Release 260111
This commit is contained in:
Comma Device
615
tinygrad/schedule/rangeify.py
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615
tinygrad/schedule/rangeify.py
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from typing import Any, cast
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import functools, operator
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from dataclasses import dataclass, field
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from tinygrad.dtype import dtypes, PtrDType, ImageDType, AddrSpace
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from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, RewriteNotReady, _substitute, ssimplify, graph_rewrite_map
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from tinygrad.uop.symbolic import sym, symbolic_simple
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from tinygrad.helpers import argsort, prod, all_same, pluralize, getenv, RANGEIFY, Context, flatten, dedup
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from tinygrad.schedule.multi import multi_pm
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from tinygrad.schedule.kernelize import Kernel
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from tinygrad.uop.ops import track_rewrites, graph_rewrite, identity_element, sint, AxisType
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# *****************
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# 0. do some cleanup rewrites, mostly copied from the old stuff
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double_reshape = PatternMatcher([
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# RESHAPE on RESHAPE is the second reshape
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(UPat(Ops.RESHAPE, src=(UPat(Ops.RESHAPE),), name="x"), lambda x: x.replace(src=(x.src[0].src[0],))),
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])
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earliest_rewrites = double_reshape+PatternMatcher([
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# non shape changing RESHAPE is NOOP
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#(UPat(Ops.RESHAPE, name="x"), lambda x: x.src[0] if x.src[0].shape == x.arg else None),
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# DETACH and CONTIGUOUS_BACKWARD are NOOPs here, so is FUSE
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#(UPat((Ops.DETACH, Ops.CONTIGUOUS_BACKWARD, Ops.FUSE), name="x"), lambda x: x.src[0].f(Ops.NOOP, tag=x.tag)),
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# just removing it works...
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(UPat((Ops.DETACH, Ops.CONTIGUOUS_BACKWARD, Ops.FUSE), name="x"), lambda x: x.src[0]),
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# preserve tags?
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# reduce of size 0 is the identity element
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(UPat(Ops.REDUCE_AXIS, name="reduce", src=(UPat.var("x"),)),
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lambda reduce,x: reduce.const_like(identity_element(reduce.arg[0], reduce.dtype)) if x.size == 0 and reduce.size != 0 else None),
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# COPY and source size need to match
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# TODO: expand after copy creates issues with tagging
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(UPat(Ops.COPY, src=(UPat(GroupOp.Movement, name="r"), UPat(name="d")), name="c"),
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lambda c,r,d: c.replace(src=(r.contiguous(), d)) if r.size != r.base.size else None),
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# assign only to buffer
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(UPat(Ops.ASSIGN, src=(UPat(GroupOp.All-{Ops.BUFFER}, name="target"), UPat(name="x")), name="assign"),
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lambda x,target,assign: x.f(Ops.NOOP, tag=assign.tag) if target.base.op is not Ops.BUFFER else None),
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# handle disk
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# TODO: this doesn't need to use st.views
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(UPat.var("x").f((Ops.BITCAST, Ops.CONTIGUOUS), name="t"),
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lambda x,t: UOp(Ops.BUFFER_VIEW, t.dtype, (x.base,), (t.size, x.st.views[0].offset), tag=t.tag).reshape(t.shape) if isinstance(x.device, str) \
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and x.device.startswith("DISK") else None),
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# contiguous/buffer/copy/assign is already contiguous
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#(UPat(Ops.CONTIGUOUS, name="root", src=(UPat((Ops.CONTIGUOUS, Ops.BUFFER, Ops.COPY, Ops.ASSIGN)),)), lambda root: root.src[0]),
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])
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# *****************
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# 1. add realize where we have to
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ALWAYS_CONTIGUOUS: set[Ops] = {Ops.CONTIGUOUS, Ops.ASSIGN, Ops.COPY, Ops.BUFFER, Ops.BUFFER_VIEW,
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Ops.CONST, Ops.BIND, Ops.DEVICE, Ops.MSELECT, Ops.MSTACK, Ops.DEFINE_GLOBAL,
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Ops.DEFINE_LOCAL, Ops.DEFINE_REG, Ops.LOAD}
