code: def test_symbolic_mask(self):
      # taken from gpt2 single kvcache
      # these two caused problems in gpt2 if reshape merged views
      view = View(
          shape=(
              1,
              (NumNode(1) + Variable("start_pos", 1, 128).bind(2)),
              16,
              64,
          ),
          strides=(0, 0, 64, 1),
          offset=NumNode(1024),
          mask=(
              (0, 1),
              (
                  Variable("start_pos", 1, 128).bind(2),
                  (NumNode(1) + Variable("start_pos", 1, 128).bind(2)),
              ),
              (0, 16),
              (0, 64),
          ),
          contiguous=False,
      )  # noqa: E501
      new_shape = (
          1,
          1,
          (NumNode(1) + Variable("start_pos", 1, 128).bind(2)),
          16,
          64,
      )
      assert view.reshape(new_shape) is None
  
      view = View(
          shape=(
              2,
              1,
              (NumNode(1) + Variable("start_pos", 1, 128)),
              16,
              64,
          ),
          strides=(0, 0, 1024, 64, 1),
          offset=131072,
          mask=(
              (1, 2),
              (0, 1),
              (0, (NumNode(1) + Variable("start_pos", 1, 128))),
              (0, 16),
              (0, 64),
          ),
          contiguous=False,
      )  # noqa: E501
      new_shape = (
          2,
          (NumNode(1) + Variable("start_pos", 1, 128)),
          16,
          64,
      )
      assert view.reshape(new_shape) is None
  
imports: import unittest
  from tinygrad.shape.shapetracker import ShapeTracker, View
  from tinygrad.shape.symbolic import Variable, NumNode
  from tinygrad.tensor import Tensor
label_desc: Use image node_id 5 for calling the TestSymbolicReshape obj's underlying member method code with example usage: obj.test_symbolic_mask() without return types