Comments (6)
Can you try curl http://127.0.0.1:8080/ping
? It will return Status equals Healthy if your service run smoothly, else return Unhealthy
from serve.
This is my config.properties
file, you can refer to it:
inference_address=http://0.0.0.0:8080
management_address=http://0.0.0.0:8081
metrics_address=http://0.0.0.0:8082
load_models=all
install_py_dep_per_model=true
model_store=model-store
models={\
"FaceDetection": {\
"1.0": {\
"defaultVersion": true,\
"marName": "FaceDetection.mar",\
"minWorkers": 1,\
"maxWorkers": 1,\
"batchSize": 256,\
"maxBatchDelay": 100,\
"responseTimeout": 120\
}\
},\
"FaceExpression": {\
"1.0": {\
"defaultVersion": true,\
"marName": "FaceExpression.mar",\
"minWorkers": 1,\
"maxWorkers": 4,\
"batchSize": 256,\
"maxBatchDelay": 100,\
"responseTimeout": 120\
}\
},\
"FaceRecognition": {\
"1.0": {\
"defaultVersion": true,\
"marName": "FaceRecognition.mar",\
"minWorkers": 1,\
"maxWorkers": 4,\
"batchSize": 256,\
"maxBatchDelay": 100,\
"responseTimeout": 120\
}\
},\
"HumanPose": {\
"1.0": {\
"defaultVersion": true,\
"marName": "HumanPose.mar",\
"minWorkers": 1,\
"maxWorkers": 4,\
"batchSize": 256,\
"maxBatchDelay": 100,\
"responseTimeout": 120\
}\
},\
"ActionRecognition": {\
"1.0": {\
"defaultVersion": true,\
"marName": "ActionRecognition.mar",\
"minWorkers": 1,\
"maxWorkers": 4,\
"batchSize": 256,\
"maxBatchDelay": 100,\
"responseTimeout": 120\
}\
}\
}
from serve.
@danial880 Once you've started torchserve and loaded the model could you please try the following API to check that the model has been successfully loaded and the workers have started successfully:
curl http://127.0.0.1:8081/models/facex
Also, when you run curl -X POST http://127.0.0.1:8080/predictions/facex -T 0294.png
what happens?
Does curl hang or show any error?
from serve.
Status
Model Info
Upon posting image: curl command get executed with no error
from serve.
@danial880 The posted log does not include the information about inference. can you please post the full log?
from serve.
@lxning I have attached it in txt file
logs.txt
from serve.
Related Issues (20)
- Standardize PyTorch 2.x features config in model-config.yaml HOT 1
- NotImplementedError: Cannot copy out of meta tensor; no data! + Models not generating output text
- The service crashes if the model takes a long time to respond HOT 6
- Two-way authentication/Mutual SSL in gRPC
- Enable pytest test_example_torch_compile.py:test_example_torch_compile.py HOT 1
- Enable pytest test_torch_compile.py: test_serve_inference HOT 1
- ImportError: cannot import name 'packaging' from 'pkg_resources' HOT 4
- "Model mode control" for gRPC
- "Token Authorization" for gRPC
- [RFC] Token Authorization by default
- Follow up on token authentication PR comments HOT 6
- Running segment_anything_fast example locally HOT 1
- pytest: test_example_torch_compile.py is faling HOT 1
- Worker dead and yet describe_model gives me `worker.status: Ready`
- Locust monkey patching leads to test cross-talking
- How to send a torch array via request HOT 4
- Handling of subsequent RegisterModel calls to Management gRPC endpoint with same model & version
- torchserve bloom7b1 demo Load model failed HOT 2
- WARNING: sun.reflect.Reflection.getCallerClass is not supported. This will impact performance. HOT 1
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