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update init_step name

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zpeng11 2025-08-20 20:05:07 -04:00
parent aafa0561d8
commit 4e0cc57052
2 changed files with 13 additions and 13 deletions
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20
GPT_SoVITS/onnx_export.py
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@ -89,7 +89,7 @@ class DictToAttrRecursive(dict):
raise AttributeError(f"Attribute {item} not found") raise AttributeError(f"Attribute {item} not found")
class T2SEncoder(nn.Module): class T2SInitStep(nn.Module):
def __init__(self, t2s, vits): def __init__(self, t2s, vits):
super().__init__() super().__init__()
self.encoder = t2s.onnx_encoder self.encoder = t2s.onnx_encoder
@ -122,7 +122,7 @@ class T2SModel(nn.Module):
self.t2s_model.model.early_stop_num = torch.LongTensor([self.hz * self.max_sec]) self.t2s_model.model.early_stop_num = torch.LongTensor([self.hz * self.max_sec])
self.t2s_model = self.t2s_model.model self.t2s_model = self.t2s_model.model
self.t2s_model.init_onnx() self.t2s_model.init_onnx()
self.onnx_encoder = T2SEncoder(self.t2s_model, self.vits_model) self.init_step = T2SInitStep(self.t2s_model, self.vits_model)
self.first_stage_decoder = self.t2s_model.first_stage_decoder self.first_stage_decoder = self.t2s_model.first_stage_decoder
self.stage_decoder = self.t2s_model.stage_decoder self.stage_decoder = self.t2s_model.stage_decoder
# self.t2s_model = torch.jit.script(self.t2s_model) # self.t2s_model = torch.jit.script(self.t2s_model)
@ -131,7 +131,7 @@ class T2SModel(nn.Module):
early_stop_num = self.t2s_model.early_stop_num early_stop_num = self.t2s_model.early_stop_num
# [1,N] [1,N] [N, 1024] [N, 1024] [1, 768, N] # [1,N] [1,N] [N, 1024] [N, 1024] [1, 768, N]
y, k, v, y_emb, x_example = self.onnx_encoder(ref_seq, text_seq, ref_bert, text_bert, ssl_content) y, k, v, y_emb, x_example = self.init_step(ref_seq, text_seq, ref_bert, text_bert, ssl_content)
for idx in tqdm(range(1, 20)): # This is a fake one! do take this as reference for idx in tqdm(range(1, 20)): # This is a fake one! do take this as reference
# [1, N] [N_layer, N, 1, 512] [N_layer, N, 1, 512] [1, N, 512] [1] [1, N, 512] [1, N] # [1, N] [N_layer, N, 1, 512] [N_layer, N, 1, 512] [1, N, 512] [1] [1, N, 512] [1, N]
@ -144,19 +144,19 @@ class T2SModel(nn.Module):
return y[:, -idx:].unsqueeze(0) return y[:, -idx:].unsqueeze(0)
def export(self, ref_seq, text_seq, ref_bert, text_bert, ssl_content, project_name, dynamo=False): def export(self, ref_seq, text_seq, ref_bert, text_bert, ssl_content, project_name, dynamo=False):
# self.onnx_encoder = torch.jit.script(self.onnx_encoder) # self.init_step = torch.jit.script(self.init_step)
if dynamo: if dynamo:
export_options = torch.onnx.ExportOptions(dynamic_shapes=True) export_options = torch.onnx.ExportOptions(dynamic_shapes=True)
onnx_encoder_export_output = torch.onnx.dynamo_export( init_step_export_output = torch.onnx.dynamo_export(
self.onnx_encoder, (ref_seq, text_seq, ref_bert, text_bert, ssl_content), export_options=export_options self.init_step, (ref_seq, text_seq, ref_bert, text_bert, ssl_content), export_options=export_options
) )
onnx_encoder_export_output.save(f"onnx/{project_name}/{project_name}_t2s_encoder.onnx") init_step_export_output.save(f"onnx/{project_name}/{project_name}_t2s_init_step.onnx")
return return
torch.onnx.export( torch.onnx.export(
self.onnx_encoder, self.init_step,
(ref_seq, text_seq, ref_bert, text_bert, ssl_content), (ref_seq, text_seq, ref_bert, text_bert, ssl_content),
f"onnx/{project_name}/{project_name}_t2s_encoder.onnx", f"onnx/{project_name}/{project_name}_t2s_init_step.onnx",
input_names=["ref_seq", "text_seq", "ref_bert", "text_bert", "ssl_content"], input_names=["ref_seq", "text_seq", "ref_bert", "text_bert", "ssl_content"],
output_names=["y", "k", "v", "y_emb", "x_example"], output_names=["y", "k", "v", "y_emb", "x_example"],
dynamic_axes={ dynamic_axes={
@ -168,7 +168,7 @@ class T2SModel(nn.Module):
}, },
opset_version=16, opset_version=16,
) )
y, k, v, y_emb, x_example = self.onnx_encoder(ref_seq, text_seq, ref_bert, text_bert, ssl_content) y, k, v, y_emb, x_example = self.init_step(ref_seq, text_seq, ref_bert, text_bert, ssl_content)
# torch.onnx.export( # torch.onnx.export(
# self.first_stage_decoder, # self.first_stage_decoder,

6
playground/freerun.py
View File

@ -63,7 +63,7 @@ def preprocess_text(text:str):
# input_phones_saved = np.load("playground/ref/input_phones.npy") # input_phones_saved = np.load("playground/ref/input_phones.npy")
# input_bert_saved = np.load("playground/ref/input_bert.npy").T.astype(np.float32) # input_bert_saved = np.load("playground/ref/input_bert.npy").T.astype(np.float32)
[input_phones, input_bert] = preprocess_text("像大雨匆匆打击过的屋檐") [input_phones, input_bert] = preprocess_text("天上的风筝在天上飞，地上的人儿在地上追")
# ref_phones = np.load("playground/ref/ref_phones.npy") # ref_phones = np.load("playground/ref/ref_phones.npy")
@ -74,9 +74,9 @@ def preprocess_text(text:str):
[audio_prompt_hubert, spectrum, sv_emb] = audio_preprocess("playground/ref/audio.wav") [audio_prompt_hubert, spectrum, sv_emb] = audio_preprocess("playground/ref/audio.wav")
encoder = ort.InferenceSession(MODEL_PATH+"_export_t2s_encoder.onnx") init_step = ort.InferenceSession(MODEL_PATH+"_export_t2s_init_step.onnx")
[y, k, v, y_emb, x_example] = encoder.run(None, { [y, k, v, y_emb, x_example] = init_step.run(None, {
"text_seq": input_phones, "text_seq": input_phones,
"text_bert": input_bert, "text_bert": input_bert,
"ref_seq": ref_phones, "ref_seq": ref_phones,