Pysyft: Implement view Functionality in FloatTensor with CPU/GPU Backend Support

Created on 23 Nov 2017 · 5Comments · Source: OpenMined/PySyft

User Story:

As a Data Scientist using PySyft's FloatTensor type, I want to leverage a wide range of methods which use our new Unity backend. For this ticket to be complete, the view() should be added to our FloatTensor class with the appropriate functionality, returning a new tensor.

Every Reference You Might Need for this Issue:

For a reference on the operation this performs check out PyTorch's documentation.
For a reference on how to program in Unity, check out this basic tutorial
For a reference on how to write HLSL code, check out this basic tutorial
For a complete tutorial on how to add functions to FloatTensor (step by step guide) see this Google Document
For a reference on how other functions like this have been implemented check out the functions in this notebook as well as the corresponding files that made it possible (SyftController, FloatTensor.Ops, FloatTensor.ShaderOps, FloatTensorShaders, and FloatTensorTest).
And of course, please consider our Contributor Guidelines for all contributions.

Acceptance Criteria:
[ ] an integration test in PySyft demonstrating the correct CPU and GPU operation implemented over a FloatTensor while connected to a Unity backend
[ ] a Unit Test in OpenMined/OpenMined demonstrating the correct operation on a FloatTensor
[ ] [inline](http://pytorch.org/docs/master/tensors.html) documentation in the python code. For inspiration on inline documentation, please check out PyTorch's documentation for this operator.
[ ] Link your Pull Request back to this Issue so that it gets closed appropriately when the PR is merged.