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/benchmarks/bench_mx.py

@@ -0,0 +1,30 @@
+# Copyright © 2024 Apple Inc.
+
+import time
+
+import mlx.core as mx
+from utils import load
+
+model, processor = load("mlx-community/encodec-48khz-float32")
+
+audio = mx.random.uniform(shape=(288000, 2))
+feats, mask = processor(audio)
+mx.eval(model, feats, mask)
+
+
+@mx.compile
+def fun():
+    codes, scales = model.encode(feats, mask, bandwidth=3)
+    reconstructed = model.decode(codes, scales, mask)
+    return reconstructed
+
+
+for _ in range(5):
+    mx.eval(fun())
+
+tic = time.time()
+for _ in range(10):
+    mx.eval(fun())
+toc = time.time()
+ms = 1000 * (toc - tic) / 10
+print(f"Time per it: {ms:.3f}")