SNPE 模型转换错误:

[旺仔QQq糖]

SNPE 模型转换错误:
你好，我遇到了一些问题。

snpe-onnx-to-dlc -i models/yolo_nas_s.onnx -o models/yolo_nas_s.dlc --out_node 877 --out_node 885
2024-11-20 07:52:50,115 - 235 - INFO - Simplified model validation is successful
2024-11-20 07:52:50,501 - 240 - WARNING - Output node 877, specified via command line, does not exist in graph.
2024-11-20 07:52:50,502 - 240 - WARNING - Output node 885, specified via command line, does not exist in graph.

遇到错误：修剪断开节点后，该模型为空。
堆栈跟踪：

Traceback (most recent call last):
File "/opt/qcom/aistack/qairt/2.27.0.240926/bin/x86_64-linux-clang/snpe-onnx-to-dlc", line 62, in
optimized_graph = optimizer.optimize(graph)
File "/opt/qcom/aistack/qairt/2.27.0.240926/lib/python/qti/aisw/converters/common/converter_ir/op_graph_optimizations.py", line 432, in optimize
remove_disconnected_nodes(graph)
File "/opt/qcom/aistack/qairt/2.27.0.240926/lib/python/qti/aisw/converters/common/converter_ir/op_graph_optimizations.py", line 1468, in remove_disconnected_nodes
raise ValueError("After pruning disconnected nodes, this model is empty.")

[weixin_38498942]

您可以按照 GenerateDLC.ipynb 中的步骤，在您的环境中对 super_gradients 进行以下修改。

这有效:
training/pretrained_models.py:47: "yolo_nas_s_coco": "https://sg-hub-nv.s3.amazonaws.com/models/yolo_nas_s_coco.pth%22,
training/utils/checkpoint_utils.py:316: unique_filename = url.split("https://sg-hub-nv.s3.amazonaws.com/models/%22)[1].replace("/", "").replace(" ", "")