Prediction Cache Data Format
==================

### Supported File Formats

RIME CV supports the same file formats for the prediction cache as it does for the [input data](task_data_format), namely [JSON](https://www.json.org/json-en.html) (`.json`) and [JSON lines](https://jsonlines.org/) (`.jsonl`) formats. Each prediction should be stored in its own dictionary in the json list or as a dictionary on its own line for JSONL files.

To use a prediction cache for a given test run, it is currently required that a prediction be present for every data point in the corresponding input data. For example, if a dataset is of size `N`, line `i` in the prediction cache should contain the model output for input example `i` in the dataset for every `0 <= i < N`.

The data format for each prediction is similar to that for the [input data](task_data_format), the only difference being the "image identifier" and ground truth label keys for the CV task are removed.


#### Image Classification

For the Image Classification task, each prediction is represented by a dictionary containing the following key-value pair:

```python
[
    {
      "probabilities": [0.02, 0.94, 0.04]                 (REQUIRED)
    },
    ...
]
```


- **`probabilities`**: List[float],  ***required***
    
    The model prediction for this data point. This should be a normalized vector of class probabilities, with a probability for each possible class.