Source code for aac_metrics.classes.spice

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import logging
from pathlib import Path
from typing import Iterable, Optional, Union

from torch import Tensor

from aac_metrics.classes.base import AACMetric
from aac_metrics.functional.spice import SPICEOuts, spice

pylog = logging.getLogger(__name__)


[docs] class SPICE(AACMetric[Union[SPICEOuts, Tensor]]): """Semantic Propositional Image Caption Evaluation class. - Paper: https://arxiv.org/pdf/1607.08822.pdf For more information, see :func:`~aac_metrics.functional.spice.spice`. """ full_state_update = False higher_is_better = True is_differentiable = False min_value = 0.0 max_value = 1.0 def __init__( self, return_all_scores: bool = True, *, cache_path: Union[str, Path, None] = None, java_path: Union[str, Path, None] = None, tmp_path: Union[str, Path, None] = None, n_threads: Optional[int] = None, java_max_memory: str = "8G", timeout: Union[None, int, Iterable[int]] = None, separate_cache_dir: bool = True, use_shell: Optional[bool] = None, verbose: int = 0, ) -> None: super().__init__() self._return_all_scores = return_all_scores self._cache_path = cache_path self._java_path = java_path self._tmp_path = tmp_path self._n_threads = n_threads self._java_max_memory = java_max_memory self._timeout = timeout self._separate_cache_dir = separate_cache_dir self._use_shell = use_shell self._verbose = verbose self._candidates = [] self._mult_references = []
[docs] def compute(self) -> Union[SPICEOuts, Tensor]: return spice( candidates=self._candidates, mult_references=self._mult_references, return_all_scores=self._return_all_scores, cache_path=self._cache_path, java_path=self._java_path, tmp_path=self._tmp_path, n_threads=self._n_threads, java_max_memory=self._java_max_memory, timeout=self._timeout, separate_cache_dir=self._separate_cache_dir, use_shell=self._use_shell, verbose=self._verbose, )
[docs] def extra_repr(self) -> str: hparams = {"java_max_memory": self._java_max_memory} repr_ = ", ".join(f"{k}={v}" for k, v in hparams.items()) return repr_
[docs] def get_output_names(self) -> tuple[str, ...]: return ("spice",)
[docs] def reset(self) -> None: self._candidates = [] self._mult_references = [] return super().reset()
[docs] def update( self, candidates: list[str], mult_references: list[list[str]], ) -> None: self._candidates += candidates self._mult_references += mult_references