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52 lines
1.5 KiB
Markdown
52 lines
1.5 KiB
Markdown
---
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title: Model Execution
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parent: Deploy ONNX Runtime Mobile
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grand_parent: Tutorials
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has_children: false
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nav_order: 5
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---
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{::options toc_levels="2..4" /}
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# Executing an ORT format model
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The API for executing ORT format models is the same as for ONNX models.
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See the [ONNX Runtime API documentation](../api) for details on individual API usage.
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## APIs by platform
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| Platform | Available APIs |
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|----------|----------------|
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| Android | C, C++, Java |
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| iOS | C, C++, Objective-C (Swift via bridge) |
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## ORT format model loading
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If you provide a filename for the ORT format model, a file extension of '.ort' will be inferred to be an ORT format model.
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If you provide in-memory bytes for the ORT format model, a marker in those bytes will be checked to infer if it's an ORT format model.
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If you wish to explicitly say that the InferenceSession input is an ORT format model you can do so via SessionOptions, although this generally should not be necessary.
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C++ API
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```c++
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Ort::SessionOptions session_options;
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session_options.AddConfigEntry('session.load_model_format', 'ORT');
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Ort::Env env;
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Ort::Session session(env, <path to model>, session_options);
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```
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Java API
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```java
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SessionOptions session_options = new SessionOptions();
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session_options.addConfigEntry("session.load_model_format", "ORT");
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OrtEnvironment env = OrtEnvironment.getEnvironment();
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OrtSession session = env.createSession(<path to model>, opsession_optionstions);
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```
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------
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Next: [Using NNAPI and CoreML with ORT Mobile](using-nnapi-coreml-with-ort-mobile)
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