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def realize(ctx:dict[UOp, None], tr:UOp) -> None: ctx[tr] = None
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def realize_parents(ctx:dict[UOp, None], rb:UOp) -> None:
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for s in rb.src:
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if s.base.op not in ALWAYS_CONTIGUOUS: ctx[s] = None
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def realize_assign(ctx:dict[UOp, None], a:UOp) -> None:
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if a.src[1].op not in ALWAYS_CONTIGUOUS: ctx[a.src[1]] = None
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do_realize = PatternMatcher([
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# always realize SINK parents
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(UPat(Ops.SINK, name="s"), lambda ctx,s: ctx.update((x.base, None) for x in s.src if x.base.op not in ALWAYS_CONTIGUOUS)),
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# always realize ASSIGN/COPY/BUFFER_VIEW/CONTIGUOUS
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(UPat({Ops.ASSIGN, Ops.COPY, Ops.BUFFER_VIEW, Ops.CONTIGUOUS}, name="tr"), realize),
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# realize parents of COPY, MSELECT, MSTACK
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(UPat((Ops.COPY, Ops.MSELECT, Ops.MSTACK), name="rb"), realize_parents),
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# realize input to assign (might be optimized out)
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(UPat(Ops.ASSIGN, name="a"), realize_assign),
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])
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class WrappedContig:
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def __init__(self, x): self.x = x
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def __repr__(self): return f"C({self.x})"
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add_contiguous = PatternMatcher([
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(UPat(GroupOp.All, name="x"),
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lambda ctx,x: x.replace(tag=WrappedContig(x.tag)).realize() if x in ctx and not isinstance(x.tag, WrappedContig) else None),
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])
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remove_contig_tags = PatternMatcher([(UPat(GroupOp.All, name="x"), lambda x: x.replace(tag=x.tag.x) if isinstance(x.tag, WrappedContig) else None)])
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# *****************
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# 2. mark all children
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@dataclass
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class ChildrenContext: children: dict[UOp, list[UOp]]|None = None
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def extract_children(ctx:ChildrenContext, x:UOp):
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if ctx.children is not None: return
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children_map = x.get_children_map()
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ctx.children = {}
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for k,v in children_map.items():
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non_sink_children = [u for u in v if u.op is not Ops.SINK]
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if len(non_sink_children) <= 1: continue
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# NOTE: this gate shouldn't be here
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if any(x.op is Ops.REDUCE_AXIS for x in k.toposort()) and any(x.op in {Ops.BUFFER, Ops.CONTIGUOUS} for x in k.toposort()):
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ctx.children[k] = non_sink_children
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def mark_children(ctx:ChildrenContext, x:UOp):
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assert ctx.children is not None
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new_srcs = [(UOp(Ops.CHILD, s.dtype, src=(UOp(Ops.CHILDREN, s.dtype, (s,), arg=len(ctx.children[s])),),
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arg=(ctx.children[s].index(x), len(ctx.children[s]))) if s in ctx.children else s) for s in x.src]
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return x.replace(src=tuple(new_srcs))
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pm_children = PatternMatcher([
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(UPat(Ops.SINK, name="x"), extract_children),
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(UPat(GroupOp.All-{Ops.CHILD, Ops.CHILDREN, Ops.SINK}, name="x"), mark_children),
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])
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# *****************
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# 3a. rangeify (movement)
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@dataclass
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class RangeifyContext:
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# block on parent until all children have been seen
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seen_children: dict[UOp, dict[int, UOp]] = field(default_factory=dict)
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seen_child: dict[UOp, Any] = field(default_factory=dict)
