Comments (4)
@zhjwy9343 is the data scentist for authoring those Notebook. James, could you have a look at those problems?
from realtime-fraud-detection-with-gnn-on-dgl.
@zinebtabet Could you add the detailed reproduciable steps how you using the code?
from realtime-fraud-detection-with-gnn-on-dgl.
I used the same code as you have in the SageMaker repository. The only thing I modified was the Docker file since I am in EU West 3. I set it up like this: ARG IMAGE_REPO=763104351884.dkr.ecr.eu-west-3.amazonaws.com FROM $IMAGE_REPO/pytorch-training:1.11.0-cpu-py38-ubuntu20.04-sagemaker ENV PATH="/opt/ml/model:${PATH}" ENV SAGEMAKER_SUBMIT_DIRECTORY /opt/ml/model COPY * /opt/ml/code/ ENV SAGEMAKER_PROGRAM fd_sl_train_entry_point.py RUN pip install dgl dglgo -f https://data.dgl.ai/wheels/repo.html
I used the same version I specified in the Docker file for the deployment as well. Then I invoked my endpoint with the Lambda function. Once I executed the test event, I received this error. I have had this error for over a month now. I will provide screenshots of the error:
the error in the lambda test event: Traceback (most recent call last): File "/var/task/lambda_function.py", line 442, in lambda_handler pred_prob = invoke_endpoint_with_idx(endpointname = ENDPOINT_NAME, target_id = transaction_id, subgraph_dict = subgraph_dict, n_feats = transaction_embed_value_dict) File "/var/task/lambda_function.py", line 314, in invoke_endpoint_with_idx response = runtime.invoke_endpoint(EndpointName=endpointname, File "/opt/python/lib/python3.8/site-packages/botocore/client.py", line 508, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/python/lib/python3.8/site-packages/botocore/client.py", line 911, in _make_api_call raise error_class(parsed_response, operation_name)
from realtime-fraud-detection-with-gnn-on-dgl.
Hello @zxkane,
Thank you for the nice project. I learn a lot from it.
We use the SageMaker notebook & studio to reproduce the project. The model was created and repackaged successfully and the endpoints of them work well. Suddenly, (in a middle of a demo) the endpoint didn't respond.
Right now, we have only one model that has a workable endpoint which is trained and repackaged with SageMaker notebook.
From then none of our endpoints (the models created with notebook or studio) does not work anymore.
I appreciate any help or suggestion!
from realtime-fraud-detection-with-gnn-on-dgl.
Related Issues (20)
- The data path inside sagemaker notebook does not work
- DataIngestLayer size exceed 250MB
- glue etl job failed on No module named 'tornado' HOT 1
- Reporting a vulnerability HOT 2
- Running the Step functions pipeline fails with "Essential Container Exited" error HOT 2
- no module named ‘aiohttp’ in inference lambda
- Having trouble to access files from S3 HOT 1
- improve data etl
- sagemaker endpoint fail to deploy or time out server error(0) bug
- failed to deploy training stack due to error ‘clouwatchs logs resource policy size was exceeded’
- enable access log for all s3 buckets
- polish neptune configuration
- polish docdb configuration
- enable vpc flow logs
- polish httpapi configuration
- polish lambda configuration
- Embedded stack arn:aws:cloudformation:us-east-1:578053008623:stack/fraud-detection-on-dgl-dashboardNestedStackdashboardNestedStackResourceB80305B3-1QLN9Y8UK7DTK/bc188160-343f-11ed-96bf-12d3ddd822cb was not successfully created: The following resource(s) failed to create: [FraudDetectionDashboardAPID13F00C7]. HOT 3
- enable log encryption of glue
- failed to run glue ETL job due to exception ‘Failed to AssociateKmsKey for logGroup using KmsKeyId’ HOT 1
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