:
             /// \param node Node that owns this output.
             /// \param index Position of the output tensor in all output tensors
-            /// \param tensor The view of this tensor; where the value will be written
+            /// \param tensor The tensor where the value will be written
             Output(Node* node, size_t index, const std::shared_ptr<Tensor>& tensor);
 
             std::shared_ptr<Node> get_node() const;

src/ngraph/descriptor/tensor.hpp

@@ -35,7 +35,7 @@ namespace ngraph
             class TensorLayout;
         }
 
-        /// \brief Compile-time descriptor of a first-class value that is a view of a tensor.
+        /// \brief Compile-time descriptor of a first-class value that is a tensor.
         class Tensor
         {
             Tensor(const Tensor&) = delete;

src/ngraph/frontend/onnx_import/core/attribute.hpp

@@ -19,7 +19,6 @@
 #include <onnx-ml.pb.h>
 
 #include "ngraph/except.hpp"
-
 #include "tensor.hpp"
 
 namespace ngraph

src/ngraph/frontend/onnx_import/core/graph.hpp

@@ -16,14 +16,12 @@
 
 #pragma once
 
+#include <onnx-ml.pb.h>
 #include <string>
 #include <vector>
 
-#include <onnx-ml.pb.h>
-
-#include "ngraph/parameter_vector.hpp"
-
 #include "model.hpp"
+#include "ngraph/parameter_vector.hpp"
 #include "operator_set.hpp"
 #include "value_info.hpp"
 #include "weight.hpp"