Allow storing inputs and outputs of FrameworkProcessor cross-accounts

**Describe the feature you'd like**
Definitions:
- Account A: where I will run SageMaker FrameworkProcessor jobs.
- Account B: where data exists that I need to access for `ProcessingInput.source` and `ProcessingOutput.destination`
- Role A: IAM role in account A that has `SageMakerFullAccess` policy attached.
- Role B: IAM role in acount B that has S3 read and write access to the needed data.
Role A can assume role B, and role B has a trusted relationship with Role A.

Problem:
I would like to create a `FrameworkProcessor` (specifically a `TensorFlowProcessor`) instance that can run on Account A but read and write data to Account B to avoid having to copy data back and forth between the two accounts.

**How would this feature be used? Please describe.**
A `role` parameter could be added to the `ProcessingInput` and `ProcessingOutput` classes that would be assumed before accessing the data.
```
processor = TensorFlowProcessor(role=role_A,...)
processor.run(
inputs=[ProcessingInput(source=.., destination=.., role=role_B)],
outputs=[ProcessingOutput(source=..,destination=.., role=role_B)],
...
)
```

**Describe alternatives you've considered**
There is a `role` parameter in the `TensorFlowProcessor` constructor. However,

- Using Role A fails with error ` No S3 objects found under S3 URL...`: reason is object exists in Account B not A!
- Using Role B fails with error:

`botocore.exceptions.ClientError: An error occurred (ValidationException) when calling the CreateProcessingJob operation: RoleArn: Cross-account pass role is not allowed.`

Reason: we need the SageMaker permissions on Account A to be defined in the role.

How can I tell SageMaker to use Role A for creating and running the processing job but to assume role B to access the datasets in account B? For example, I am able to do that easily in SageMaker notebooks.

Please let me know if there is a way to achieve that with the current `FrameworkProcessor` implementation.