0e0d1e590e8cdae50d04a96617ea6601446f99fb,torchaudio/transforms.py,PadTrim,__call__,#PadTrim#Any#,104

Before Change

        
        if self.max_len > tensor.size(0):
            pad = torch.ones((self.max_len - tensor.size(0),
                              tensor.size(1))) * self.fill_value
            pad = pad.type_as(tensor)
            tensor = torch.cat((tensor, pad), dim=0)
        elif self.max_len < tensor.size(0):
            tensor = tensor[:self.max_len, :]
        return tensor

After Change

               "Too many channels ({}) detected, look at channels_first param.".format(tensor.size(self.ch_dim))
        if self.max_len > tensor.size(self.len_dim):

            padding_size = [self.max_len - tensor.size(self.len_dim) if i == self.len_dim
                            else tensor.size(self.ch_dim)
                            for i in range(2)]
            pad = torch.empty(padding_size, dtype=tensor.dtype).fill_(self.fill_value)
            tensor = torch.cat((tensor, pad), dim=self.len_dim)
        elif self.max_len < tensor.size(self.len_dim):
            tensor = tensor.narrow(self.len_dim, 0, self.max_len)

Instances