tools/utilities/pythonlibs/audio/training/train_classifier.py
def export(self, name, device):    
        """ Export the model to the ONNX file format """
        self.init_hidden()
        dummy_input = Variable(torch.randn(1, 1, self.input_dim))
        if device:
            dummy_input = dummy_input.to(device)
        torch.onnx.export(self, dummy_input, name, verbose=True)
 Export the model to the ONNX file format 
Export the model to the ONNX file format
Export the model to the ONNX file format
def export(self, name, device):    
        self.init_hidden()
        dummy_input = Variable(torch.randn(1, 1, self.input_dim))
        if device:
            dummy_input = dummy_input.to(device)
        torch.onnx.export(self, dummy_input, name, verbose=True)
def export ( self , name , device ) : self . init_hidden ( ) dummy_input = Variable ( torch . randn ( 1 , 1 , self . input_dim ) ) if device : dummy_input = dummy_input . to ( device ) torch . onnx . export ( self , dummy_input , name , verbose = True )
Export the model to the ONNX file format
Export the model to the ONNX file format
""" Export the model to the ONNX file format """
self
name
device