* Rewrites public function signatures to operate on tensors (vs ndarray).
* Most of our backends presume immutable tensors at public function boundaries.
* This elides the very common code the compiler adds for chaining otherwise tensor-related numpy ops together.
* More aggressive canonicalizations would require more advanced analysis.
* Preserving shape across the copy ops makes more thing shaped by default.
* Inference of ndarray types will now preserve the shape when specializing the dtype.
* Adds an op interface for adding CPA constraints.
* Adds a type conversion hook for handling built-in types (that we can't have adopt our interface).
* Converts tensor<> to object(!Tensor, [e:<type>]) just like NdArray.
* Implement a few numpy ops far enough to do dtype inference for simple sequences.
The secret here is LLVM_ENABLE_WARNINGS=ON.
I also fixed a couple warnings, which gets us to be warning-clean.
I noticed also that npcomp-run-mlir/basic.mlir seems to be failing.
Maybe something since the latest integrate. My next commit (introduce
npcomp mini runtime) will largely rewrite it though, so it'll get fixed
then.