Comments (1)
I fixed it myself by replacing the default symbol database in model_config_pb2.py and service_pb2.py files with a new database. The default database is stored in the google protobuf module, which is shared among libraries like tritonclient and seldon mlserver that caused conflicts. This is only a walkaround and I barely have experiences with grpc, if anyone has a better solution I would appreciate very much.
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Related Issues (20)
- AttributeError: 'InferenceServerClient' object has no attribute 'InferInput' HOT 3
- Converting InferenceRequest to InferInput
- Revert urllib3 version pin HOT 11
- urllib dependency is present when using [grpc, cuda] options
- Add support for FetchContent or find_package HOT 2
- input_data HOT 1
- Any example of triton-vllm in c++?
- Incomplete installation of all genai-perf dependencies prevents its from being run on air-gapped servers HOT 2
- How do I get genai-perf to analyze my defined data set HOT 2
- genai-perf KeyError: 'service_kind' HOT 6
- tritonclient.utils.InferenceServerException: [StatusCode.INTERNAL] Unable to open shared memory region: '/output_simple'
- [QUESTION] - Tensorflow python infer to triton client
- How to write cmakelist to use grpcclient?
- Bug in grpc client
- Memory leak from grpcio
- Delayed aio infer during burst requests HOT 7
- Benchmarking VQA Model with Large Base64-Encoded Input Using perf_analyzer HOT 2
- Decreased Accuracy in Text Detection and Recognition Models after Upgrading to tritonclient 23.04-py3
- Allow client to request subset of ensemble model outputs HOT 1
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