> For the complete documentation index, see [llms.txt](https://picsellia.gitbook.io/picsellia/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://picsellia.gitbook.io/picsellia/experiment-tracking/checkout-an-experiment.md).

# Checkout an experiment

Here we will see how to retrieve an experiment, it is useful if you want to work on an experiment created in our UI or if you need to download your saved model weights for inference for example...

## The checkout method

To checkout an experiment, you can use the following method : 

```python
from picsellia.client import Client

api_token = '4a54b5d45e45f4c454b54dee5b54bac4dd4'
project_token = '9a7d45b4c-691d-4c3a-9972-6a22b1dcd6f'

experiment = Client.Experiment(
    api_token=api_token,
    project_token=project_token
    )
experiment.checkout(
    name='my_new_experiment'
    )
```

The `checkout` method will return the instance of the `Experiment` Class, you will now have access to every method without entering the name or id again.

## Arguments

There are several optional arguments you can specify for this method  

* tree (Boolean, default=False)
* with\_file (Boolean, default=False)
* with\_data (Boolean, default=False)

### Tree

Use the `tree` parameter to automatically create training-ready folders for your experiment. If set to `True` it will create the following folders :

* checkpoint
* config
* exported\_model
* images
* metrics
* records
* results

Please check the [`picsellia_tf`](/picsellia/references-1/python-training-reference.md) documentation for more details on how this different folders are used.

### with\_data

Set this argument to True to access the details of every data assets stored for your experiment, this will give you access to the raw data stored in every asset. 

You can access the list in the `data` property of the `Experiment` Class

```python
exp = experiment.checkout(name='classification-v2', with_data=True)
print(exp.data)
```

```
[
{'id': 73, 'date_created': '2021-02-09T12:33:53.653119Z', 
'last_update': '2021-02-09T12:33:53.652903Z', 
'name': 'parameters', 
'data': {'steps': 100000, 'nb_gpus': 2, 'batch_size': 8, 
    'learning_rate': 0.001, 'annotation_type': 'classificiation'}, 
'type': 'table'}
]
```

### with\_file

Set this argument to True to download every file asset stored for your experiment

{% hint style="info" %}
If `tree` is set to True, the files will be downloaded to the folder corresponding to their type (e.g a file named 'chekpoint-index' will be stored in the 'checkpoint' folder.

If not, all the files will be stored to the path of the code you are running.
{% endhint %}