# wandb.watch

[![](https://www.tensorflow.org/images/GitHub-Mark-32px.png)View source on GitHub](https://www.github.com/wandb/client/tree/v0.10.31.dev1/wandb/sdk/wandb_watch.py#L19-L99)

Hooks into the torch model to collect gradients and the topology.

```python
watch(
    models, criterion=None, log="gradients", log_freq=1000, idx=None
)
```

Should be extended to accept arbitrary ML models.

| Args        |                                                                       |
| ----------- | --------------------------------------------------------------------- |
| `models`    | (torch.Module) The model to hook, can be a tuple                      |
| `criterion` | (torch.F) An optional loss value being optimized                      |
| `log`       | (str) One of "gradients", "parameters", "all", or None                |
| `log_freq`  | (int) log gradients and parameters every N batches                    |
| `idx`       | (int) an index to be used when calling wandb.watch on multiple models |

| Returns                                                                         |   |
| ------------------------------------------------------------------------------- | - |
| `wandb.Graph` The graph object that will populate after the first backward pass |   |