class_docstr: Test that SparseTensorDenseMatul operates reproducibly (on CPU only).
code: def testForward(self):
      for data_type in [
          np.float16,
          np.float32,
          np.float64,
          np.complex64,
          np.complex128,
      ]:  # skipping int32 and bfloat16
          sparse_input, dense_input = _gen_data(
              m=2430,
              k=615,
              n=857,
              nnz=(1 << 16) + 243,
              row_occupied_rate=0.02,
              data_type=data_type,
              seed=123,
          )
          with self.session(), test_util.force_cpu():
              result_a = sparse_ops.sparse_tensor_dense_matmul(
                  sparse_input, dense_input
              )
              for _ in range(5):
                  result_b = sparse_ops.sparse_tensor_dense_matmul(
                      sparse_input, dense_input
                  )
                  self.assertAllEqual(result_a, result_b)
  
file_path: tensorflow-upstream/tensorflow/python/kernel_tests/sparse_ops/sparse_tensor_dense_matmul_op_d9m_test.py
imports: import random
  import numpy
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the SparseTensorDenseMatmulOpDeterministicTest obj's underlying member method code with example usage: obj.testForward() without return types