|
|
--- |
|
|
title: vessl.progress |
|
|
version: EN |
|
|
--- |
|
|
|
|
|
# vessl.progress |
|
|
|
|
|
Use `vessl.progress` to track the progress of your experiment. VESSL provides an estimate of a remaining training time by calculating the average elapsed time of previous epochs or batch sizes. You can view this information by hovering over the status of a running experiment. This can be used in both VESSL's managed server or in a local environment.  |
|
|
|
|
|
| Parameter | Description | |
|
|
| --------- | -------------------------------------------------- | |
|
|
| `value` | Amount of progress (decimal value between 0 and 1) | |
|
|
|
|
|
### Examples |
|
|
|
|
|
```python |
|
|
import vessl |
|
|
|
|
|
for epoch in range(epochs): |
|
|
... |
|
|
|
|
|
# Update experiment progress every epoch |
|
|
vessl.progress((epoch+1) / epochs) |
|
|
``` |
|
|
|
|
|
```python |
|
|
def train(model, device, train_loader, optimizer, epoch, start_epoch): |
|
|
model.train() |
|
|
loss = 0 |
|
|
for batch_idx, (data, label) in enumerate(train_loader): |
|
|
... |
|
|
|
|
|
# Update experiment progress every batch |
|
|
vessl.progress( |
|
|
((epoch+1)*batch_size + batch_idx) / (batch_size * epochs)) |
|
|
) |
|
|
``` |
|
|
|
