Closed zhukai242 closed 1 year ago
@dyastremsky @Tabrizian
I don't know what is being done in utils.postprocess
but adding .contiguous
before returning the tensors would usually solve this issue.
@Tabrizian thanks, this is utils.py where i need to add .contiguous utils.py.txt
@zhukai242 Could you please try again on the 23.05 release? We had some fixes that could be related to this issue.
Closing issue due to inactivity. Please let us know if you need to reopen the issue for follow-up.
Description i use model.onnx transform from yolov5s.pt(v6.1) , deploy in triton server, as the model name yolo, and add nms in ensemble
tritonclient.utils.InferenceServerException: [400] in ensemble 'simple_yolov5_ensemble', Failed to process the request(s) for model instance 'nms_0', message: TritonModelException: DLPack tensor is not contiguous. Only contiguous DLPack tensors that are stored in C-Order are supported
Triton Information docker image tag is 23.04-py3
Are you using the Triton container or did you build it yourself? container
To Reproduce Steps to reproduce the behavior. i use model.onnx transform from yolov5s.pt(v6.1) ,as the model name yolo, and add nms in ensemble here is my some code file: ensembel config.pbtxt
name: "simple_yolov5_ensemble" platform: "ensemble" max_batch_size: 8 input [ { name: "ENSEMBLE_INPUT_0" data_type: TYPE_FP32 dims: [1,3, 640, 640] } ]
output [ name: "simple_yolov5_ensemble" { name: "ENSEMBLE_OUTPUT_0" data_type: TYPE_FP32 dims: [ 300, 6 ] } ]
ensemble_scheduling { step [ { model_name: "yolo" model_version: 1 input_map: { key: "images" value: "ENSEMBLE_INPUT_0" } output_map: { key: "output" value: "FILTER_BBOXES" } }, { model_name: "nms" model_version: 1 input_map: { key: "candidate_boxes" value: "FILTER_BBOXES" } output_map: { key: "BBOXES" value: "ENSEMBLE_OUTPUT_0" } } ] }
nms model.py error line is : model.py.txt out_tensor = pb_utils.Tensor.from_dlpack('BBOXES', to_dlpack(bboxes))
here is client code: