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Batch deployment input details for Pytorch models

Follow these rules when you are specifying input details for batch deployments of Pytorch models.

Data type summary table:

Data	Description
Type	inline, data references
File formats	.zip archive that contains JSON files

Data Sources

Input/output data references:

Local/managed assets from the space
Connected (remote) assets: Cloud Object Storage and Storage Volumes

If you are specifying input/output data references programmatically:

Data source reference type depends on the asset type. Refer to the Data source reference types section in Adding data assets to a deployment space.
If you deploy Pytorch models with ONNX format, specify the keep_initializers_as_inputs=True flag and set opset_version to 9 (always set opset_version to the latest version that is supported by the deployment runtime).
```
torch.onnx.export(net, x, 'lin_reg1.onnx', verbose=True, keep_initializers_as_inputs=True, opset_version=9)
```

Note: The environment variables parameter of deployment jobs is not applicable.

Parent topic: Batch deployment input details by framework