don't serialize window and mel filters

src/transformers/models/speecht5/feature_extraction_speecht5.py

@@ -14,7 +14,7 @@
 # limitations under the License.
 """Feature extractor class for SpeechT5."""
 
-from typing import List, Optional, Union
+from typing import Any, Dict, List, Optional, Union
 
 import numpy as np
 import torch
@@ -111,7 +111,7 @@ def __init__(
         window = getattr(torch, self.win_function)(window_length=self.sample_size, periodic=True)
         self.window = window.numpy().astype(np.float64)
 
-        self.mel_filter_banks = get_mel_filter_banks(
+        self.mel_filters = get_mel_filter_banks(
             nb_frequency_bins=self.n_freqs,
             nb_mel_filters=self.num_mel_bins,
             frequency_min=self.fmin,
@@ -181,7 +181,7 @@ def _extract_mel_features(
 
         stft_out = self._stft(one_waveform, self.n_fft, self.sample_stride, self.window)
 
-        return np.log10(np.maximum(self.mel_floor, np.dot(stft_out, self.mel_filter_banks)))
+        return np.log10(np.maximum(self.mel_floor, np.dot(stft_out, self.mel_filters)))
 
     def __call__(
         self,
@@ -383,3 +383,14 @@ def _process_audio(
             padded_inputs = padded_inputs.convert_to_tensors(return_tensors)
 
         return padded_inputs
+
+    def to_dict(self) -> Dict[str, Any]:
+        output = super().to_dict()
+
+        # Don't serialize these as they are derived from the other properties.
+        names = ["window", "mel_filters", "sample_size", "sample_stride", "n_fft", "n_freqs"]
+        for name in names:
+            if name in output:
+                del output[name]
+
+        return output