Add new quantizer

1 files changed, 32 insertions, 0 deletions

diff --git a/text_recognizer/networks/quantizer/kmeans.py b/text_recognizer/networks/quantizer/kmeans.py
new file mode 100644
index 0000000..a34c381
--- /dev/null
+++ b/text_recognizer/networks/quantizer/kmeans.py
@@ -0,0 +1,32 @@
+"""K-means clustering for embeddings."""
+from typing import Tuple
+
+from einops import repeat
+import torch
+from torch import Tensor
+
+from text_recognizer.networks.quantizer.utils import norm, sample_vectors
+
+
+def kmeans(
+    samples: Tensor, num_clusters: int, num_iters: int = 10
+) -> Tuple[Tensor, Tensor]:
+    """Compute k-means clusters."""
+    D = samples.shape[-1]
+
+    means = sample_vectors(samples, num_clusters)
+
+    for _ in range(num_iters):
+        dists = samples @ means.t()
+        buckets = dists.max(dim=-1).indices
+        bins = torch.bincount(buckets, minlength=num_clusters)
+        zero_mask = bins == 0
+        bins_min_clamped = bins.masked_fill(zero_mask, 1)
+
+        new_means = buckets.new_zeros(num_clusters, D).type_as(samples)
+        new_means.scatter_add_(0, repeat(buckets, "n -> n d", d=D), samples)
+        new_means /= bins_min_clamped[..., None]
+        new_means = norm(new_means)
+        means = torch.where(zero_mask[..., None], means, new_means)
+
+    return means, bins