code: def test_sparse_to_dense(self):
      def single_arg_dense_fn(x):
          y0 = ops.exp(x)
          return (y0,)
  
      x = KerasTensor(shape=(None, 3, 3), sparse=True)
      ys = backend.compute_output_spec(single_arg_dense_fn, x)
      for y in ys:
          self.assertEqual(y.shape, (None, 3, 3))
          self.assertFalse(y.sparse)
  
      def three_args_2_kwarg_dense_fn(x1, x2, x3=None):
          y0 = ops.add(x1, x3)  # sparse, dense
          y1 = ops.add(x3, x1)  # dense, sparse
          y2 = ops.concatenate([x1, x3], axis=0)  # sparse, dense
          y3 = ops.matmul(x1, x3)  # sparse, dense
          y4 = ops.matmul(x3, x1)  # dense, sparse
          indices = KerasTensor((3,), "int64", sparse=True)
          y5 = ops.take(x3, indices=indices, axis=1)  # dense, sparse
          y6 = ops.divide(x1, x2)
          return (y0, y1, y2, y3, y4, y5, y6)
  
      x1 = KerasTensor(shape=(None, 3, 3), sparse=True)
      x2 = KerasTensor(shape=(None, 3, 3), sparse=True)
      x3 = KerasTensor(shape=(None, 3, 3), sparse=False)
      ys = backend.compute_output_spec(
          three_args_2_kwarg_dense_fn, x1, x2, x3=x3
      )
      for y in ys:
          self.assertEqual(y.shape, (None, 3, 3))
          self.assertFalse(y.sparse)
  
file_path: keras/keras/backend/tests/compute_output_spec_test.py
imports: import unittest
  import pytest
  from keras import backend
  from keras import ops
  from keras.backend.common.keras_tensor import KerasTensor
label_desc: Use image node_id 4 for calling the ComputeOutputSpecTest obj's underlying member method code with example usage: obj.test_sparse_to_dense() and returns: y0, y0,  y1,  y2,  y3,  y4,  y5,  y6