Feature/redesign

[RobinKa]

• Remove original MultiVector class and use bare tf.Tensor instances and functions on them instead
• Use dense representation instead of sparse with blade indices
• Add new MultiVector class that just wraps those functions, operates on MultiVector instances and exposes less verbose operators (eg. ~ for reversion as before)

Advantages:

• Dense is faster (STA MV*MV roughly 50x speedup on GPU)
• No tf.Tensor * MultiVector issues (because tf.Tensor's __mul__ doesn't raise NotImplemented)
• Can easily use tensorflow functions etc.
• Easier implementation (no thinking about blade indices required anymore)

Disadvantages:

• Might be confusing having both the bare tf.Tensor representation and the MultiVector wrapper
• Sparse representation might still be faster on CPU, and uses less memory