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Revert #579 #581

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Apr 17, 2024
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Revert #579 #581

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3 changes: 2 additions & 1 deletion models/lung_nodule_ct_detection/configs/metadata.json
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Original file line number Diff line number Diff line change
@@ -1,7 +1,8 @@
{
"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
"version": "0.6.4",
"version": "0.6.5",
"changelog": {
"0.6.5": "remove notes for trt_export in readme",
"0.6.4": "add notes for trt_export in readme",
"0.6.3": "add load_pretrain flag for infer",
"0.6.2": "add checkpoint loader for infer",
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2 changes: 0 additions & 2 deletions models/lung_nodule_ct_detection/docs/README.md
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Expand Up @@ -130,8 +130,6 @@ It is possible that your inference dataset should set `"affine_lps_to_ras": fals
python -m monai.bundle trt_export --net_id network_def --filepath models/model_trt.ts --ckpt_file models/model.pt --meta_file configs/metadata.json --config_file configs/inference.json --precision <fp32/fp16> --input_shape "[1, 1, 512, 512, 192]" --use_onnx "True" --use_trace "True" --onnx_output_names "['output_0', 'output_1', 'output_2', 'output_3', 'output_4', 'output_5']" --network_def#use_list_output "True"
```

Note that if you're using a container based on [PyTorch 24.03](nvcr.io/nvidia/pytorch:24.03-py3), and the size of your input exceeds (432, 432, 152), the TensorRT export might fail. In such cases, it would be necessary for users to manually adjust the input_shape downwards. Keep in mind that minimizing the input_shape could potentially impact performance. Hence, always reassess the model's performance after making such adjustments to validate if it continues to meet your requirements.

#### Execute inference with the TensorRT model

```
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