Fix: FER name in comment and internal variables. Also fix internal ca…

…ll in vocab metric.

src/aac_metrics/classes/fer.py

@@ -26,7 +26,7 @@ class FER(AACMetric[Union[tuple[dict[str, Tensor], dict[str, Tensor]], Tensor]])
     - Paper: https://arxiv.org/abs/2110.04684
     - Original implementation: https://github.com/blmoistawinde/fense
 
-    For more information, see :func:`~aac_metrics.functional.fluerr.fluerr`.
+    For more information, see :func:`~aac_metrics.functional.fer.fer`.
     """
 
     full_state_update = False

src/aac_metrics/classes/vocab.py

@@ -61,7 +61,7 @@ def compute(self) -> Union[tuple[dict[str, Tensor], dict[str, Tensor]], Tensor]:
 
     def get_output_names(self) -> tuple[str, ...]:
         return (
-            "vocab.cands",
+            "vocab",
             "vocab.mrefs_full",
             "vocab.ratio_full",
             "vocab.mrefs_avg",

src/aac_metrics/functional/evaluate.py

@@ -5,7 +5,7 @@
 import time
 
 from functools import partial
-from typing import Any, Callable, Iterable, Union
+from typing import Any, Callable, Iterable, Optional, Union
 
 import torch
 
@@ -53,7 +53,7 @@
     # DCASE challenge task6a metrics for 2023
     "dcase2023": (
         "meteor",
-        "spider_fl",  # includes cider_d, spice, spider, fluerr
+        "spider_fl",  # includes cider_d, spice, spider, fer
     ),
     # All metrics
     "all": (
@@ -63,8 +63,8 @@
         "bleu_4",
         "meteor",
         "rouge_l",
-        "fense",  # includes sbert, fluerr
-        "spider_fl",  # includes cider_d, spice, spider, fluerr
+        "fense",  # includes sbert, fer
+        "spider_fl",  # includes cider_d, spice, spider, fer
         "vocab",
     ),
 }
@@ -243,9 +243,9 @@ def _get_metric_factory_functions(
     tmp_path: str = ...,
     device: Union[str, torch.device, None] = "auto",
     verbose: int = 0,
-    init_kwds: dict[str, Any] = ...,
+    init_kwds: Optional[dict[str, Any]] = ...,
 ) -> dict[str, Callable[[list[str], list[list[str]]], Any]]:
-    if init_kwds is ...:
+    if init_kwds is None or init_kwds is ...:
         init_kwds = {}
 
     init_kwds = init_kwds | dict(return_all_scores=return_all_scores)

src/aac_metrics/functional/fense.py

@@ -116,7 +116,7 @@ def _fense_from_outputs(
     fer_outs: tuple[dict[str, Tensor], dict[str, Tensor]],
     penalty: float = 0.9,
 ) -> tuple[dict[str, Tensor], dict[str, Tensor]]:
-    """Combines SBERT and FluErr outputs.
+    """Combines SBERT and FER outputs.
 
     Based on https://github.com/blmoistawinde/fense/blob/main/fense/evaluator.py#L121
     """

src/aac_metrics/functional/fer.py

@@ -144,7 +144,7 @@ def fer(
     )
     fer_scores = (probs_outs_sents["error"] > error_threshold).astype(float)
 
-    fer_scores = torch.from_numpy(fluerr_scores)
+    fer_scores = torch.from_numpy(fer_scores)
     fer_score = fer_scores.mean()
 
     if return_all_scores:

src/aac_metrics/functional/spider_fl.py

@@ -145,7 +145,7 @@ def _spider_fl_from_outputs(
     fer_outs: tuple[dict[str, Tensor], dict[str, Tensor]],
     penalty: float = 0.9,
 ) -> tuple[dict[str, Tensor], dict[str, Tensor]]:
-    """Combines SPIDEr and FluErr outputs.
+    """Combines SPIDEr and FER outputs.
 
     Based on https://github.com/felixgontier/dcase-2023-baseline/blob/main/metrics.py#L48
     """

src/aac_metrics/functional/vocab.py

@@ -87,7 +87,7 @@ def vocab(
                 for refs in tok_mrefs
             ]
             popped_refs = [refs[idx] for idx, refs in zip(indexes, tok_mrefs)]
-            vocab_mrefs_len_i = _corpus_vocab(popped_refs)
+            vocab_mrefs_len_i = _corpus_vocab(popped_refs, dtype)
             vocab_mrefs_lens[i] = vocab_mrefs_len_i
 
         vocab_mrefs_avg = vocab_mrefs_lens.mean()