from tinygrad.uop.ops import UOp, PatternMatcher, UPat, Ops, graph_rewrite, _substitute, range_start from tinygrad.uop.symbolic import symbolic_flat, sym from tinygrad.helpers import partition from tinygrad.dtype import dtypes def flatten_range(r:UOp): off = range_start[r.op] rngs = r.src[off:] if not len(rngs): return None new_rngs = [x for x in UOp.sink(*rngs).toposort() if x.op is Ops.RANGE] return r.replace(src=r.src[:off]+tuple(new_rngs)) pm_flatten_range = PatternMatcher([ # real ranges only (UPat((Ops.REDUCE, Ops.STORE), name="r"), flatten_range), ]) def count_divmod(x:UOp): return len([u for u in x.toposort() if u.op in {Ops.IDIV, Ops.MOD}]) def simplify_merge_adjacent(u:UOp) -> UOp|None: i = range_start[u.op] while i < len(u.src)-1: r0, r1 = u.src[i], u.src[i+1] # check same type if r0.arg[-1] == r1.arg[-1]: s0, s1 = r0.src[0], r1.src[0] # do the merge new_range = r0.replace(src=(s0*s1,)) nidx = graph_rewrite(u, _substitute+symbolic_flat+pm_flatten_range, ctx={r0:new_range//s1, r1:new_range%s1}, name=f"check_merge_{r0.arg[0]}_{r1.arg[0]}") # check if it simplifies if count_divmod(nidx) <= count_divmod(u): u = nidx continue i += 1 return u pm_simplify_ranges = PatternMatcher([ (UPat((Ops.STORE, Ops.REDUCE), name="u"), simplify_merge_adjacent), ]) # **** reduce simplification **** def reduce_rangeless(red:UOp): # TODO: share code with reduce_unparented if red.arg not in {Ops.ADD, Ops.MAX}: return None if red.src[0].dtype != red.dtype: return None if any(x.op in {Ops.RANGE} for x in red.src[0].toposort()): return None ret = red.src[0] if red.arg is Ops.ADD: for r in red.src[1:]: ret = ret * r.src[0].cast(ret.dtype.scalar()).broadcast(ret.dtype.count) return ret def no_range(u:UOp) -> bool: return not any(x.op is Ops.RANGE for x in u.sparents) pm_reduce_collapse = PatternMatcher([ # lift x+y out of reduce on lt ((UPat.var("x")+UPat.var("y")).or_casted() < UPat.var("c"), lambda x,y,c: (x < (c.cast(y.dtype)-y)) if no_range(y) and no_range(c) else None), # lift x*y out of reduce ((UPat.var("x")*UPat.var("y")) < UPat.var("c"), lambda x,y,c: (x < ((c+y-1) // y)) if no_range(y) and no_range(c) and y.vmin > 0 else None), # lift x+y out of reduce on ne ((UPat.var("x")+UPat.var("y")).or_casted() != UPat.var("c"), lambda x,y,c: (x != (c.cast(y.dtype)-y)) if no_range(y) and no_range(c) else None), # fold the range ((UPat(Ops.RANGE, name="r") < UPat.var("cut")).where(0, UPat.cvar("val")).reduce(arg=Ops.ADD, allow_any_len=True), lambda r,cut,val: (r.src[0]-cut).maximum(0).minimum(r.src[0]).cast(val.dtype) * val), ((UPat(Ops.RANGE, name="r") < UPat.var("cut")).where(UPat.cvar("val"), 0).reduce(arg=Ops.ADD, allow_any_len=True), lambda r,cut,val: cut.maximum(0).minimum(r.src[0]).cast(val.dtype) * val), # REDUCE on ADD ((UPat.var("x")+UPat.var("y")).reduce(arg=Ops.ADD, allow_any_len=True, name="r"), lambda x,y,r: x.reduce(*r.src[1:], arg=Ops.ADD) + y.reduce(*r.src[1:],arg=Ops.ADD)), # MUL casted bool ((UPat.var("x") * UPat.var("gate", dtype=dtypes.bool).cast().or_broadcasted(name="b")), lambda x,gate,b=None: gate.broadcast(x.dtype.count).where(x, 0) if b is not None else gate.where(x, 0)), # WHERE on LOAD (works on max too) (UPat.var("gate").where(UPat(Ops.INDEX, src=(UPat.var("buf"), UPat.var("idx"))).load(), 0).reduce(arg=Ops.ADD, allow_any_len=True), lambda buf,idx,gate: buf.index(idx, gate).load()), (UPat.var("gate").where(0, UPat(Ops.INDEX, src=(UPat.var("buf"), UPat.var("idx"))).load()).reduce(arg=Ops.ADD, allow_any_len=True), lambda buf,idx,gate: buf.index(idx, gate.logical_not()).load()), # INDEX on RANGE / gated RANGE (UPat.var("buf").index(UPat.var("expr"), UPat.var("idx").eq(UPat(Ops.RANGE, name="r").or_casted())), lambda buf,r,idx,expr: buf.index(expr.substitute({r:idx.cast(r.dtype)}), (idx.cast(r.dtype) >= 0) & (idx.cast(r.dtype) < r.src[0]))), # AND on WHERE ((UPat.any(UPat(Ops.DEFINE_VAR, name="x"), UPat(Ops.DEFINE_VAR).gep(name="x")) & UPat.var("y")) \ .where(UPat.cvar("c"), 0).reduce(arg=Ops.ADD, allow_any_len=True, name="r"), lambda x,y,c,r: y.where(c, 0).reduce(*r.src[1:], arg=Ops.ADD)*x.cast(c.dtype)), # remove REDUCEs that no longer have a RANGE in the src (UPat(Ops.REDUCE, name="red"), reduce_rangeless), ])+sym def reduce_collapse(red:UOp): included, not_included = partition(red.parents, lambda x: any(y in x.sparents for y in red.src[1:])) if any(x.op in {Ops.STORE, Ops.REDUCE} for x in included): return None replaces: dict[UOp, UOp] = {} for u in included: for s in u.src: if s in not_included and s not in replaces and s.op not in {Ops.CONST, Ops.VCONST, Ops.DEFINE_GLOBAL, Ops.DEFINE_LOCAL, Ops.DEFINE_VAR}: replaces[s] = UOp(Ops.DEFINE_VAR, dtype=s.dtype, arg=(f'in{len(replaces)}', s.vmin, s.vmax)) collapse_fxn = red.substitute(replaces) sink = graph_rewrite(collapse_fxn, pm_reduce_collapse, name="reduce_collapse") if any(x.op is Ops.RANGE for x in sink.toposort()): return None return sink.substitute({v:k for k,v in replaces.items()}) def reduce_unparented(red:UOp): if red.arg not in {Ops.ADD, Ops.MAX, Ops.MUL}: return None reduce_parented, reduce_unparented = partition(red.src[1:], lambda x: x in red.src[0].sparents) if len(reduce_unparented) == 0: return None ret = red.replace(src=(red.src[0],)+tuple(reduce_parented)) if len(reduce_parented) or red.dtype != red.src[0].dtype else red.src[0] if red.arg is Ops.ADD: for r in reduce_unparented: ret = ret * r.src[0].cast(ret.dtype.scalar()).broadcast(ret.dtype.count) if red.arg is Ops.MUL: for r in reduce_unparented: ret = ret ** r.src[0].cast(ret.dtype.scalar()).broadcast(ret.dtype.count) return ret pm_reduce_simplify = PatternMatcher([ # remove any ranges from a REDUCE that aren't referenced in the reduce source (UPat(Ops.REDUCE, name="red"), reduce_unparented), # remove REDUCE without loads (generic arange opt / indexing). TODO: support multi range (UPat(Ops.REDUCE, src=(UPat(), UPat()), name="red"), reduce_collapse), ])