ultralytics 8.2.23 New YouTube Shorts inference (#13150)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Erfan Zekri Esfahani <40582518+eze1376@users.noreply.github.com>
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@ -62,8 +62,9 @@ The Triton Model Repository is a storage location where Triton can access and lo
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from pathlib import Path
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# Define paths
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model_name = "yolo"
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triton_repo_path = Path("tmp") / "triton_repo"
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triton_model_path = triton_repo_path / "yolo"
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triton_model_path = triton_repo_path / model_name
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# Create directories
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(triton_model_path / "1").mkdir(parents=True, exist_ok=True)
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@ -86,6 +87,7 @@ The Triton Model Repository is a storage location where Triton can access and lo
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Run the Triton Inference Server using Docker:
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```python
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import contextlib
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import subprocess
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import time
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@ -125,7 +125,7 @@ The arguments provided when using [export](../modes/export.md) for an Ultralytic
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- `workspace` : Controls the size (in GiB) of the device memory allocation while converting the model weights.
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- Aim to use the <u>minimum</u> `workspace` value required as this prevents testing algorithms that require more `workspace` from being considered by the TensorRT builder. Setting a higher value for `workspace` may take **considerably longer** to calibrate and export.
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- Adjust the `workspace` value according to your calibration needs and resource availability. While a larger `workspace` may increase calibration time, it allows TensorRT to explore a wider range of optimization tactics, potentially enhancing model performance and accuracy. Conversely, a smaller `workspace` can reduce calibration time but may limit the optimization strategies, affecting the quality of the quantized model.
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- Default is `workspace=4` (GiB), this value may need to be increased if calibration crashes (exits without warning).
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