forked from tinygrad/tinygrad
optim flatten().shape[0] is numel (#10935)
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@@ -21,7 +21,7 @@ class Optimizer:
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# store lr in at least float32 precision
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self.lr = Tensor(lr if getenv("CONST_LR") else [lr], requires_grad=False, device=self.device,
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dtype=least_upper_dtype(dtypes.default_float, dtypes.float32))
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if self.fused: self.pos_params = list(itertools.accumulate(self.params, lambda x,y: x+y.flatten().shape[0], initial=0))
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if self.fused: self.pos_params = list(itertools.accumulate(self.params, lambda x,y: x+y.numel(), initial=0))
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def _new_optim_param(self) -> list[Tensor]:
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param_dtype = getenv("OPTIM_DTYPE", "float32")
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