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
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 setopset_version
to9
(always setopset_version
to the most recent 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