From 87433c5bd976849b6253d9919aad574e942e2c5f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E6=BA=90=E6=96=87=E9=9B=A8?=
 <41315874+fumiama@users.noreply.github.com>
Date: Mon, 10 Jun 2024 21:50:43 +0900
Subject: [PATCH] fix(infer): argument mismatch

---
 infer/lib/infer_pack/models.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/infer/lib/infer_pack/models.py b/infer/lib/infer_pack/models.py
index 76b4a64..3e8ce1a 100644
--- a/infer/lib/infer_pack/models.py
+++ b/infer/lib/infer_pack/models.py
@@ -1,4 +1,4 @@
-from typing import Optional, List
+from typing import Optional, List, Union
 
 import torch
 from torch import nn
@@ -33,11 +33,11 @@ class SynthesizerTrnMsNSFsid(nn.Module):
         upsample_kernel_sizes: List[int],
         spk_embed_dim: int,
         gin_channels: int,
-        sr: Optional[str | int],
+        sr: Optional[Union[str, int]],
         encoder_dim: int,
         use_f0: bool,
     ):
-        super(SynthesizerTrnMs256NSFsid, self).__init__()
+        super().__init__()
         if isinstance(sr, str):
             sr = {
                 "32k": 32000,
@@ -175,7 +175,7 @@ class SynthesizerTrnMsNSFsid(nn.Module):
         phone_lengths: torch.Tensor,
         sid: torch.Tensor,
         pitch: Optional[torch.Tensor] = None,
-        nsff0: Optional[torch.Tensor] = None,
+        pitchf: Optional[torch.Tensor] = None, # nsff0
         skip_head: Optional[torch.Tensor] = None,
         return_length: Optional[torch.Tensor] = None,
         # return_length2: Optional[torch.Tensor] = None,
@@ -191,17 +191,17 @@ class SynthesizerTrnMsNSFsid(nn.Module):
             z = self.flow(z_p, x_mask, g=g, reverse=True)
             z = z[:, :, dec_head : dec_head + length]
             x_mask = x_mask[:, :, dec_head : dec_head + length]
-            if nsff0 is not None:
-                nsff0 = nsff0[:, head : head + length]
+            if pitchf is not None:
+                pitchf = pitchf[:, head : head + length]
         else:
             m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
             z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
             z = self.flow(z_p, x_mask, g=g, reverse=True)
         del z_p, m_p, logs_p
-        if nsff0 is not None:
+        if pitchf is not None:
             o = self.dec(
                 z * x_mask,
-                nsff0,
+                pitchf,
                 g=g,
                 # n_res=return_length2,
             )
@@ -235,7 +235,7 @@ class SynthesizerTrnMs256NSFsid(SynthesizerTrnMsNSFsid):
         upsample_kernel_sizes: List[int],
         spk_embed_dim: int,
         gin_channels: int,
-        sr: str | int,
+        sr: Union[str, int],
     ):
         super().__init__(
             spec_channels,
@@ -281,7 +281,7 @@ class SynthesizerTrnMs768NSFsid(SynthesizerTrnMsNSFsid):
         upsample_kernel_sizes: List[int],
         spk_embed_dim: int,
         gin_channels: int,
-        sr: str | int,
+        sr: Union[str, int],
     ):
         super().__init__(
             spec_channels,