core: (affine) Add functions dealing with dimensions to AffineMap and AffineExpr

[watermelonwolverine]

Add a couple of utility functions to AffineMap and AffineExpr that deal with dimensions.
Cherry picked from #3650, prerequisite for implementing vector.transfer_read and vector.transfer_write ops

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 90.19%. Comparing base (a9ee7c9) to head (bf55c00).
Report is 2 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #4007   +/-   ##
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  Coverage   90.19%   90.19%           
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  Files         458      458           
  Lines       58319    58341   +22     
  Branches     5688     5692    +4     
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+ Hits        52598    52619   +21     
  Misses       4331     4331           
- Partials     1390     1391    +1     

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[superlopuh]

Do you know what MLIR does here? We should probably mimic their beaviour.

[watermelonwolverine]

is_function_of_dim is basically bool isFunctionOfDim(unsigned position)
ununsed_dims_bit_vector is basically llvm::SmallBitVector getUnusedDimsBitVector(ArrayRef<AffineMap> maps); (or at least a precursor to it)
Both are in mlir/include/mlir/IR/AffineMap.h

Both used_dims and unused_dims are just utiltity functions I added to make the implementation a bit more pythonic

[superlopuh]

Am I right in understanding that neither unused_dims nor the bit vector version are used in your other PR? Are we sure we need these helpers?

[superlopuh]

Actually it seems like none of these helpers are used?

[watermelonwolverine]

I just updated that PR, have a look now. I removed some verification that wasn't ready yet because of the changes that needed to be done to the VectorType

[superlopuh]

Set construction feels expensive enough to me to only want to do it once:

Suggested change

	result: set[int] = set()
	for expr in self.results:
	result = result.union(expr.used_dims())
	return result
	return {expr.position for res_expr in self.results for expr in res_expr.dfs() if isinstance(expr, AffineDimExpr)}

[superlopuh]

Same here, let's avoid the set construction

Suggested change

	used_dims = self.used_dims()
	return tuple(
	True if position in used_dims else False
	for position in range(self.num_dims)
	)
	used_dims = [False] * self.num_dims
	for res_expr in self.results:
	for expr in res_expr.dfs():
	if isinstance(expr, AffineDimExpr):
	used_dims[expr.position] = True
	return tuple(used_dims)

[superlopuh]

Thank you!