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Added information about unsupported subgraphs for set affinity (#2872)

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Ilya Churaev 2020-10-29 06:22:25 +03:00 committed by GitHub
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docs/IE_DG/supported_plugins/HETERO.md
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@ -32,6 +32,8 @@ Another way to annotate a network is to set affinity manually using <code>ngraph
The fallback policy does not work if even one layer has an initialized affinity. The sequence should be calling of automating affinity settings and then fix manually. The fallback policy does not work if even one layer has an initialized affinity. The sequence should be calling of automating affinity settings and then fix manually.
> **NOTE**: If you set affinity manually, be careful at the current moment Inference Engine plugins don't support constant (`Constant`->`Result`) and empty (`Parameter`->`Result`) networks. Please avoid such subgraphs when you set affinity manually.
@snippet openvino/docs/snippets/HETERO1.cpp part1 @snippet openvino/docs/snippets/HETERO1.cpp part1
If you rely on the default affinity distribution, you can avoid calling <code>InferenceEngine::Core::QueryNetwork</code> and just call <code>InferenceEngine::Core::LoadNetwork</code> instead: If you rely on the default affinity distribution, you can avoid calling <code>InferenceEngine::Core::QueryNetwork</code> and just call <code>InferenceEngine::Core::LoadNetwork</code> instead:

2
docs/nGraph_DG/nGraph_Python_API.md
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@ -188,6 +188,8 @@ for node in function.get_ordered_ops():
Attributes are properties of nodes in the computational graph, which will be stored when the model is serialized to a file. However, there can be additional properties of nodes, which are only important during the execution of a graph. An example of such a property is `affinity`, which determines which operation will be executed on which hardware in a heterogeneous environment. You can get and set runtime information by using the `get_rt_info` method of a node. Attributes are properties of nodes in the computational graph, which will be stored when the model is serialized to a file. However, there can be additional properties of nodes, which are only important during the execution of a graph. An example of such a property is `affinity`, which determines which operation will be executed on which hardware in a heterogeneous environment. You can get and set runtime information by using the `get_rt_info` method of a node.
> **NOTE**: If you set affinity manually, be careful at the current moment Inference Engine plugins don't support constant (`Constant`->`Result`) and empty (`Parameter`->`Result`) networks. Please avoid such subgraphs when you set affinity manually.
```python ```python
rt_info = node.get_rt_info() rt_info = node.get_rt_info()
rt_info["affinity"] = "test_affinity" rt_info["affinity"] = "test_affinity"