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[CUDA] update python doc for user_compute_stream (#19245)
### Description Update python doc about user_compute_stream in CUDA python API for https://github.com/microsoft/onnxruntime/pull/19229. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
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@ -61,7 +61,15 @@ Default value: 0
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Defines the compute stream for the inference to run on.
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It implicitly sets the `has_user_compute_stream` option. It cannot be set through `UpdateCUDAProviderOptions`, but rather `UpdateCUDAProviderOptionsWithValue`.
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This cannot be used in combination with an external allocator.
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This can not be set using the python API.
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Example python usage:
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```python
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providers = [("CUDAExecutionProvider", {"device_id":torch.cuda.current_device(), "user_compute_stream": str(torch.cuda.current_stream().cuda_stream)})]
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sess_options = ort.SessionOptions()
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sess = ort.InferenceSession("my_model.onnx", sess_options=sess_options, providers=providers)
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```
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To take advantage of user compute stream, it is recommended to use [I/O Binding](../api/python/api_summary.html#data-on-device) to bind inputs and outputs to tensors in device.
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### do_copy_in_default_stream
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Whether to do copies in the default stream or use separate streams. The recommended setting is true. If false, there are race conditions and possibly better performance.
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