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progress: int = 0
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# create ranges
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range_idx: int = 0
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def new_range(self, s:sint, axistype:AxisType=AxisType.LOOP):
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ret = UOp.range(s, self.range_idx, axistype)
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self.range_idx += 1
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return ret
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def map_reshape(idx:UOp, r:UOp):
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acc = 1
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to_sum = []
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for s,src in list(zip(idx.shape, idx.src[1:]))[::-1]:
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to_sum.append(acc*src)
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acc *= s
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mish = sum(to_sum, start=UOp.const(dtypes.index, 0))
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ret:list[UOp] = []
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for s in r.src[0].shape[::-1]:
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ret.append(mish % s) # NOTE: simplify will turn this to CONST
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mish //= s
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tret = ret[0].sink(*ret[1:]).simplify().src[::-1] if len(ret) else ()
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return r.src[0].index(*tret, dtype=idx.dtype, arg=idx.arg)
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def map_pad(idx:UOp, r:UOp):
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ret = list(idx.src[1:])
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bigwhere = UOp.const(dtypes.bool, True)
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for i,(sh,(s,e)) in enumerate(zip(r.shape, r.arg)):
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if s == 0 and e == 0: continue
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where = UOp.const(dtypes.bool, True)
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if resolve(e > 0): where = where & (ret[i] < (sh-e))
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if resolve(s > 0): where = where & (ret[i] >= s)
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bigwhere = bigwhere & where
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with Context(TRACK_MATCH_STATS=0):
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ret[i] = graph_rewrite(where.where(ret[i]-s, UOp.invalid()), sym)
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# PAD is with 0
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return bigwhere.simplify().where(r.src[0].index(*ret, dtype=idx.dtype, arg=idx.arg), UOp.const(r.dtype, 0))
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def map_expand(r:UOp, idx:UOp):
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new_rngs = []
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ending_ranges = []
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non_ending_ranges = []
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for a,x,y in zip(idx.src[1:], r.src[0].shape, r.shape):
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axis_to_range = [u for u in a.toposort() if u.op is Ops.RANGE]
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if resolve(x==y, False):
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non_ending_ranges.extend(axis_to_range)
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new_rngs.append(a)
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else:
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ending_ranges.extend(axis_to_range)
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new_rngs.append(a.const_like(0))
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ending_ranges = [x.arg for x in ending_ranges if x not in non_ending_ranges]
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if idx.arg is not None: ending_ranges.append(idx.arg)
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return r.src[0].index(*new_rngs, arg=min(ending_ranges) if ending_ranges else None)
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pm_mops = PatternMatcher([
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# this is like the definitions of these
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(UPat(Ops.SHRINK, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"),
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lambda r,idx: r.src[0].index(*[a+ss if resolve(ss != 0) else a for a,(ss,_) in zip(idx.src[1:], r.arg)], dtype=idx.dtype, arg=idx.arg)),
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(UPat(Ops.PERMUTE, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"),
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lambda r,idx: r.src[0].index(*[idx.src[1+p] for p in argsort(idx.src[0].arg)], dtype=idx.dtype, arg=idx.arg)),
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(UPat(Ops.FLIP, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"),
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lambda r,idx: r.src[0].index(*[((s-1)-a) if f else a for a,s,f in zip(idx.src[1:], r.shape, r.arg)], dtype=idx.dtype, arg=idx.arg)),
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# expand needs to end ranges
