code: def test_to_dense(self):
      if self.nbatch > 0:
          x_shape = (self.nbatch, self.shape[0], self.shape[1])
      else:
          x_shape = self.shape
      x0 = _setup_tensor(0.5, 1, x_shape, self.dtype, 0.75)
      if self.use_ldnz:
          ldnz = self.shape[0] * self.shape[1]
          sp_x = utils.to_coo(x0, ldnz=ldnz)
      else:
          sp_x = utils.to_coo(x0)
      assert sp_x.data.shape == sp_x.row.shape == sp_x.col.shape
      if self.nbatch > 0:
          assert sp_x.data.ndim == 2
          assert sp_x.data.shape[0] == self.nbatch
          if self.use_ldnz:
              assert sp_x.data.shape[1] == ldnz
          else:
              max_nnz = 0
              for i in range(self.nbatch):
                  max_nnz = max(max_nnz, numpy.count_nonzero(x0[i]))
              assert sp_x.data.shape[1] == max_nnz
      else:
          assert sp_x.data.ndim == 1
          if self.use_ldnz:
              assert sp_x.data.shape[0] == ldnz
          else:
              max_nnz = numpy.count_nonzero(x0)
              assert sp_x.data.shape[0] == max_nnz
      x1 = sp_x.to_dense()
      numpy.testing.assert_array_equal(x0, x1)
  
file_path: chainer/tests/chainer_tests/utils_tests/test_sparse.py
imports: import unittest
  import numpy
  from chainer import testing
  from chainer import utils
label_desc: Use image node_id 1 for calling the TestCooMatrix obj's underlying member method code with example usage: obj.test_to_dense() without return types