forked from tinygrad/tinygrad
remove spec dtype check that's trivially true [PR] (#17823)
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This commit is contained in:
@@ -247,7 +247,7 @@ class CStyleLanguage(Renderer):
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(u.op in {Ops.STACK, *(GroupOp.ALU-{Ops.WHERE}), Ops.CAST, Ops.BITCAST} and child_count[u] == 1 and not getenv("EXPAND_SSA"))):
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r[u] = l
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else:
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if u.op not in {Ops.RANGE, Ops.STORE, Ops.BUFFER} and u.dtype != dtypes.void:
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if u.op not in {Ops.RANGE, Ops.BUFFER} and u.dtype != dtypes.void:
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l = f"{self.render_type(u)} {r[u]} = {l}" + (";" if u.op is not Ops.SPECIAL else "")
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kernel.append("\n".join(" "*depth + line for line in l.split("\n")))
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if prefix: c[prefix] += 1 # if it was used, increment
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@@ -80,7 +80,6 @@ class PythonProgram(Program['PythonDevice']):
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# in the python emulator, the warp is always in sync
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i += 1
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continue
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assert u.dtype is not None, f"{u.op} is missing a dtype"
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if u.op is Ops.STORE:
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assert len(src_values) == 2, f"STORE must be lowered to 2 srcs, got {len(src_values)}"
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store_gate = exec_masks[-1]
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+13
-15
@@ -68,8 +68,8 @@ spec_shared = PatternMatcher([
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(UPat(GroupOp.Comparison, dtype=dtypes.bool, src=(UPat.var("x"), UPat.var("y"))),
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lambda x,y: matches_dtype(x, y.dtype) or matches_dtype(y, x.dtype) or x.dtype in dtypes.weaks or y.dtype in dtypes.weaks),
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(UPat((Ops.AND, Ops.OR, Ops.XOR, Ops.SHL, Ops.SHR), name="x"), lambda x: False if any(dtypes.is_float(s.dtype) for s in x.src) else None),
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(UPat((Ops.SHL, Ops.SHR), src=(UPat.var("x"), UPat.var("c")), name="a"), lambda a,x,c: (matches_dtype(x, a.dtype) or x.dtype is dtypes.weakint)
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and (matches_dtype(c, a.dtype) or c.dtype in (dtypes.uint, dtypes.weakint) or x.base.is_invalid)),
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(UPat((Ops.SHL, Ops.SHR), src=(UPat.var("x"), UPat.var("c")), name="a"), lambda a,x,c:
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matches_dtype(c, a.dtype) or c.dtype in (dtypes.uint, dtypes.weakint) or x.base.is_invalid),
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(UPat((Ops.CDIV, Ops.CMOD, Ops.FLOORDIV, Ops.FLOORMOD), name="x"),
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lambda x: None if dtypes.is_int(x.dtype) or any(s.base.is_invalid for s in x.src) else False),
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(UPat(GroupOp.ALU, name="x"), lambda x: all(matches_dtype(y, x.dtype) or y.dtype in dtypes.weaks for y in x.src)),
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@@ -78,8 +78,7 @@ spec_shared = PatternMatcher([
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(UPat((Ops.BITCAST, Ops.CAST), src=(UPat(),), name="x"), lambda x: isinstance(x.arg, DType)),
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# RANGE can be in the big graph now. a void RANGE is a bound-less loop header, the arg is an axis id like RANGE
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(UPat(Ops.RANGE, src=(UPat.var("x"),), allow_any_len=True, name="rng"), lambda rng,x:
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matches_dtype(x, rng.dtype) and isinstance(rng.arg, tuple) and len(rng.arg) >= 2 and \
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(UPat(Ops.RANGE, src=(UPat(),), allow_any_len=True, name="rng"), lambda rng: isinstance(rng.arg, tuple) and len(rng.arg) >= 2 and \
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all(isinstance(ra, int) for ra in rng.arg[0:-1]) and isinstance(rng.arg[-1], AxisType)),
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(UPat(Ops.INDEX, name="x"), lambda x: len(x.src)>0 and all(dtypes.is_int(y.dtype) or y.base.is_invalid for y in x.src[1:]) or None),
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# END closes RANGEs
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@@ -97,7 +96,7 @@ spec_shared = PatternMatcher([
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# AFTER on Movement Op, PARAM, BUFFER, CONTIGUOUS, or another AFTER
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(UPat(Ops.AFTER, src=(UPat(GroupOp.Movement.union({Ops.PARAM, Ops.BUFFER, Ops.CONTIGUOUS, Ops.INDEX,
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Ops.AFTER, Ops.UNSHARD, Ops.BITCAST, Ops.INS})),),
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allow_any_len=True, name="x"), lambda x: matches_dtype(x.src[0], x.dtype)),
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allow_any_len=True), lambda: True),
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# CUSTOM (inline and non inline): the arg is the source string and the dtype it produces, void for a bare statement
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(UPat((Ops.CUSTOMI, Ops.CUSTOM), name="x"),
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@@ -132,7 +131,7 @@ spec_shared = PatternMatcher([
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def is_device(d): return isinstance(d, str) or (isinstance(d, tuple) and all(isinstance(s, str) for s in d))
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def valid_gettuple(g:UOp, t:UOp): return isinstance(g.arg, int) and 0 <= g.arg < len(t.src) and matches_dtype(t.src[g.arg], g.dtype)
