code: def test_attention(self, dropout_p=0.0):
      def f(q, k, v):
          return Tensor.scaled_dot_product_attention(
              q.transpose(1, 2),
              k.transpose(1, 2),
              v.transpose(1, 2),
              dropout_p=dropout_p,
          ).realize()
  
      for i in range(1, 5):
          vi = Variable("i", 1, 10).bind(i)
          q = Tensor.rand(2, 1, 4, 8)
          k = Tensor.rand(2, i, 4, 8)
          v = Tensor.rand(2, i, 4, 8)
          symbolic = (
              f(q, k.reshape(2, vi, 4, 8), v.reshape(2, vi, 4, 8))
              .reshape(2, 4, 1, 8)
              .numpy()
          )
          expected = f(q, k, v).numpy()
          np.testing.assert_allclose(
              symbolic, expected, atol=1e-6, rtol=1e-6
          )
  
imports: import unittest
  from tinygrad.shape.symbolic import Variable
  from tinygrad.helpers import getenv
  from tinygrad.tensor import Tensor
  from examples.gpt2 import Attention
  import numpy
label_desc: Use image node_id 4 for calling the TestSymbolicOps obj's underlying member method code with example usage: obj.test_attention(dropout_p) and returns: Tensor