Refactor _batch_cal_norm and remove #pyre-ignore
#3200
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Summary: "inf" norm calculation for FSDP2 is incorrect, as the `total_grad_norm` would always be 1.0 regardless of the gradients. This is due to `_batch_cal_norm` would calculate `total_grad_norm = total_grad_norm ** (1.0 / norm_type)`, even if the `norm_type` is `inf` norm. For `inf` norm, since `norm_type` is `torch.inf`, `total_grad_norm` would become `total_grad_norm ** (1.0 / torch.inf) `, which would always just be 1.0. Before the fix, line 220 is comparing `self._norm_type != torch.inf`, as `self._norm_type` is either float number of `"inf"`, it would always enter this if statement, which is incorrect for the infinity norm case. This issue is found during Shampoo War Room debugging for HSDP2 (context: https://fb.workplace.com/groups/3095840833991792/permalink/4084834545092411/). During ablation study, we found that DDP Fused Adam is on-par with HSDP2 Fused Adam when 2-norm is used for clipping (Figure 1), while HSDP2 Fused Adam behaves strangely (high variance between runs) when infinity norm is used for clipping (Figure 2). Figure 1 {F1980311095} Figure 2 {F1980311115} Differential Revision: D78326114
Summary: As title. Remove repeated `total_grad_norm` calculation and fix #pyre errors. Differential Revision: D78398248
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Summary: As title. Remove repeated
total_grad_normcalculation and fix #pyre errors.Differential Revision: D78398248