As of version ``0.15``, there is a new backend API to work with functions that
can be compiled as a runtime ``Executable``. Where previously ``Backend`` used a
``shared_ptr<Function>`` as the handle passed to the ``call`` method to execute
a compiled object, the addition of the ``shared_ptr<Executable>`` object has
more direct methods to actions such as ``validate``, ``call``, ``get_performance_data``, and so on. This new API permits any executable to be saved or loaded *into* or
more direct methods to actions such as ``validate``, ``call``, ``get_performance_data``,
and so on. This new API permits any executable to be saved or loaded *into* or
*out of* storage and makes it easier to distinguish when a Function is compiled,
thus making the internals of the ``Backend`` and ``Executable`` easier to
@@ -15,8 +15,9 @@ each of these briefly to get started.
A framework bridge interfaces with the "frontend" Core API. A framework bridge
is a component that sits between a framework like TensorFlow or MXNet, and the
nGraph Core frontend API. A framework bridge does two things: first, it
translates a framework's operations into graphs in nGraph’s in-memory :abbr:`Intermediary Representation (IR)`. Second, it executes the nGraph IR graphs via
the backend execution interface.
translates a framework's operations into graphs in nGraph’s in-memory
:abbr:`Intermediary Representation (IR)`. Second, it executes the nGraph IR
graphs via the backend execution interface.
The details of bridge implementation vary from framework to framework, but there
are some common patterns: a fairly typical example for a graph-based framework
...
...
@@ -59,16 +60,14 @@ descriptions:
.. csv-table::
:header: "Namespace", "Description", "Location in Repo", "Docs"
:widths: 23, 53, 13, 23
:escape: ~
``ngraph``, The Intel nGraph C++ API, `ngraph`_, Implicit namespace omitted from most API documentation
``ngraph``, The Intel nGraph C++ API, ngraph, Implicit namespace omitted from most API documentation
``builder``, "Convenience functions that create additional graph nodes to implement commonly-used recipes; for example, auto-broadcast", `builder`_, Coming Soon
``descriptor``, Descriptors are compile-time representations of objects that will appear at run-time, `descriptor`_, Coming Soon
``op``, Ops used in graph construction, `op`_, :doc:`../ops/index`
``runtime``, The objects and methods used for executing the graph, `runtime`_, :doc:`../backend-support/cpp-api`
``runtime``, The objects and methods used for executing the graph, `runtime`_, :doc:`../backends/cpp-api`
[nGraph's build instructions][ngraph_build] give detailed instructions on building nGraph on different operating systems. Please make sure you specify the options `-DNGRAPH_PYTHON_BUILD_ENABLE=ON` and `-DNGRAPH_ONNX_IMPORT_ENABLE=ON` when building nGraph. Use the `make python_wheel` command to build nGraph and create Python packages.