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(UPat(Ops.EXPAND, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"), map_expand),
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# reshape does a lot of symbolic stuff
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(UPat(Ops.RESHAPE, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"), map_reshape),
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# pad adds min and max
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(UPat(Ops.PAD, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"), map_pad),
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])
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# *****************
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# 3b. rangeify (ops)
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# bufferization can happen in three ways
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# 1. there's an explicit REALIZE in the graph
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# 2. the ranges from the children don't match and we have to create a buffer (only on children)
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# 3. might_end_axis triggers because we should be closing a loop to save compute
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@dataclass(frozen=True)
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class BufferizeOpts:
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# on AddrSpace.LOCAL, device is the id
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device: str|tuple[str, ...]|int|None
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addrspace: AddrSpace = AddrSpace.GLOBAL
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def map_partial_realize(ctx:RangeifyContext, x:UOp, idx:UOp):
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if x.arg is None: return None # map_contiguous can handle this
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# NOTE: all partial contiguous can safely be replaced by full contiguous. we should be able to match old functionality like this
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if not (RANGEIFY > 1): return idx.replace(src=(x.replace(arg=None),)+idx.src[1:])
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ranges = []
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new_ranges = []
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passthrough_idx = []
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for i,s in enumerate(x.shape):
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if i not in x.arg:
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ranges.append(idx.src[1+i])
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continue
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passthrough_idx.append(idx.src[1+i])
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ranges.append(ctx.new_range(s))
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new_ranges.append(ranges[-1])
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# TODO: this should be able to be global or local
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ret = x.src[0].index(*ranges).bufferize(*[x for x in new_ranges if x.op is not Ops.CONST],
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arg=BufferizeOpts(device=None, addrspace=AddrSpace.LOCAL))
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return ret.index(*passthrough_idx)
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def map_realize(ctx:RangeifyContext, x:UOp):
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if x.arg is not None: return None
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ranges = [ctx.new_range(s) for s in x.shape]
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return x.src[0].index(*ranges).bufferize(*x.src[1:], *ranges, arg=BufferizeOpts(device=x.device), tag=x.src[0].tag)
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def map_reduce(ctx:RangeifyContext, idx:UOp, red:UOp):
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rngs = list(idx.src[1:])
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new_ranges = []
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for i,s in enumerate(red.src[0].shape):
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if i in red.arg[1]:
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rngs[i] = ctx.new_range(s, axistype=AxisType.REDUCE)
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new_ranges.append(rngs[i])
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return UOp(Ops.REDUCE, red.dtype, src=(red.src[0].index(*rngs),)+tuple(new_ranges), arg=red.arg[0], tag=red.tag)
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def index_child(ctx:RangeifyContext, c:UOp, x:UOp, idx:UOp):
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if c not in ctx.seen_children: ctx.seen_children[c] = {}
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# wait here until we have seen all the children
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if len(ctx.seen_children[c]) != x.arg[1]:
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ctx.progress += 1
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if ctx.progress > 10000: raise RuntimeError("children not making progress")
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# NOTE: we mark this here
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ctx.seen_children[c][x.arg[0]] = idx
