# General AutoDL Blocks (A\_DL\_ALL)

After training auto models, you'd have to use them of course. Blocks in this category are the right tools for the job. They are compatible with all AutoDL models, thanks to our dynamic approach to handling them

## Evaluating an Automated Deep Learning Model

```json
{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "A_DL_ALL_E",
    "args": {
        "hyp_params": {
            "batch_size": 32
        }
    }
}
```

## Parameter Details

## AutoDL Evaluating

<mark style="color:green;">`POST`</mark>&#x20;

#### Request Body

| Name                                             | Type   | Description                                                         |
| ------------------------------------------------ | ------ | ------------------------------------------------------------------- |
| project\_id<mark style="color:red;">\*</mark>    | int    | The `id` of the current project                                     |
| parent\_id<mark style="color:red;">\*</mark>     | int    | The `id` of the previous block                                      |
| block\_id<mark style="color:red;">\*</mark>      | int    | The `id` of the current block                                       |
| function\_code<mark style="color:red;">\*</mark> | String | Function code for the current block                                 |
| args<mark style="color:red;">\*</mark>           | object | Block arguments                                                     |
| hyp\_params<mark style="color:red;">\*</mark>    | object | hyper parameters for model evaluation                               |
| batch\_size                                      | int    | Number of samples that are processed by the model during evaluation |

{% tabs %}
{% tab title="200: OK Statemanagement object" %}

```json
{
    "status": "true",
    "message": {
        "id": 9,
        "project": 1,
        "block_id": 9,
        "parent_id": 8,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}
```

{% endtab %}
{% endtabs %}

## Predicting with an Automated Deep Learning Model

```json
{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "A_DL_ALL_P",
    "args": {
        "test_data": ""
    }
}
```

## Parameter Details

## AutoDL Predict

<mark style="color:green;">`POST`</mark> `https://autogon.ai/api/v1/engine/start`

#### Request Body

| Name                                             | Type   | Description                                                  |
| ------------------------------------------------ | ------ | ------------------------------------------------------------ |
| test\_data<mark style="color:red;">\*</mark>     | String | <p>Input data for prediction<br>Defaults to x\_test\_url</p> |
| project\_id<mark style="color:red;">\*</mark>    | int    | ID of the current project                                    |
| block\_id<mark style="color:red;">\*</mark>      | int    | ID of the current block                                      |
| parent\_id<mark style="color:red;">\*</mark>     | int    | ID of the previous block                                     |
| function\_code<mark style="color:red;">\*</mark> | String | Function code for the current block                          |
| args<mark style="color:red;">\*</mark>           | object | Block arguments                                              |
| add\_dim                                         | bool   | Sets whether an extra dimension should be added to `x` data  |

{% tabs %}
{% tab title="200: OK Statemanagement object" %}

```javascript
{
    "status": "true",
    "message": {
        "id": 9,
        "project": 1,
        "block_id": 9,
        "parent_id": 8,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}
```

{% endtab %}
{% endtabs %}

{% tabs %}
{% tab title="Python" %}

```
// Some code
```

{% endtab %}

{% tab title="Node" %}

```
// Some code
```

{% endtab %}
{% endtabs %}