Add Pedalboard to benchmarks.

README.md

@@ -21,6 +21,7 @@ This is relevant for machine learning models that today often process raw (time
 | [torchaudio](https://github.com/pytorch/audio) (soundfile)                                                                              | 0.9.0   | `torchaudio`     | PyTorch Tensor    | all codecs supported by Soundfile                   | ✅               |
 | [soxbindings](https://github.com/pseeth/soxbindings)                                                                                    | 0.9.0   | `soxbindings`    | Numpy Tensor      | all codecs supported by Soundfile                   | ✅               |
 | [stempeg](https://github.com/faroit/stempeg)                                                                                            | 0.2.3   | `stempeg`        | Numpy Tensor      | all codecs supported by FFMPEG                      | ✅               |
+| [pedalboard.io.AudioFile](https://github.com/spotify/pedalboard)                                                                                            | 0.5.1   | `pedalboard`        | Numpy Array      | WAV, AIFF, MP3, OGG, FLAC        | ✅               |
 
 ### Not included
 

benchmark_metadata.py

@@ -62,6 +62,7 @@ def __len__(self):
         'soundfile',
         'sox',
         'audioread',
+        'pedalboard',
     ]
 
     for lib in libs:

benchmark_np.py

@@ -72,7 +72,8 @@ def test_np_loading(fp, lib):
         'pydub',
         'soundfile',
         'librosa',
-        'scipy_mmap'
+        'scipy_mmap',
+        'pedalboard',
     ]
 
     for lib in libs:

benchmark_pytorch.py

@@ -72,6 +72,7 @@ def __len__(self):
         'librosa',
         'scipy',
         'scipy_mmap',
+        'pedalboard',
     ]
 
     if args.ext != "mp4":

benchmark_tf.py

@@ -59,6 +59,7 @@ def _py_loader_function(fp):
         'scipy',
         'scipy_mmap',
         'tf_decode_wav',
+        'pedalboard',
     ]
 
     for lib in libs:

loaders.py

@@ -13,6 +13,7 @@
 import soxbindings
 import sox
 import stempeg
+import pedalboard
 
 
 """
@@ -121,6 +122,12 @@ def load_librosa(fp):
     return sig
 
 
+def load_pedalboard(fp):
+    with pedalboard.io.AudioFile(fp) as f:
+        # Pedalboard output is (num_channels, num_samples)
+        return f.read(f.frames)[0]
+
+
 def _convert_buffer_to_float(buf, n_bytes=2, dtype=np.float32):
     # taken from librosa.util.utils
     # Invert the scale of the data
@@ -206,4 +213,14 @@ def info_stempeg(fp):
     info["samples"] = si.samples(0)
     info["channels"] = si.channels(0)
     info["duration"] = si.duration(0)
-    return info
+    return info
+
+
+def info_pedalboard(fp):
+    info = {}
+    with pedalboard.io.AudioFile(fp) as af:
+        info["sampling_rate"] = af.samplerate
+        info["samples"] = af.frames
+        info["channels"] = af.num_channels
+        info["duration"] = af.duration
+    return info

requirements.txt

@@ -15,3 +15,4 @@ seaborn
 pandas
 ipython
 cffi
+pedalboard==0.5.1