Encodec (#991)

* initial encodec

* works

* nits

* use fast group norm

* fix for rnn layer

* fix mlx version

* use custom LSTM kernel

* audio encodec

* fix example, support batched inference

* nits

encodec/example.py

@@ -0,0 +1,37 @@
+# Copyright © 2024 Apple Inc.
+
+import mlx.core as mx
+from utils import load, load_audio, save_audio
+
+# Load the 48 KHz model and preprocessor.
+model, processor = load("mlx-community/encodec-48khz-float32")
+
+# Load an audio file
+audio = load_audio("/path/to/audio", model.sampling_rate, model.channels)
+
+# Preprocess the audio (this can also be a list of arrays for batched
+# processing).
+feats, mask = processor(audio)
+
+
+# Encode at the given bandwidth. A lower bandwidth results in more
+# compression but lower reconstruction quality.
+@mx.compile
+def encode(feats, mask):
+    return model.encode(feats, mask, bandwidth=3)
+
+
+# Decode to reconstruct the audio
+@mx.compile
+def decode(codes, scales, mask):
+    return model.decode(codes, scales, mask)
+
+
+codes, scales = encode(feats, mask)
+reconstructed = decode(codes, scales, mask)
+
+# Trim any padding:
+reconstructed = reconstructed[0, : len(audio)]
+
+# Save the audio as a wave file
+save_audio("reconstructed.wav", reconstructed, model.sampling_rate)