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remove few dead or unneeded codes [pr] (#14275)
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@@ -220,7 +220,7 @@ class Scheduler:
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def _apply_tc_opt(self, use_tensor_cores:int, axis:int, tc_select:int, opt_level:int) -> None|list[UOp]:
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if not (reduceops := self.reduceops): raise KernelOptError("no reduce ops for TensorCore")
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reduceop = reduceops[0]
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if use_tensor_cores and reduceop is not None and reduceop.arg is Ops.ADD:
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if use_tensor_cores and reduceop.arg is Ops.ADD:
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mul = reduceop.src[0] if reduceop.src[0].op is not Ops.CAST else reduceop.src[0].src[0]
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if mul.op is not Ops.MUL: return None
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in0, in1 = mul.src
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@@ -323,7 +323,6 @@ class TinyJit(Generic[ReturnType]):
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try:
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ret = self.fxn(*args, **kwargs)
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if len(params:=get_parameters(ret)): Tensor.realize(params[0], *params[1:])
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except Exception as e: raise e
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finally: capturing.clear()
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jit_cache = self._jit_cache
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del self._buffer_replace, self._jit_cache
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@@ -308,12 +308,11 @@ class UOp(OpMixin, metaclass=UOpMetaClass):
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for er in self.ended_ranges:
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if er.op is Ops.RANGE:
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# if it's a single RANGE, we don't flow through it.
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if er in ret: del ret[er]
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ret.pop(er, None)
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else:
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# if it's not a RANGE, we include all ranges in srcs.
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# technically we shouldn't flow through these ranges either, but this is pre pm_add_control_flow so it's the same.
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for s in er.ranges:
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if s in ret: del ret[s]
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for s in er.ranges: ret.pop(s, None)
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return ret
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@property
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