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raise RewriteNotReady
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ctx.progress = 0
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if c not in ctx.seen_child:
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all_rngs = list(zip(*[ch.src[1:] for ch in ctx.seen_children[c].values()]))
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out_rngs = []
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end_ranges = []
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idx_ranges = []
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# NOTE: locals aren't working, so we only fully bufferize here (unless RANGEIFY > 1)
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all_all_same = all(all_same(r) for r in all_rngs)
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for i,valid_rngs in enumerate(all_rngs):
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rngs, valids = zip(*[(r.get_idx(), r.get_valid()) for r in valid_rngs])
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# we compare the ranges without their valids
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if all_same(rngs) and (all_all_same or RANGEIFY > 1):
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# the new valid is the OR of all the children valids
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minimum_valid = functools.reduce(operator.or_, valids, UOp.const(dtypes.bool, False))
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out_rngs.append(minimum_valid.where(rngs[0], UOp.invalid()).simplify())
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else:
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out_rngs.append(ctx.new_range(c.shape[i]))
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end_ranges.append(out_rngs[-1])
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idx_ranges.append(i)
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ctx.seen_child[c] = (out_rngs, idx_ranges, end_ranges)
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else:
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out_rngs, idx_ranges, end_ranges = ctx.seen_child[c]
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for i,nr in zip(idx_ranges, end_ranges): out_rngs[i] = nr
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# index based on the shared ranges
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ret = c.index(*out_rngs)
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# if all ranges aren't the same between children, we have to bufferize
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if len(idx_ranges) > 0:
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if len(idx_ranges) == len(out_rngs):
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# this is a global bufferize
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ret = ret.bufferize(*end_ranges, arg=BufferizeOpts(device=x.device))
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else:
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assert RANGEIFY > 1, "this isn't supported with RANGEIFY=1"
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ret = ret.bufferize(*end_ranges, arg=BufferizeOpts(device=None, addrspace=AddrSpace.LOCAL))
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ret = ret.index(*[idx.src[1+i] for i in idx_ranges])
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return ret
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def children_gate(ctx:RangeifyContext, idx:UOp, c:UOp):
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if len(ctx.seen_children[c]) != c.arg: raise RuntimeError("all children should have been seen by now")
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return idx.replace(src=(idx.src[0].src[0],)+idx.src[1:])
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def might_end_axis(idx:UOp):
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if idx.arg is None: return None
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# TODO: write a proper cost function here
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if all(x.op not in {Ops.BUFFER, Ops.REALIZE, Ops.BUFFERIZE} for x in idx.toposort()): return None
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if all(x.op not in {Ops.REDUCE_AXIS} for x in idx.toposort()): return None
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to_end_axis = []
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for i,a in enumerate(idx.src[1:]):
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if any(x.arg > idx.arg for x in a.toposort() if x.op is Ops.RANGE):
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to_end_axis.append(i)
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if to_end_axis: return idx.replace(src=(idx.src[0].realize(arg=tuple(to_end_axis)),)+idx.src[1:], arg=None)
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return idx.replace(arg=None)
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def unprocessed_index(x:UOp): raise RuntimeError(f"unprocessed index on {x.src[0].op}")
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pm_rangeify = pm_mops+PatternMatcher([
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# sink contigs to kick it off
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(UPat(Ops.REALIZE, src=(UPat(),), name="x", allow_any_len=True), map_realize),
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# if there's an INDEX it can support partial contig
