I have a list of tasks that each take a different amount of time. Let's say, I have 3 tasks, with durations close to 1*x, 5*x, 10*x. My tqdm code is something like:

```
from tqdm import tqdm
def create_task(n):
def fib(x):
if x == 1 or x == 0:
return 1
return fib(x - 1) + fib(x - 2)
return lambda: fib(n)
n = 1
tasks = [create_task(n), create_task(5*n), create_task(10*n)]
for task in tqdm(tasks):
task.run()
```

The problem is that tqdm thinks each iteration takes the same amount of time. As the first takes approximately 1/10 of the time, the ETA is unreliable.

**My question**: is it possible to somehow add a hint to tqdm to inform how much each iteration takes compared to the first? Something like informing the duration weights of each iteration...

Thanks!

If "create_task" can be modified, the "inspect" library can help.