Source code for aac_metrics.classes.spider

#!/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.spider import SPIDErOuts, spider

pylog = logging.getLogger(__name__)


[docs] class SPIDEr(AACMetric[Union[SPIDErOuts, Tensor]]): """SPIDEr class. - Paper: https://arxiv.org/pdf/1612.00370.pdf For more information, see :func:`~aac_metrics.functional.spider.spider`. """ full_state_update = False higher_is_better = True is_differentiable = False min_value = 0.0 max_value = 5.5 def __init__( self, return_all_scores: bool = True, *, # CIDErD args n: int = 4, sigma: float = 6.0, # SPICE args 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, verbose: int = 0, ) -> None: super().__init__() self._return_all_scores = return_all_scores self._n = n self._sigma = sigma 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._verbose = verbose self._candidates = [] self._mult_references = []
[docs] def compute(self) -> Union[SPIDErOuts, Tensor]: return spider( candidates=self._candidates, mult_references=self._mult_references, return_all_scores=self._return_all_scores, # CIDEr args n=self._n, sigma=self._sigma, # SPICE args 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, verbose=self._verbose, )
[docs] def extra_repr(self) -> str: hparams = { "n": self._n, "sigma": self._sigma, "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 ("cider_d", "spice", "spider")
[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