optimized_execution() takes 1 positional argument but 2 were given
I'm following the pytorch sagemaker docs here and I'm stuck on this line

torch.jit.optimized_execution(True, {'target_device': 'eia:device ordinal'})

When I run it, I get the error optimized_execution() takes 1 positional argument but 2 were given. I'm using pytorch 1.3.1, but I tried with 1.4.0 and was running into similar problems. Can I use optimized execution without this second argument? How can I specify the accelerator?

(I'll refer to the Elastic Inference enabled PyTorch framework as "PyTorch-EI" for convenience)

Are you using SageMaker through notebook or hosting? SageMaker notebook support is not currently released, so there's no official notebook kernel / Conda environment that you can activate that will have the Elastic Inference enabled PyTorch framework. You could however create your own by activating the pytorch_p36 environment (which has standard PyTorch), uninstalling PyTorch, and then installing using the PyTorch-EI 1.3.1 framework wheel - linked from here.

SageMaker hosting does currently support PyTorch-EI out of the box. If you're currently using SageMaker hosting and having issues, share some of your inference code + what container you're using. List of containers can be found at here.

Also note that EC2 currently supports Elastic Inference through the DLAMI v27.0. The Conda environment name is amazonei_pytorch_p36.
