any suggestion for onnx exporting?

[wkkuniquegmail]

[lucasjinreal]

I have export it to onnx, seems no obstacles to do this:

onnxexp glance -m vits_baker_v1.onnx                                                                                           vits!?
Namespace(model='vits_baker_v1.onnx', subparser_name='glance', verbose=False, version=False)
Exploring on onnx model: vits_baker_v1.onnx
Model summary on: vits_baker_v1.onnx
-------------------------------------------
ir version: 7
opset_import: 11 
producer_name: pytorch
doc_string: 
all ops used: Gather,Constant,Mul,Transpose,Shape,Cast,Range,Unsqueeze,Less,Conv,Concat,Reshape,Div,MatMul,Sub,Add,ConstantOfShape,Slice,Pad,Equal,Where,Softmax,Pow,ReduceMean,Sqrt,Relu,Split,Erf,RandomNormalLike,Not,Greater,And,Expand,ScatterND,NonZero,GatherND,CumSum,Softplus,ReduceSum,GatherElements,Neg,Exp,Ceil,Clip,ReduceMax,If,Tanh,Sigmoid,LeakyRelu,ConvTranspose
-------------------------------------------

Summary: 
Name         Shape    Input/Output
-----------  -------  --------------
tst          [1, -1]  INPUT
tst_lengths  [1]      INPUT
output       [-1]     OUTPUT

[lucasjinreal]

@AronWang @Aloento I have updated the exportation code here: https://github.com/jinfagang/lark

I have reconstructed VITS training now it can be more easily training on other backbones.

[Aloento]

@jinfagang sad, 404

[lucasjinreal]

Will be release after some code refactoring. Meanwhile, join QQ group: 526506088 for more discussion about speech model

[Approximetal]

I have export it to onnx, seems no obstacles to do this:

onnxexp glance -m vits_baker_v1.onnx                                                                                           vits!?
Namespace(model='vits_baker_v1.onnx', subparser_name='glance', verbose=False, version=False)
Exploring on onnx model: vits_baker_v1.onnx
Model summary on: vits_baker_v1.onnx
-------------------------------------------
ir version: 7
opset_import: 11 
producer_name: pytorch
doc_string: 
all ops used: Gather,Constant,Mul,Transpose,Shape,Cast,Range,Unsqueeze,Less,Conv,Concat,Reshape,Div,MatMul,Sub,Add,ConstantOfShape,Slice,Pad,Equal,Where,Softmax,Pow,ReduceMean,Sqrt,Relu,Split,Erf,RandomNormalLike,Not,Greater,And,Expand,ScatterND,NonZero,GatherND,CumSum,Softplus,ReduceSum,GatherElements,Neg,Exp,Ceil,Clip,ReduceMax,If,Tanh,Sigmoid,LeakyRelu,ConvTranspose
-------------------------------------------

Summary: 
Name         Shape    Input/Output
-----------  -------  --------------
tst          [1, -1]  INPUT
tst_lengths  [1]      INPUT
output       [-1]     OUTPUT

@jinfagang What about the speed?