code: def test_copy_tensors_produces_equivalent_tensors(self):
      with tf.compat.v1.Graph().as_default():
          tensors = {
              "dense": tf.compat.v1.placeholder(
                  tf.int64, (None,), name="my_dense_input"
              ),
              "sparse": tf.compat.v1.sparse_placeholder(
                  tf.int64, name="my_sparse_input"
              ),
              "ragged": tf.compat.v1.ragged.placeholder(
                  tf.int64, ragged_rank=1, name="my_ragged_input"
              ),
          }
          copied_tensors = tf_utils.copy_tensors(tensors)
  
          with tf.compat.v1.Session() as session:
              dense_value = [1, 2]
              sparse_value = tf.compat.v1.SparseTensorValue(
                  indices=[[0, 0], [0, 2], [1, 1]],
                  values=[3, 4, 5],
                  dense_shape=[2, 3],
              )
              ragged_value = tf.compat.v1.ragged.RaggedTensorValue(
                  values=np.array([3, 4, 5], dtype=np.int64),
                  row_splits=np.array([0, 2, 3], dtype=np.int64),
              )
              sample_tensors = session.run(
                  copied_tensors,
                  feed_dict={
                      tensors["dense"]: dense_value,
                      tensors["sparse"]: sparse_value,
                      tensors["ragged"]: ragged_value,
                  },
              )
              self.assertAllEqual(sample_tensors["dense"], dense_value)
              self.assertAllEqual(
                  sample_tensors["sparse"].indices, sparse_value.indices
              )
              self.assertAllEqual(
                  sample_tensors["sparse"].values, sparse_value.values
              )
              self.assertAllEqual(
                  sample_tensors["sparse"].dense_shape,
                  sparse_value.dense_shape,
              )
              self.assertAllEqual(
                  sample_tensors["ragged"].values, ragged_value.values
              )
              self.assertAllEqual(
                  sample_tensors["ragged"].row_splits,
                  ragged_value.row_splits,
              )
  
imports: import os
  import numpy
  from packaging import version
  import tensorflow
  from tensorflow_transform import analyzers
  from tensorflow_transform import annotators
  from tensorflow_transform import tf_utils
  from tensorflow_transform import test_case
  from tensorflow.python.framework import composite_tensor
label_desc: Use image node_id 3 for calling the TFUtilsTest obj's underlying member method code with example usage: obj.test_copy_tensors_produces_equivalent_tensors() without return types