From ef30a9d5ae60fdde5f6b44d6cea8cee0a40dd3e9 Mon Sep 17 00:00:00 2001
From: BlueAmulet <43395286+BlueAmulet@users.noreply.github.com>
Date: Sun, 2 Apr 2023 23:42:10 -0600
Subject: [PATCH] perf(utils): better implementation of repeat_expand_2d (#216)

---
 src/so_vits_svc_fork/utils.py | 18 ++++++------------
 1 file changed, 6 insertions(+), 12 deletions(-)

diff --git a/src/so_vits_svc_fork/utils.py b/src/so_vits_svc_fork/utils.py
index c84ffbb8..9878825b 100644
--- a/src/so_vits_svc_fork/utils.py
+++ b/src/so_vits_svc_fork/utils.py
@@ -369,18 +369,12 @@ def get_hparams(config_path: Path | str) -> HParams:
 def repeat_expand_2d(content: torch.Tensor, target_len: int) -> torch.Tensor:
     # content : [h, t]
     src_len = content.shape[-1]
-    target = torch.zeros(
-        [content.shape[0], target_len], dtype=content.dtype, device=content.device
-    )
-    temp = torch.arange(src_len + 1) * target_len / src_len
-    current_pos = 0
-    for i in range(target_len):
-        if i < temp[current_pos + 1]:
-            target[:, i] = content[:, current_pos]
-        else:
-            current_pos += 1
-            target[:, i] = content[:, current_pos]
-    return target
+    if target_len < src_len:
+        return content[:, :target_len]
+    else:
+        return torch.nn.functional.interpolate(
+            content.unsqueeze(0), size=target_len, mode="nearest"
+        ).squeeze(0)
 
 
 def plot_data_to_numpy(x: ndarray, y: ndarray) -> ndarray: