-assume-no-undeclared-side-effects : Allow dead code to be eliminated in some situations (e.g. dead while loops) under the assumption that ops are pure unless declared with explicit MLIR `MemoryEffects`. Notably, this means `func.call` ops will be assumed pure.
-fold-op-element-limit             : Upper limit on how many elements may be folded by an op folder. This limit doesn't apply in certain special cases such as addition with 0, multiplication by 1, and some splat operations.
-optimize-float                    : Allow float optimizations that, though mathematically equivalent, may result in slightly different quantization of floating-point values (e.g. `log(sqrt(x))` -> `0.5 * log(x)`). Float optimizations that can't affect numerical results are always enabled.

- add(cst, X) -> add(X, cst)
- add(X, 0) -> X
- and(cst, X) -> and(X, cst)
- and(X, 0) -> 0
- and(X, 1) -> X
- broadcast_in_dim(broadcast_in_dim(X, [dimsA...]), [dimsB...]) -> broadcast_in_dim(X, merge(dimsA, dimsB))
- broadcast_in_dim(X, [dims...]) -> transpose(X, [dims...]) [if same numel & rank]
- broadcast_in_dim(X, [iota...]) -> X
- broadcast_in_dim(X, [sorted...]) -> reshape(X, [sorted...]) [if same numel]
- compare(cst, X, comparator) -> compare(X, cst, inv(comparator))
- compare(X, X, [EQ,GE,LE]) -> true
- compare(X, X, [NE,GT,LT]) -> false
- complex(real(X), imag(X))) -> X
- concatenate(concatenate(X, Y), Z) -> concatenate(X, Y, Z)
- concatenate(X) -> X
- concatenate(X, Y, []) -> concatenate(X, Y)
- convert(X, [X.type]) -> X
- dynamic_broadcast_in_dim(dynamic_broadcast_in_dim(X, _, [dimsA...]), shape, [dimsB...]) -> dynamic_broadcast_in_dim(X, shape, merge(dimsA, dimsB))
- dynamic_broadcast_in_dim(dynamic_reshape(X, shape), shape) -> dynamic_reshape(X, shape)
- dynamic_broadcast_in_dim(X, _, _, [all_nonexpanding...]) -> convert(X)
- dynamic_broadcast_in_dim(X, shape_of(X)) -> X
- dynamic_gather(x, constant(slice_sizes)) -> gather(x, slice_sizes)
- dynamic_iota(shape, dim) ->
- dynamic_pad(X, low, high, interior) -> pad(X, low, high, interior)
- dynamic_reshape(dynamic_reshape(X, _), shape)) -> dynamic_reshape(X, shape)
- dynamic_reshape(op(dynamic_reshape(X, shape)), shape)
- dynamic_slice(X, begin, slice_sizes) -> slice(X, begin, slice_sizes)
- dynamic_update_slice(X, update, start_indices : zero)) -> update
- dynamic_update_slice(X, update : zero_extent)) -> X
- gather(X, cst_start_indices) -> slice(X, slice_start, slice_end)
- get_dimension_size(X, i) -> X.shape[i]
- get_tuple_element(tuple(X_0, X_1, ...), i) -> X_i
- imag(complex(R,I)) -> I
- iota(dim) : multi_rank
- iota(dim) : type -> constant(0) : type [if type[dim] == 1]
- max(cst, X) -> max(X, cst)
- minimum(cst, X) -> minimum(X, cst)
- multiply(cst, X) -> multiply(X, cst)
- multiply(X, 0i) -> 0i
- multiply(X, 1i) -> X
- op(X : zero_extent_tensor) -> constant([])
- or(cst, X) -> or(X, cst)
- or(X, 0) -> X
- or(X, 1) -> 1
- pad(empty_tensor, _) -> broadcast_in_dim(empty_tensor, _)
- real(complex(R,I)) -> X
- real_dynamic_slice(X, start, limit, strides)
- real_dynamic_slice(X, start, limit, strides)
- reduce[A](_, _, fn:return A) -> A...
- reduce(empty_0, empty_1, ...) -> [broadcast_in_dim(empty_i)...]
- reduce(in_1, in_2, _, _) -> reduce(in_1, _, _) [if unused(in_2)]
- reduce(X..., dims=[], add) -> X...
- reshape(reshape(X, _), [shape]) -> reshape(X, [shape])
- reshape(X, [X.shape]) -> X
- select(broadcast(not(p)), t, f) => select(broadcast(p), f, t)
- select(not(p), t, f) => select(p, f, t)
- shape_of(dynamic_reshape(X, shape)) -> shape
- slice(concat(X,Y,Z,...),...) -> concat(slice(X),slice(Y),slice(Z))
- slice(X, [A:A], [B:B], ...) -> X
- sort(X) -> sort(X, dim = N) [when dim can be inferred]
- sort(X,Y) -> sort(X) [if Y unused and unused in comparator]
- subtract(X, 0) -> X
- subtract(X, X) -> 0
- transpose(X, [iota...]) -> X
- transpose(X, [no_mem_layout_change...]) -> reshape(X)
- tuple(get_tuple_element(X, 0), get_tuple_element(X, 1), ...) -> X
- while -> while (loop invariants as implicit captures)
- xor(cst, X) -> xor(X, cst)
- (+more)

-fold-op-element-limit : Upper limit on how many elements may be folded by an op folder. This limit doesn't apply in certain special cases such as addition with 0, multiplication by 1, and some splat operations.

-assume-no-undeclared-side-effects : Allow dead code to be eliminated in some situations (e.g. dead while loops) under the assumption that ops are pure unless declared with explicit MLIR `MemoryEffects`. Notably, this means `func.call` ops will be assumed pure.
-fold-op-element-limit             : Upper limit on how many elements may be folded by an op folder. This limit doesn't apply in certain special cases such as addition with 0, multiplication by 1, and some splat operations.
-optimize-float                    : Allow float optimizations that, though mathematically equivalent, may result in slightly different quantization of floating-point values (e.g. `log(sqrt(x))` -> `0.5 * log(x)`). Float optimizations that can't affect numerical results are always enabled.