fix: ksampler error when the tensor is not contiguous #535 (#673)

* Update utils.py-fix [Bug] ksampler error #535

* Update utils.py

* Update linear.py-fix [Bug] ksampler error #535 New issue

Author: wallen0322

nunchaku/models/linear.py

@@ -179,12 +179,12 @@ def forward(self, x: torch.Tensor, output: torch.Tensor | None = None) -> torch.
         B: batch size, S: sequence length
         """
         batch_size, seq_len, channels = x.shape
-        x = x.view(batch_size * seq_len, channels)
+        x = x.reshape(batch_size * seq_len, channels)
         if output is None:
             output = torch.empty(batch_size * seq_len, self.out_features, dtype=x.dtype, device=x.device)
         quantized_x, ascales, lora_act_out = self.quantize(x)
         output = self.forward_quant(quantized_x, ascales, lora_act_out, output)
-        output = output.view(batch_size, seq_len, -1)
+        output = output.reshape(batch_size, seq_len, -1)
         return output
 
     def quantize(self, x: torch.Tensor, pad_size: int = 256) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]: