Reduced CPU overhead in precompute_float8_dynamic_scale_for_fsdp (#331)

Summary:
Pull Request resolved: #331

**Description**
For Llama3-8B on 8xH100 profiling with `with_stack=True` (which does add overhead), the `precompute_float8_dynamic_scale_for_fsdp` CPU time decreases from 24 ms to 15 ms.

Before:
<img width="600" alt="Screenshot 2024-07-25 at 10 16 38 AM" src="https://github.com/user-attachments/assets/5d2384a0-6864-4bdc-91db-90cae809c702">

After:
<img width="638" alt="Screenshot 2024-07-25 at 10 17 00 AM" src="https://github.com/user-attachments/assets/1dbf3b2e-a576-4cdf-ac4f-06ae96020c38">

**Test Plan**
```
(pytorch-3.10) [[email protected] /data/users/andgu/float8_experimental (precompute_float8)]$ pytest test/test_fsdp2/test_fsdp2.py
========================================================= test session starts =========================================================
platform linux -- Python 3.10.13, pytest-7.3.2, pluggy-1.3.0
rootdir: /data/users/andgu/float8_experimental
plugins: xdoctest-1.1.0, hypothesis-5.35.1, xdist-3.3.1, shard-0.1.2, rerunfailures-13.0, flakefinder-1.1.0, cpp-2.3.0
collected 8 items
Running 8 items in this shard

test/test_fsdp2/test_fsdp2.py ........                                                                                          [100%]

========================================================== warnings summary ===========================================================
test/test_fsdp2/test_fsdp2.py::TestFloat8MultiThread::test_fp32_fp8_multi_module_parity
test/test_fsdp2/test_fsdp2.py::TestFloat8MultiThread::test_fp32_fp8_single_module_parity
  /data/users/andgu/float8_experimental/float8_experimental/float8_linear_utils.py:272: FutureWarning: The combination of ranks + tag as process group identifier has been deprecated. Please switch to using ProcessGroup, DeviceMesh, or group name instead.
    all_reduced_amax_tensor = all_reduce(

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
============================================== 8 passed, 2 warnings in 121.90s (0:02:01) ==============================================
```

imported-using-ghimport

Test Plan: Imported from OSS

Reviewed By: weifengpy

Differential Revision: D60236258

Pulled By: awgu

fbshipit-source-id: 7b1e48d431dac25d534a77d64d1e5571ad3ad807

Author: Andrew Gu

float8_experimental/fsdp_utils.py

@@ -57,18 +57,16 @@ def precompute_float8_dynamic_scale_for_fsdp(module: nn.Module) -> None:
 
     # inf-norm is equivalent to max(abs(w))
     max_weights = torch._foreach_norm(weights, ord=math.inf)  # Partial
-    amax_tensor = torch.vstack(max_weights)  # Partial
+    amax_tensor = torch.stack(max_weights)  # Partial
     # clamp is dispatched through DTensor
     # it will issue a single all-reduce
     amax_tensor = torch.clamp(amax_tensor, EPS)  # Replicate
     scale_tensor = torch.finfo(torch.float8_e4m3fn).max / amax_tensor  # Replicate
     if amax_tensor.dtype is torch.float16:
         scale_tensor = torch.clamp(scale_tensor, max=torch.finfo(torch.float16).max)
-    scales = torch.split(scale_tensor, 1)  # Replicate
-    for scale, float8_linear in zip(scales, float8_linears):
-        float8_linear.weight._local_tensor._precomputed_scale = (
-            scale._local_tensor.squeeze()
-        )
+    local_scale_tensor = scale_tensor.to_local()
+    for i, float8_linear in enumerate(float8_linears):
+        float8_linear.weight._local_tensor._precomputed_scale = local_scale_tensor[i]
 
 
 # FSDP pads its local tensor on dim-0. The subclass should be preserved such