TypeError                                 Traceback (most recent call last)
 in 
27 # pycwt = CWT(widths, “cmorlet”, 3, 2048)*
28 # > #this==>>>>
—> 29 out = pycwt(x_ten)
30 # >
31 print(out.shape)
/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
725             result = self._slow_forward(*input, **kwargs)
726         else:
 → 727             result = self.forward(*input, **kwargs)
728         for hook in itertools.chain(
729                 _global_forward_hooks.values(),
 in forward(self, x)
84             wavelet_imag = self.wavelet_bank.imag.to(device=x.device, dtype=x.dtype)
85
—> 86             output_real = nn.functional.conv2d(x, wavelet_real, padding=“same”)
87             output_imag = nn.functional.conv2d(x, wavelet_imag, padding=“same”)
88 #This
TypeError: conv2d(): argument ‘padding’ must be tuple of ints, not str

Blockquote


I’m really sorry, ptrblck. I had a brain fart about my first question. I think I was drunk.

  
      

      kaggle.com
  

  
    

Continuous wavelet transform (CWT) in PyTorch 4

  Explore and run machine learning code with Kaggle Notebooks | Using data from G2Net Gravitational Wave Detection


  

  
    
    
  

  


The code is from this person.
In case you are wondering, let me organize the code in a way that is easy to understand.
I’m really sorry.