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Documentation updates (#1433)

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This commit is contained in:
Ilya Lavrenov
2020-07-23 13:15:20 +03:00
committed by GitHub
parent 8fedb0bf94
commit 9440561fa4
12 changed files with 197 additions and 160 deletions
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17
docs/optimization_guide/dldt_optimization_guide.md
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@@ -272,15 +272,13 @@ using namespace InferenceEngine::PluginConfigParams;
using namespace InferenceEngine::HeteroConfigParams;
...
enginePtr = dispatcher.getPluginByDevice("HETERO:FPGA,CPU");
InferencePlugin plugin(enginePtr);
plugin.SetConfig({ {KEY_HETERO_DUMP_GRAPH_DOT, YES} });
auto execNetwork = ie.LoadNetwork(network, "HETERO:FPGA,CPU", { {KEY_HETERO_DUMP_GRAPH_DOT, YES} });
```
After enabling the configuration key, the heterogeneous plugin generates two files:
- `hetero_affinity.dot` - per-layer affinities. This file is generated only if default fallback policy was executed (as otherwise you have set the affinities by yourself, so you know them).
- `hetero_subgraphs.dot` - affinities per sub-graph. This file is written to the disk during execution of `ICNNNetwork::LoadNetwork` for the heterogeneous plugin.
- `hetero_subgraphs.dot` - affinities per sub-graph. This file is written to the disk during execution of `Core::LoadNetwork` for the heterogeneous flow.
You can use GraphViz\* utility or `.dot` converters (for example, to `.png` or `.pdf`), like xdot\*, available on Linux\* OS with `sudo apt-get install xdot`. Below is an example of the output trimmed to the two last layers (one executed on the FPGA and another on the CPU):
@@ -439,16 +437,11 @@ Infer Request based API offers two types of request: Sync and Async. The Sync is
More importantly, an infer request encapsulates the reference to the “executable” network and actual inputs/outputs. Now, when you load the network to the plugin, you get a reference to the executable network (you may consider that as a queue). Actual infer requests are created by the executable network:
```cpp
CNNNetReader network_reader;
network_reader.ReadNetwork("Model.xml");
network_reader.ReadWeights("Model.bin");
auto network = network_reader.getNetwork();
Core ie;
auto network = ie.ReadNetwork("Model.xml", "Model.bin");
InferenceEngine::InputsDataMap input_info(network.getInputsInfo());
InferenceEnginePluginPtr engine_ptr = PluginDispatcher(pluginDirs).getSuitablePlugin(TargetDevice::eGPU);
InferencePlugin plugin(engine_ptr);
auto executable_network = plugin.LoadNetwork(network, {/*opt config*/});
auto executable_network = ie.LoadNetwork(network, "GPU");
auto infer_request = executable_network.CreateInferRequest();
for (auto & item : inputInfo) {