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(UPat(Ops.INDEX, src=(UPat(Ops.REALIZE, src=(UPat(),), name="x"),), allow_any_len=True, name="idx"), map_partial_realize),
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# if there are new ended children, tag the SINK
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(UPat(Ops.INDEX, src=(UPat(Ops.CHILD, src=(UPat(name="c"), ), name="x"),), allow_any_len=True, name="idx"), index_child),
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(UPat(Ops.INDEX, src=(UPat(Ops.CHILDREN, name="c"),), allow_any_len=True, name="idx"), children_gate),
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# if we come across this, remove it. it was a CHILD unused in an INDEX
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(UPat(Ops.CHILD, src=(UPat(Ops.CHILDREN, src=(UPat.var("x"),)),)), lambda x: x),
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# CONST (or DEFINE_VAR) can't have axes. remove INDEX when we get here
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(UPat(Ops.INDEX, src=(UPat((Ops.CONST, Ops.DEFINE_VAR), name="c"),)), lambda c: c),
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# handle arg on any op with weight. old endrange stuff
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(UPat(Ops.INDEX, src=(UPat(GroupOp.Elementwise.union({Ops.REDUCE_AXIS})),), allow_any_len=True, name="idx"), might_end_axis),
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# handle size 0
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(UPat(Ops.INDEX, name="x"), lambda x: x.replace(src=(x.const_like(0),)+x.src[1:]) if x.st is not None and x.size == 0 else None),
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# handle assign
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(UPat(Ops.INDEX, src=(UPat(Ops.ASSIGN, name="assign"),), allow_any_len=True, name="x"),
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||||
lambda x,assign: assign.replace(src=tuple([s.index(*x.src[1:]) for s in assign.src])+(assign.src[0],))),
|
||||
|
||||
# move MAP through elementwise ALU / reduce. these are the items with cost
|
||||
(UPat(Ops.INDEX, src=(UPat(GroupOp.Elementwise.union(
|
||||
{Ops.STORE, Ops.COPY, Ops.BUFFER_VIEW, Ops.DEVICE, Ops.BIND, Ops.CONTIGUOUS, Ops.NOOP})),), allow_any_len=True, name="x"),
|
||||
lambda x: x.src[0].replace(src=tuple([s.index(*x.src[1:]) for s in x.src[0].src]))),
|
||||
(UPat(Ops.INDEX, src=(UPat(Ops.REDUCE_AXIS, name="red"),), allow_any_len=True, name="idx"), map_reduce),
|
||||
|
||||
# assert if there's any index we didn't process
|
||||
(UPat(GroupOp.All-{Ops.REALIZE, Ops.BUFFERIZE}).f(Ops.INDEX, name="x"), unprocessed_index),
|
||||
])
|
||||
|
||||
# *****************
|
||||
# 3.5 cleanups
|
||||
|
||||
# you don't know in the first pass if axes are going to die, this happens if there's an EXPAND to the left
|
||||
def cleanup_dead_axes(b:UOp):
|
||||
new_rng = []
|
||||
hit = False
|
||||
reshape: list[sint] = []
|
||||
for s,rng in zip(b.shape, b.src[1:]):
|
||||
if rng not in b.src[0].sparents and rng.op is Ops.RANGE:
|
||||
reshape.append(1)
|
||||
hit = True
|
||||
else:
|
||||
reshape.append(s)
|
||||
new_rng.append(rng)
|
||||
if hit:
|
||||
return b.replace(src=b.src[0:1]+tuple(new_rng)).reshape(tuple(reshape)).expand(b.shape)
|
||||
|
||||
# if a buffer is being stored just for permutes or something, remove it
|
||||
# we want to reexpress the indexes of idx2 in terms of the implied b1
|
||||
def remove_bufferize(src:UOp, buf:UOp, idx:UOp):
|
||||
# see if we can't do it, should this ever hit?
|
||||
assert len(buf.src) == len(idx.src), "index on wrong bufferize"
|
||||
assert all(x.op is Ops.RANGE for x in buf.src[1:])
|
||||
|
||||
# if it's user contiguous, we never remove it
|
||||
if src.op is Ops.CONTIGUOUS: return None
|
||||
|
||||
# here is where we compute the cost
|
||||
# for now just no REDUCE, COPY, or ASSIGN
|
||||
ran = src.toposort(gate=lambda x: x.op not in {Ops.INDEX})
|
||||
# we don't want to bufferize threefry, also causes problems because not all platforms support long
|
||||
if any(x.op in {Ops.REDUCE, Ops.COPY, Ops.BUFFER_VIEW, Ops.ASSIGN} for x in ran) and src.op is not Ops.THREEFRY: return None
|
||||
|
||||
# simple, matching old behavior
|
||||
#if src.op is not Ops.INDEX: return None
|
||||
|
||||
# this is the ranges replaced
|
||||
return src.substitute(dict(zip(buf.src[1:], idx.src[1:])))
|
||||
|
||||
def pre_bufferize(b:UOp, x:UOp, copy:UOp):
|
||||
nb = b.replace(src=(b.src[0].contiguous(),)+b.src[1:])
|
||||
return copy.replace(src=(x.replace(src=(nb,)+x.src[1:]), copy.src[1]))
|
||||
|
||||
pm_cleanups = double_reshape+pm_mops+PatternMatcher([
|
||||
#(UPat(Ops.BUFFERIZE, name="b"), cleanup_dead_axes),
|
||||
# remove noop buffers. if we look at the next index we can remove even more of these
|
||||
# NOTE: this is mostly the same case as below, but if there's no INDEX this gets more
|
||||
(UPat(Ops.INDEX, name="idx").f(Ops.BUFFERIZE, allow_any_len=True, name="b2"),
|
||||
lambda idx,b2: idx.src[0].replace(tag=nt if len(nt:=(idx.src[0].tag or ()) + (b2.tag or ())) else None) if idx.src[1:] == b2.src[1:] \
|
||||
and idx.src[0].op is not Ops.BUFFER_VIEW else None),
|
||||
# remove reindexing with cost function
|
||||
(UPat.var("src").f(Ops.BUFFERIZE, allow_any_len=True, name="buf").f(Ops.INDEX, allow_any_len=True, name="idx"), remove_bufferize),
|
||||
# no buffers for const
|
||||
