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System Information
- Framework (e.g. TensorFlow) / Algorithm (e.g. KMeans): SageMaker/Factorization Machines
- Framework Version:
- Python Version:
- CPU or GPU:
- Python SDK Version:
- Are you using a custom image:
Describe the problem
I was able to train the model with sparse matrix recordIO file created with sagemaker python sdk. For inference, looks like JSON and RecordIO are supported.
If I want to use to JSON, how should I pass in the sparse matrix information? Ideally, it is preferable to send only the columns for which values exist.
For example: 623:1 3399:1
Thank you for the prompt help so far
Minimal repro / logs
Please provide any logs and a bare minimum reproducible test case, as this will be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.
- Exact command to reproduce:
Please fill out the form below.
System Information
Describe the problem
I was able to train the model with sparse matrix recordIO file created with sagemaker python sdk. For inference, looks like JSON and RecordIO are supported.
If I want to use to JSON, how should I pass in the sparse matrix information? Ideally, it is preferable to send only the columns for which values exist.
For example: 623:1 3399:1
Thank you for the prompt help so far
Minimal repro / logs
Please provide any logs and a bare minimum reproducible test case, as this will be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.