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Move setup message into the Setup environment section in TRT tutorial (Project-MONAI#1344)
### Description Move some text from the introduction to Setup environment ### Checks <!--- Put an `x` in all the boxes that apply, and remove the not applicable items --> - [x] Avoid including large-size files in the PR. - [x] Clean up long text outputs from code cells in the notebook. - [x] For security purposes, please check the contents and remove any sensitive info such as user names and private key. - [x] Ensure (1) hyperlinks and markdown anchors are working (2) use relative paths for tutorial repo files (3) put figure and graphs in the `./figure` folder - [x] Notebook runs automatically `./runner.sh -t <path to .ipynb file>` Signed-off-by: Mingxin Zheng <[email protected]>
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acceleration/TensorRT_inference_acceleration.ipynb

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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This tutorial shows how to convert a bundle into a TensorRT engine-based TorchScript for better performance and benchmark the latency difference between the original bundle and the TensorRT engine-based TorchScript.\n",
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"\n",
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"The `spleen_ct_segmentation` bundle is used as the example in this tutorial. The inference latency before and after the coversion process will be compared. The TensorRT conversion is supported since **MONAI 1.2** with **Torch-TensorRT 1.4.0** and **TensorRT 8.5.3**. Please use the MONAI Docker whose version is >=1.2 or ensure the environment meets the min version requirement."
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"The `spleen_ct_segmentation` bundle is used as the example in this tutorial. The inference latency before and after the coversion process will be compared. "
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Setup environment"
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"## Setup environment\n",
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"\n",
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"The TensorRT conversion is supported since **MONAI 1.2** with **Torch-TensorRT 1.4.0** and **TensorRT 8.5.3**. If a docker container is used, please ensure the MONAI version is >=1.2 or the environment meets the min version requirement."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"root dir is: /workspace/data/medical\n"
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"root dir is: /workspace/data\n"
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]
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}
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],

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