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Last updated: Jan 12, 2024
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 or output data references:
- Local or managed assets from the space
- Connected (remote) assets: Cloud Object Storage
If you are specifying input/output data references programmatically:
- Data source reference
depends on the asset type. Refer to the Data source reference types section in Adding data assets to a deployment space.type
- If you deploy Pytorch models with ONNX format, specify the
flag and setkeep_initializers_as_inputs=True
toopset_version
(always set9
to the most recent version that is supported by the deployment runtime).opset_version
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