From 122afe0251d1a6232741f7f864a7ad02d220af30 Mon Sep 17 00:00:00 2001
From: OedoSoldier <31711261+OedoSoldier@users.noreply.github.com>
Date: Mon, 27 Nov 2023 13:08:43 +0800
Subject: [PATCH] Update infer.py (#196)

* Update

* Update
---
 infer.py | 31 ++++++++++++++++---------------
 1 file changed, 16 insertions(+), 15 deletions(-)

diff --git a/infer.py b/infer.py
index dcc4c36..ad6322a 100644
--- a/infer.py
+++ b/infer.py
@@ -82,7 +82,7 @@ def get_net_g(model_path: str, version: str, device: str, hps):
     return net_g
 
 
-def get_text(text, reference_audio, emotion, language_str, hps, device):
+def get_text(text, language_str, hps, device):
     # 在此处实现当前版本的get_text
     norm_text, phone, tone, word2ph = clean_text(text, language_str)
     phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
@@ -113,12 +113,6 @@ def get_text(text, reference_audio, emotion, language_str, hps, device):
     else:
         raise ValueError("language_str should be ZH, JP or EN")
 
-    emo = (
-        torch.from_numpy(get_emo(reference_audio))
-        if reference_audio
-        else torch.Tensor([emotion])
-    )
-
     assert bert.shape[-1] == len(
         phone
     ), f"Bert seq len {bert.shape[-1]} != {len(phone)}"
@@ -126,7 +120,16 @@ def get_text(text, reference_audio, emotion, language_str, hps, device):
     phone = torch.LongTensor(phone)
     tone = torch.LongTensor(tone)
     language = torch.LongTensor(language)
-    return bert, ja_bert, en_bert, emo, phone, tone, language
+    return bert, ja_bert, en_bert, phone, tone, language
+
+
+def get_emo(reference_audio, emotion):
+    emo = (
+        torch.from_numpy(get_emo(reference_audio))
+        if reference_audio
+        else torch.Tensor([emotion])
+    )
+    return emo
 
 
 def infer(
@@ -191,9 +194,10 @@ def infer(
                 device,
             )
     # 在此处实现当前版本的推理
-    bert, ja_bert, en_bert, emo, phones, tones, lang_ids = get_text(
-        text, reference_audio, emotion, language, hps, device
+    bert, ja_bert, en_bert, phones, tones, lang_ids = get_text(
+        text, language, hps, device
     )
+    emo = get_emo(reference_audio, emotion)
     if skip_start:
         phones = phones[1:]
         tones = tones[1:]
@@ -261,10 +265,8 @@ def infer_multilang(
     skip_start=False,
     skip_end=False,
 ):
-    bert, ja_bert, en_bert, emo, phones, tones, lang_ids = [], [], [], [], [], [], []
-    # bert, ja_bert, en_bert, phones, tones, lang_ids = get_text(
-    #     text, language, hps, device
-    # )
+    bert, ja_bert, en_bert, phones, tones, lang_ids = [], [], [], [], [], []
+    emo = get_emo(reference_audio, emotion)
     for idx, (txt, lang) in enumerate(zip(text, language)):
         skip_start = (idx != 0) or (skip_start and idx == 0)
         skip_end = (idx != len(text) - 1) or (skip_end and idx == len(text) - 1)
@@ -300,7 +302,6 @@ def infer_multilang(
     bert = torch.concatenate(bert, dim=1)
     ja_bert = torch.concatenate(ja_bert, dim=1)
     en_bert = torch.concatenate(en_bert, dim=1)
-    emo = torch.concatenate(emo, dim=1)
     phones = torch.concatenate(phones, dim=0)
     tones = torch.concatenate(tones, dim=0)
     lang_ids = torch.concatenate(lang_ids, dim=0)