Add options for eval and gradient required

[ElliottKasoar]

Resolves #73

Adds flags in all(?) functions that operate on tensors (tensor creation, model loading, forward) to optionally disable autograd, which should improve performance for inference.

Also adds a similar flag to set evaluation mode for the loaded model.

• Evaluation mode

  • Contrary to my initial comments in Loaded TorchScript missing no_grad context  #73, from testing evaluation mode does appear to be preserved, both between saving and loading TorchScript, and when applied to the loaded model.
  • In most cases evaluation mode is therefore likely to already be set, but I think it's useful to have the option to change it, particularly if FTorch may be extended to facilitate training (Training functionality #22).

• NoGradMode

  • Enabling or disabling gradients is more complicated, as it defined via a context manager, which only appears to define the behaviour within its own scope, and so it seems necessary to enable/disable gradients before every code block that operates on tensors (similar to the Python equivalent with torch.no_grad():).

• InferenceMode

  • No changes are currently included, but it would be good to support InferenceMode too eventually, as it should provide further performance benefits over NoGradMode.
  • However, it has stricter requirements, and the mode was only added (as a beta) in PyTorch 1.9, so we would need to be careful if we want to support older versions.

• Model freezing

  • No changes are currently included, and less directly applicable to the main FTorch library, although there are still interactions e.g. freezing the model can allow InferenceMode to be enabled when loading the model.
  • Freezing is currently the "default" when tracing in pt2ts.py, but not for scripting, despite potentially improving performance.
  • Freezing appears to (sometimes) introduce numerical errors when saving the reloading (differences ~10^-6), and can seem to lead to issues loading with Forpy too.

(For more general explanation of autograd/evaluation mode, see autograd mechanics).

Note: I've also removed the old, commented out torch_from_blob function.

[TomMelt]

thanks @ElliottKasoar , these changes look great to me

[jatkinson1000]

I'll review this in the new year.
I see @TomMelt is happy, but there are a lot of changes so I also want to be sure I've understood them.

[jatkinson1000]

A new PR rebasing this work on top of the latest changes to resolve conflicts is at #103

[jatkinson1000]

Since #103 is progressing I am closing this.