Skip to content

euroeval.model_cache

source module euroeval.model_cache

ModelCache class for caching model outputs.

Classes

Functions

source class ModelCache(model_cache_dir: Path, cache_name: str, max_generated_tokens: int)

A cache for model outputs.

Initialise the model output cache.

Attributes

  • model_cache_dir — The directory to store the cache in.

  • cache_path — The path to the cache file.

  • cache — The model output cache.

  • max_generated_tokens — The maximum number of tokens to generate for each example.

Parameters

  • model_cache_dir : Path — The directory to store the cache in.

  • cache_name : str — The name of the cache file.

  • max_generated_tokens : int — The maximum number of tokens to generate for each example.

Methods

  • load — Load the model output cache.

  • save — Save the model output cache to disk.

  • remove — Remove the cache from memory and delete it from disk.

  • add_to_cache — Add the model input/output to the cache.

source method ModelCache.load() → None

Load the model output cache.

source method ModelCache.save() → None

Save the model output cache to disk.

source method ModelCache.remove() → None

Remove the cache from memory and delete it from disk.

source method ModelCache.add_to_cache(model_inputs: dict, model_output: GenerativeModelOutput) → None

Add the model input/output to the cache.

Parameters

source split_dataset_into_cached_and_non_cached(dataset: Dataset, cache: ModelCache) → tuple['Dataset', 'Dataset']

Split a dataset into a cached and non-cached part.

Parameters

  • dataset : Dataset — The dataset to split.

  • cache : ModelCache — The model output cache.

Returns

  • tuple['Dataset', 'Dataset'] — The cached and non-cached parts of the dataset.

source load_cached_model_outputs(cached_dataset: Dataset, cache: ModelCache) → GenerativeModelOutput

Load the cached model outputs.

Parameters

  • cached_dataset : Dataset — The dataset containing the cached examples.

  • cache : ModelCache — The model output cache.

Returns