Using model.resource_name and endpoint.resource_name to instantiate the model and endpoint resources about vertex-ai-samples HOT 3 CLOSED

Hi, a few questions to troubleshoot this:

• Can you confirm that you've successfully trained a model in the previous steps?
• Also you've updated the DEPLOYED_MODEL_NAME variable?
• Can you provide the details of the error message you're seeing?

from vertex-ai-samples.

@aarondietz234 Can you take a look at this?

from vertex-ai-samples.

Hi, to answer the questions:

• I have trained the model and uploaded the model to Vertex Models
  (screenshot included)
  

• I updated the DEPLOYED_MODEL_NAME as the deployed model name, "fraud-detection-model-v1"

  • variables used to retrieve the model and the endpoint: MODEL_DISPLAY_NAME: fraud-detection-model
    ENDPOINT_DISPLAY_NAME: fraud-detection-model-ep1
    

• Error Message:

InactiveRpcError Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/google/api_core/grpc_helpers.py in error_remapped_callable(*args, **kwargs)
65 try:
---> 66 return callable(*args, **kwargs)
67 except grpc.RpcError as exc:

/opt/conda/lib/python3.7/site-packages/grpc/_channel.py in call(self, request, timeout, metadata, credentials, wait_for_ready, compression)
945 wait_for_ready, compression)
--> 946 return _end_unary_response_blocking(state, call, False, None)
947

/opt/conda/lib/python3.7/site-packages/grpc/_channel.py in _end_unary_response_blocking(state, call, with_call, deadline)
848 else:
--> 849 raise _InactiveRpcError(state)
850

_InactiveRpcError: <_InactiveRpcError of RPC that terminated with:
status = StatusCode.INVALID_ARGUMENT
details = "List of found errors: 1.Field: name; Message: Invalid Model resource name. "
debug_error_string = "{"created":"@1636406161.921552593","description":"Error received from peer ipv4:142.250.128.95:443","file":"src/core/lib/surface/call.cc","file_line":1066,"grpc_message":"List of found errors:\t1.Field: name; Message: Invalid Model resource name.\t","grpc_status":3}"

The above exception was the direct cause of the following exception:

InvalidArgument Traceback (most recent call last)
/tmp/ipykernel_1/2157564676.py in
1 # instantiate the model and endpoint resources
----> 2 model = aiplatform.Model(model_name=MODEL_DISPLAY_NAME)
3 endpoint = aiplatform.Endpoint(endpoint_name=ENDPOINT_DISPLAY_NAME)
4
5 # deploy the model to the endpoint

/opt/conda/lib/python3.7/site-packages/google/cloud/aiplatform/models.py in init(self, model_name, project, location, credentials)
1394 resource_name=model_name,
1395 )
-> 1396 self._gca_resource = self._get_gca_resource(resource_name=model_name)
1397
1398 # TODO(b/170979552) Add support for predict schemata

/opt/conda/lib/python3.7/site-packages/google/cloud/aiplatform/base.py in _get_gca_resource(self, resource_name)
531 )
532
--> 533 return getattr(self.api_client, self._getter_method)(name=resource_name)
534
535 def _sync_gca_resource(self):

/opt/conda/lib/python3.7/site-packages/google/cloud/aiplatform_v1/services/model_service/client.py in get_model(self, request, name, retry, timeout, metadata)
589
590 # Send the request.
--> 591 response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
592
593 # Done; return the response.

/opt/conda/lib/python3.7/site-packages/google/api_core/gapic_v1/method.py in call(self, timeout, retry, *args, **kwargs)
140 kwargs["metadata"] = metadata
141
--> 142 return wrapped_func(*args, **kwargs)
143
144

/opt/conda/lib/python3.7/site-packages/google/api_core/grpc_helpers.py in error_remapped_callable(*args, **kwargs)
66 return callable_(*args, **kwargs)
67 except grpc.RpcError as exc:
---> 68 raise exceptions.from_grpc_error(exc) from exc
69
70 return error_remapped_callable

InvalidArgument: 400 List of found errors: 1.Field: name; Message: Invalid Model resource name.

• I checked the Apiplatform SDK, both APIs need to use resource name or ID to retrieve model and endpoint. Here we're using the display names rather than the resource names.
  
  

I tried to run with resource_name and it worked. I hope this helps with troubleshooting!

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