(UPat(Ops.CONST, name='c').f(Ops.BUFFERIZE, allow_any_len=True, name="b"),
|
||||
lambda c,b: c.reshape((1,)*len(b.shape)).expand(b.shape).replace(tag=b.tag)),
|
||||
# if any CONST with DEVICE make it here (symbolic/copy issue), remove it
|
||||
#(UPat(Ops.DEVICE).f(Ops.CONST, name="c"), lambda c: c.replace(src=())),
|
||||
# copy on CONST is CONST
|
||||
(UPat(Ops.COPY, src=(UPat.cvar("x"), UPat()), name="copy"), lambda copy,x: copy.const_like(x.arg)),
|
||||
(UPat(Ops.COPY, src=(UPat(GroupOp.All-{Ops.CONTIGUOUS, Ops.COPY}).f(Ops.BUFFERIZE, allow_any_len=True, name="b")
|
||||
.f(Ops.INDEX, allow_any_len=True, name="x"), UPat()), name="copy"), pre_bufferize),
|
||||
])
|
||||
|
||||
# *****************
|
||||
# 4. put in buffers for bufferize
|
||||
# TODO: should BUFFERIZE look a lot more like STORE
|
||||
# BUFFERIZE has device in arg
|
||||
# BUFFERIZE doesn't have indexing, that's implied by the ranges it closes
|
||||
# BUFFERIZE returns the BUFFER ready for INDEXing (doing this will make splitting a lot easier)
|
||||
# NOTE: this has been fixed up a bit
|
||||
|
||||
def bufferize_to_store(x:UOp):
|
||||
rngs = x.src[1:]
|
||||
shape = tuple([int(r.vmax+1) for r in rngs])
|
||||
sym_shape = tuple([ssimplify(r.src[0]) for r in rngs])
|
||||
size = prod(shape)
|
||||
assert size > 0, f"no zero sized buffers {shape}"
|
||||
|
||||
sdtype = x.dtype.ptr(size=size, addrspace=x.arg.addrspace)
|
||||
if x.src[0].op is Ops.ASSIGN:
|
||||
assign_target, assign_src, assign_mops = x.src[0].src
|
||||
assert assign_target.op is Ops.INDEX
|
||||
# in assign, this is the buffer size, not the bufferize size
|
||||
# TODO: assign_mops here
|
||||
ret = assign_target.replace(dtype=sdtype).store(assign_src, *rngs, dtype=x.dtype)
|
||||
mops = []
|
||||
walk = assign_mops
|
||||
while walk is not assign_mops.base:
|
||||
mops.append((walk.op, walk.arg))
|
||||
walk = walk.src[0]
|
||||
for m in mops[::-1]: ret = ret._mop(*m)
|
||||
return ret.forced_reshape(shape).replace(tag=x.tag)
|
||||
|
||||
# NOTE: the DEFINE_LOCAL needs to be disambiguated here
|
||||
if sdtype.addrspace == AddrSpace.GLOBAL:
|
||||
buf = UOp.new_buffer(x.arg.device, size, x.dtype)
|
||||
ret = buf.reshape(shape).index(*rngs, dtype=sdtype).store(x.src[0], *rngs, dtype=x.dtype)
|
||||
ret = ret.forced_reshape(shape)
|
||||
# TODO: is this right? what if it's offset
|
||||
if shape is not sym_shape: ret = ret.shrink(tuple([(0,x) for x in sym_shape]))
|
||||
return ret.replace(tag=x.tag)
|
||||
|
||||
# handle locals
|
||||
tag = x.arg.device
|
||||
if tag is None: tag = UOp.unique().arg # TODO: hack
|
||||
buf = UOp(Ops.DEFINE_LOCAL, sdtype, arg=tag)
|
||||
# store has the other dtype here
|
||||
# TODO: how is this unified?
|
||||
return buf.reshape(shape).index(*rngs, dtype=sdtype).store(x.src[0], *rngs, dtype=sdtype).forced_reshape(shape, dtype=x.dtype)
|
||||
|
||||
pm_add_buffers = pm_mops+PatternMatcher([
|
||||
(UPat(Ops.BUFFERIZE, name="x"), bufferize_to_store),
|
||||
|
||||
# move RESHAPEs through MSELECT/MSTACK
|
||||
(UPat((Ops.MSELECT, Ops.MSTACK), src=UPat(Ops.RESHAPE), name="m"),
|
||||
lambda m: m.replace(src=tuple([x.src[0] for x in m.src])).reshape(m.src[0].arg)),
|
||||
])
|
||||
|
||||
# *****************
|
||||
# 5. split into kernels
|
||||
|
||||
@dataclass
|
||||
class LocalAddBufferContext:
|
||||
dg:int = 0
|
||||
map:dict = field(default_factory=dict)
|
||||
vars:dict = field(default_factory=dict)
|
||||
range:int = 0
|
||||
|
||||
def debuf(ctx:LocalAddBufferContext, buf:UOp):
|
||||
ret = UOp(Ops.DEFINE_GLOBAL, buf.dtype.ptr(buf.arg), arg=ctx.dg)
|
||||
if buf not in ctx.map: ctx.map[buf] = buf
|
||||
ctx.dg += 1
|
||||
return ret
|
||||
|
||||
def unbind_kernel(ctx:LocalAddBufferContext, b:UOp):
|
||||
ctx.vars[b] = None
|
||||
return b.src[0]
|
||||
|
||||
def handle_assign(ctx:LocalAddBufferContext, assign:UOp):
|
||||
buf = assign.as_buf()
|
||||
# HACK to put the buffer in the MAP instead of MSTACK/MSELECT
|
||||
if buf.op in {Ops.MSTACK, Ops.MSELECT}: buf = buf.src[0]
|
||||
assert buf not in ctx.map
|
||||
ctx.map[buf] = assign
|
||||
return buf
|
||||
|
||||
def renumber_range(ctx:LocalAddBufferContext, r:UOp):
|
||||
if r.tag is not None: return None
|
||||
ret = r.replace(arg=(ctx.range,)+r.arg[1:], tag=())
|
||||
ctx.range += 1
|
||||
return ret
|
||||
|
||||
to_define_global = PatternMatcher([
|
||||
(UPat(Ops.BUFFER, name="buf"), debuf),
|
||||
(UPat(Ops.BIND, name="b"), unbind_kernel),
|
||||
(UPat((Ops.ASSIGN, Ops.MSTACK, Ops.MSELECT), name="assign"), handle_assign),
|
||||
|
||||
# HACK in case any CONSTs were replaced
|
||||
# this is only needed if you are using symbolic
|
||||
(UPat((Ops.CONST, Ops.DEFINE_VAR), name="c"), lambda c: c.replace(src=()) if len(c.src) else None),
|
||||
|
||||
# renumber the ranges starting with 0 so that kernel deduping works
|
||||
(UPat(Ops.RANGE, name="r"), renumber_range),
|
||||
])
|
||||
|
||||
rangeify_codegen = PatternMatcher([
|
||||
# no NOOP in the kernel graph
|
||||
# TODO: this can be moved into codegen?
|
||||
(UPat((Ops.NOOP, Ops.CONTIGUOUS), name="x"), lambda x: x.src[0]),
|
||||
|
||||
# strip the arg from store
|
||||
(UPat(Ops.STORE, name="x"), lambda x: x.replace(arg=None) if x.arg is not None else None),
|
||||
|
||||
# add loads to non ptr indexes
|
||||
# TODO: this can be moved into codegen?
|
||||
(UPat((Ops.DEFINE_GLOBAL, Ops.STORE), name="dg").f(Ops.INDEX, name="idx", allow_any_len=True),
|
||||
lambda dg,idx: None if isinstance(idx.dtype, (PtrDType, ImageDType)) else idx.replace(dtype=dg.dtype, arg=None).load()),
