fix: Fix unfold method in torch frontend with shape mismatch issues w…

…ith the native fw

ivy/functional/frontends/torch/tensor.py

@@ -767,14 +767,9 @@ def unfold(self, dimension, size, step):
             slicing[dimension] = slice(i, i + size)
             slices.append(self.ivy_array[tuple(slicing)])
         stacked = torch_frontend.stack(slices, dim=dimension)
-        new_shape = list(self.shape)
-        num_slices = (self.shape[dimension] - size) // step + 1
-        new_shape[dimension] = num_slices
-        new_shape.insert(dimension + 1, size)
-        reshaped = stacked.reshape(new_shape)
         dims = list(range(len(stacked.shape)))
         dims[-2], dims[-1] = dims[-1], dims[-2]
-        return reshaped.permute(*dims)
+        return stacked.permute(*dims)
 
     def long(self, memory_format=None):
         self.ivy_array = ivy.astype(self.ivy_array, ivy.int64, copy=False)