[Whisper] Don't return attention mask in feat extractor (#19521)

* [Whisper] Don't return attention mask in feat extractor

* remove attention mask from test

* fix failing tests

* quality

src/transformers/models/whisper/feature_extraction_whisper.py

@@ -65,13 +65,19 @@ class WhisperFeatureExtractor(SequenceFeatureExtractor):
         chunk_length=30,
         n_fft=400,
         padding_value=0.0,
+        return_attention_mask=False,  # pad inputs to max length with silence token (zero) and no attention mask
         **kwargs
     ):
-        super().__init__(feature_size=feature_size, sampling_rate=sampling_rate, padding_value=padding_value, **kwargs)
+        super().__init__(
+            feature_size=feature_size,
+            sampling_rate=sampling_rate,
+            padding_value=padding_value,
+            return_attention_mask=return_attention_mask,
+            **kwargs,
+        )
         self.n_fft = n_fft
         self.hop_length = hop_length
         self.chunk_length = chunk_length
-        self.return_attention_mask = True
         self.n_samples = chunk_length * sampling_rate
         self.nb_max_frames = self.n_samples // hop_length
         self.sampling_rate = sampling_rate
@@ -301,7 +307,6 @@ class WhisperFeatureExtractor(SequenceFeatureExtractor):
             max_length=max_length if max_length else self.n_samples,
             truncation=truncation,
             pad_to_multiple_of=pad_to_multiple_of,
-            return_attention_mask=False,
             **kwargs,
         )
         # make sure list is in array format

tests/models/whisper/test_feature_extraction_whisper.py

@@ -66,7 +66,7 @@ class WhisperFeatureExtractionTester(unittest.TestCase):
         chunk_length=8,
         padding_value=0.0,
         sampling_rate=4_000,
-        return_attention_mask=True,
+        return_attention_mask=False,
         do_normalize=True,
     ):
         self.parent = parent