Introduce branchless implementations of TensorImpl bools (#94473)
This is the main payload of this diff stack. With it, we are able to construct a 1D tensor from unbacked SymInt with guards that are equivalent to asserting that the size is non-negative (which makes sense!) To get here, I had to arrange for all of the guards that occur when doing contiguity tests to be lazy. This was done by writing non-branching implementations of each of the tests in `sympy_is_contiguous` etc functions, and then using those implementations when we don't branch.
I also had to do some bug fixes for `is_non_overlapping_and_dense`, as unbacked SymInts were very untested previously (and that was the only time you would actually hit the Python version of the code.) In particular, we now consistently pass separate sizes/strides lists into each of the boolean computation functions (and only pack them into a single argument list when going to Sympy, which doesn't support lists of variables in custom functions.)
Finally, to actually test that this is doing something, I add a simple assumptions system from https://github.com/pytorch/pytorch/pull/90985 and use this to get the end to end test test_item_to_constructor passing. Soon, I intend to replace this with a range analysis system which will be used for assumptions in the short term. (We still might use Z3, but for all the stray assumptions I've seen range analysis will be good enough.)
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94473
Approved by: https://github.com/albanD