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def valid_gettuple(g:UOp, t:UOp): return isinstance(g.arg, int) and 0 <= g.arg < len(t.src)
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# these ops can exist in tensor but not programs. example: movement
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spec_tensor = PatternMatcher([
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@@ -160,7 +159,7 @@ spec_tensor = PatternMatcher([
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(UPat(Ops.GETTUPLE, src=(UPat(Ops.TUPLE, name="t"),), name="g"), valid_gettuple),
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# SPECIAL is index before index lowering. custom_kernel currently has this
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(UPat(Ops.SPECIAL, src=(UPat.var("x", dtypes.weakint),), name="s"), lambda s,x: matches_dtype(x, s.dtype) and isinstance(s.arg, str)),
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(UPat(Ops.SPECIAL, src=(UPat(dtype=dtypes.weakint),), name="s"), lambda s: isinstance(s.arg, str)),
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# movement ops
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(UPat((Ops.RESHAPE, Ops.EXPAND), src=(UPat(), UPat())), lambda: True),
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@@ -173,20 +172,19 @@ spec_tensor = PatternMatcher([
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and isinstance(x.arg[1], int) and all(y.dtype in (dtypes.weakint, dtypes.int) for y in x.src[1:])),
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# COPY
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(UPat(Ops.COPY, name="copy", src=(UPat.var("x"),)), lambda copy,x: matches_dtype(x, copy.dtype) and is_device(copy.arg)),
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(UPat(Ops.ALLREDUCE, name="red", src=(UPat.var("x"),)), lambda red,x: matches_dtype(x, red.dtype) and isinstance(red.arg, tuple) and
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len(red.arg) == 2 and red.arg[0] in GroupOp.Reduce and is_device(red.arg[1])),
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(UPat(Ops.COPY, name="copy", src=(UPat(),)), lambda copy: is_device(copy.arg)),
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(UPat(Ops.ALLREDUCE, name="red", src=(UPat(),)),
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lambda red: isinstance(red.arg, tuple) and len(red.arg) == 2 and red.arg[0] in GroupOp.Reduce and is_device(red.arg[1])),
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# UNSHARD/MSELECT/MSTACK
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# an UNSHARD carries the value and one sharding range per sharded axis (usually a DEVICE RANGE, but can be a derived expression)
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(UPat(Ops.UNSHARD, name="multi"), lambda multi: len(multi.src) == 1+len(multi.arg) and matches_dtype(multi.src[0], multi.dtype)
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(UPat(Ops.UNSHARD, name="multi"), lambda multi: len(multi.src) == 1+len(multi.arg)
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and all(isinstance(a, int) for a in multi.arg) and all(r.dtype in dtypes.weaks for r in multi.src[1:])),
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(UPat(Ops.MSELECT, name="x"), lambda x: isinstance(x.src[0].device, tuple) and x.arg < len(x.src[0].device)),
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(UPat(Ops.MSTACK, name="x"), lambda x: all(isinstance(s.device, str) for s in x.src) or (all_same(x.src) and x.src[0].device is None)),
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# CONTIGUOUS ensures the source UOp realizes
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(UPat((Ops.DETACH, Ops.CONTIGUOUS, Ops.CONTIGUOUS_BACKWARD), name="root", src=(UPat.var("x"),), arg=None),
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lambda root,x: matches_dtype(x, root.dtype)),
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(UPat((Ops.DETACH, Ops.CONTIGUOUS, Ops.CONTIGUOUS_BACKWARD), src=(UPat(),), arg=None), lambda: True),
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# TODO: this should not be here. STAGE is transformed to BUFFER later
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(UPat(Ops.STAGE, src=(UPat(),), allow_any_len=True), lambda: True),
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@@ -224,7 +222,7 @@ spec_program = PatternMatcher([
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(UPat(Ops.ENDIF, dtype=dtypes.void, src=(UPat(Ops.IF),)), lambda: True),
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# SPECIAL is int32 after index lowering
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(UPat(Ops.SPECIAL, src=(UPat.var("x", dtypes.int32),), name="s"), lambda s,x: matches_dtype(x, s.dtype) and isinstance(s.arg, str)),
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(UPat(Ops.SPECIAL, src=(UPat(dtype=dtypes.int32),), name="s"), lambda s: isinstance(s.arg, str)),
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])+spec_shared
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spec_hcq = PatternMatcher([
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@@ -271,7 +269,7 @@ spec_kernel_graph = PatternMatcher([
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(UPat(Ops.CALL, src=(UPat((Ops.SINK, Ops.LINEAR, Ops.PROGRAM, Ops.CUSTOM_FUNCTION)),), allow_any_len=True), lambda: True),
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# after on PARAM or AFTER
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(UPat(Ops.AFTER, src=(UPat(GroupOp.Movement.union({Ops.PARAM, Ops.AFTER, Ops.BUFFER, Ops.MSTACK, Ops.MSELECT, Ops.BITCAST, Ops.RESHAPE})),),
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allow_any_len=True, name="x"), lambda x: matches_dtype(x.src[0], x.dtype)),
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allow_any_len=True), lambda: True),
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])
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# **** pyrender (move this) ****
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