code: def _randomTensor(
      self,
      size,
      values_dtype,
      adjoint=False,
      sparse=False,
      indices_dtype=np.int64,
  ):
      n, m = size
      x = np.random.randn(n, m).astype(values_dtype)
      if values_dtype in (np.complex64, np.complex128):
          x.imag = np.random.randn(n, m)
  
      if adjoint:
          x = x.transpose().conj()
  
      if sparse:
          return self._sparsify(x, indices_dtype=indices_dtype)
      else:
          return constant_op.constant(x, dtype=values_dtype)
  
file_path: tensorflow/tensorflow/python/kernel_tests/sparse_ops/sparse_tensor_dense_matmul_grad_test.py
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import sparse_ops
  import tensorflow.python.ops.sparse_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the SparseTensorDenseMatMulGradientTest obj's underlying member method code with example usage: obj._randomTensor(size, values_dtype, adjoint, sparse, indices_dtype) and returns: self, constant_op