Update aom to commit id e87fb2378f01103d5d6e477a4ef6892dc714e614

1 files changed, 36 insertions, 4 deletions

diff --git a/third_party/aom/av1/encoder/palette.h b/third_party/aom/av1/encoder/palette.h
index 8afe5a782..efd89f66f 100644
--- a/third_party/aom/av1/encoder/palette.h
+++ b/third_party/aom/av1/encoder/palette.h
@@ -18,17 +18,49 @@
 extern "C" {
 #endif
 
+#define AV1_K_MEANS_RENAME(func, dim) func##_dim##dim
+
+void AV1_K_MEANS_RENAME(av1_calc_indices, 1)(const float *data,
+                                             const float *centroids,
+                                             uint8_t *indices, int n, int k);
+void AV1_K_MEANS_RENAME(av1_calc_indices, 2)(const float *data,
+                                             const float *centroids,
+                                             uint8_t *indices, int n, int k);
+void AV1_K_MEANS_RENAME(av1_k_means, 1)(const float *data, float *centroids,
+                                        uint8_t *indices, int n, int k,
+                                        int max_itr);
+void AV1_K_MEANS_RENAME(av1_k_means, 2)(const float *data, float *centroids,
+                                        uint8_t *indices, int n, int k,
+                                        int max_itr);
+
 // Given 'n' 'data' points and 'k' 'centroids' each of dimension 'dim',
 // calculate the centroid 'indices' for the data points.
-void av1_calc_indices(const float *data, const float *centroids,
-                      uint8_t *indices, int n, int k, int dim);
+static INLINE void av1_calc_indices(const float *data, const float *centroids,
+                                    uint8_t *indices, int n, int k, int dim) {
+  if (dim == 1) {
+    AV1_K_MEANS_RENAME(av1_calc_indices, 1)(data, centroids, indices, n, k);
+  } else if (dim == 2) {
+    AV1_K_MEANS_RENAME(av1_calc_indices, 2)(data, centroids, indices, n, k);
+  } else {
+    assert(0 && "Untemplated k means dimension");
+  }
+}
 
 // Given 'n' 'data' points and an initial guess of 'k' 'centroids' each of
 // dimension 'dim', runs up to 'max_itr' iterations of k-means algorithm to get
 // updated 'centroids' and the centroid 'indices' for elements in 'data'.
 // Note: the output centroids are rounded off to nearest integers.
-void av1_k_means(const float *data, float *centroids, uint8_t *indices, int n,
-                 int k, int dim, int max_itr);
+static INLINE void av1_k_means(const float *data, float *centroids,
+                               uint8_t *indices, int n, int k, int dim,
+                               int max_itr) {
+  if (dim == 1) {
+    AV1_K_MEANS_RENAME(av1_k_means, 1)(data, centroids, indices, n, k, max_itr);
+  } else if (dim == 2) {
+    AV1_K_MEANS_RENAME(av1_k_means, 2)(data, centroids, indices, n, k, max_itr);
+  } else {
+    assert(0 && "Untemplated k means dimension");
+  }
+}
 
 // Given a list of centroids, returns the unique number of centroids 'k', and
 // puts these unique centroids in first 'k' indices of 'centroids' array.