[Profiler] Change FLOP/s to Total FLOPs (#62779)

[Profiler] Change FLOP/s to Total FLOPs (#62779)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62779

Change from floating point operations per second to total floating point operations.  This requires removing the division  by executing time from the Kineto computed FLOPs and updating necessary documentation

Test Plan:
Running the following script:

```
import torch
from torch.profiler import profile
import torchvision.models as models

model = models.resnet18().eval()
inputs = torch.randn(5, 3, 224, 224)
with torch.no_grad():
    with profile(record_shapes=True, with_flops=True) as prof:
        model(inputs)
print(prof.key_averages().table(sort_by="cpu_time_total"))
```

Before diff results in:

{F636640118}

And after diff should be about `(27.78 * 10^9) FLOP/s * .652838 seconds =18135839640 FLOP = 18.136 GFLOP`.  Running the script again yields this answer:

{F636655686}

------------------------------------

Reviewed By: gdankel

Differential Revision: D29972997

fbshipit-source-id: 0f8d9f264b7d9f8f6bb3f10ab7c2c9794291e28b