|
||||
|
||||
# TODO: this can be moved into codegen
|
||||
(UPat(Ops.STORE, name="store").f(Ops.INDEX, allow_any_len=True, name="idx").f(Ops.LOAD),
|
||||
lambda store,idx: idx.replace(src=(store.as_buf(),)+idx.src[1:]).load(store if idx.dtype.addrspace != AddrSpace.LOCAL else store.barrier())),
|
||||
|
||||
# TODO: hack for group for reduce
|
||||
(UPat(Ops.IF, src=(UPat.var("gate"), UPat(Ops.LOAD, src=(UPat.var("src"), UPat.var("barrier"))),)),
|
||||
lambda src, barrier, gate: src.load(UOp(Ops.IF, src=(gate, barrier)))),
|
||||
])
|
||||
|
||||
def split_store(ctx:list[UOp], x:UOp):
|
||||
if len(x.ranges): return None
|
||||
if x.src[0].ptrdtype.addrspace is AddrSpace.LOCAL: return None
|
||||
|
||||
# local kernel rewrite
|
||||
lctx = LocalAddBufferContext()
|
||||
ret = graph_rewrite(x, to_define_global+rangeify_codegen, ctx=lctx, name="kernel split", bottom_up=True)
|
||||
|
||||
# gather the metadata
|
||||
metadatas = [ctx[y].metadata for x in ret.sparents if x.tag is not None for y in x.tag]
|
||||
|
||||
# NOTE: the hack for COPY is here
|
||||
ret = ret.sink() if ret.src[1].op not in {Ops.COPY, Ops.BUFFER_VIEW} else ret.src[1]
|
||||
kernel_arg = Kernel(ret,tuple(dedup(flatten([x for x in metadatas if x is not None]))))
|
||||
kernel = UOp(Ops.KERNEL, src=tuple(lctx.map.values())+tuple(lctx.vars.keys()), arg=kernel_arg)
|
||||
return x.as_buf().assign(kernel)
|
||||
|
||||
split_kernels = PatternMatcher([
|
||||
(UPat(Ops.STORE, name="x"), split_store),
|
||||
])
|
||||
|
||||
def tag_uop(ctx:list[UOp], x:UOp):
|
||||
if x.tag is not None: return None
|
||||
ctx.append(x)
|
||||
return x.replace(tag=(len(ctx)-1,))
|
||||
add_tags = PatternMatcher([
|
||||
# don't tag BUFFERs, they are global
|
||||
(UPat(GroupOp.All-{Ops.BUFFER, Ops.CONST, Ops.DEVICE, Ops.UNIQUE, Ops.DEFINE_VAR, Ops.BIND}.union(GroupOp.Movement), name="x"), tag_uop),
|
||||
])
|
||||
|
||||
@track_rewrites(lambda _,ret: f"Schedule {pluralize('Kernel', len([u for u in UOp.sink(*ret.values()).toposort() if u.op is Ops.KERNEL]))}", True)
|
||||
def get_rangeify_map(sink:UOp) -> dict[UOp, UOp]:
|
||||
uop_list: list[UOp] = []
|
||||
tsink = graph_rewrite(sink, add_tags, ctx=uop_list, bottom_up=True, name="number the uops")
|
||||
|
||||
# HACKS: handle multi with graph_rewrite_map in order to not have to add all the tag logic to multi
|
||||
msink = graph_rewrite_map(tsink, multi_pm, name="multi")
|
||||
tsink = msink[tsink].substitute({v:v.rtag(k.tag) for k,v in msink.items() if v.tag is None and k.tag is not None})
|
||||
|
||||
tsink = graph_rewrite(tsink, earliest_rewrites, name="earliest rewrites")
|
||||
realize_map: dict[UOp, UOp] = {}
|
||||
graph_rewrite(tsink, do_realize, ctx=realize_map, name="Input Graph")
|
||||
# NOTE: we don't use contiguous here, contiguous is a user op
|
||||
tsink = graph_rewrite(tsink, add_contiguous, ctx=realize_map, bottom_up=True, name="add realize")
|
||||
tsink = graph_rewrite(tsink, remove_contig_tags, name="remove contiguous tags")
|
||||
tsink = graph_rewrite(tsink, pm_children, ctx=ChildrenContext(), bottom_up=True, name="get children")
|
||||
|
||||
# rangeify
|
||||
tsink = graph_rewrite(tsink, pm_rangeify, ctx=RangeifyContext(), bottom_up=True, name="rangeify")
|
||||
# NOTE: sym (vs symbolic_simple) breaks things here because ranges with len 1 aren't handled right
|
||||
tsink = graph_rewrite(tsink, symbolic_simple, name="symbolic") # this supports const folding
|
||||
tsink = graph_rewrite(tsink, pm_cleanups, bottom_up=True, name="remove costly buffers")
|
||||
|
||||
# rebuild the sink with all the BUFFERIZEs with tags, this is what's ending up in the tensor graph
|
||||
# if it's not tagged by here, it's out
|
||||
tsink = UOp.sink(*[x for x in tsink.parents if (x.op is Ops.BUFFERIZE or x.base.op in {Ops.CONST}) and x.tag is not None])
|
||||
|
||||
if getenv("VIZ"): graph_rewrite(tsink, PatternMatcher([]), name="View Tagged Rangeify")
|
||||
|
||||
# bufferize -> store
|
||||
tsink = graph_rewrite(tsink, pm_add_buffers, bottom_up=True, name="bufferize to store")
|
||||
tsink = graph_rewrite(tsink, split_kernels, ctx=uop_list, name="split kernels")
|
||||
|
||||
# if a kernel depends on a buffer, and that buffer is later assigned to, make the assign depend on the kernel's assign
|
||||
kernel_assign: dict[UOp, UOp] = {}
|
||||
assign_rep: dict[UOp, UOp] = {}
|
||||
for u in tsink.toposort():
|
||||
if u.op is not Ops.ASSIGN: continue
|
||||
kernel_assign[u.buf_uop] = u
|
||||
for s in u.src[1].src:
|
||||
# TODO: this is probably broken for MSELECT/MSTACK
|
||||
if s.op is not Ops.BUFFER or s is u.buf_uop or (a:=kernel_assign.get(s)) is None: continue
|
||||
if any(x.op is Ops.ASSIGN and x.buf_uop is s for x in u.toposort()):
|
||||
raise RuntimeError(f"cycle detected in graph, kernel for {u.buf_uop} must either depend on ASSIGN or BUFFER")
|
||||
assign_rep[a] = kernel_assign[s] = a.replace(src=a.src+(u,))
|
||||
if assign_rep: tsink = graph_rewrite(tsink, _substitute, ctx=assign_rep, bottom_up=True, name="fix_assign")
|
||||
|
||||
if getenv("VIZ"): graph_rewrite(tsink, PatternMatcher([]), name="View Kernel Graph")
|
||||
|
||||
becomes_map: dict[UOp, UOp] = {}
|
||||
for s in tsink.src:
|
||||
assert s.tag is not None
|
||||
for a in s.tag:
|
||||
if a is None: continue
|
||||
becomes_map[uop_list[cast(int, a)]] = s.replace(tag=None)
|
||||
return becomes_map
|
||||
Reference in New Issue
Block a user