code: def _adjust_dtype_and_shape_hints(self, x):
      x_ = tf.cast(x, self.dtype)
  
      # Since there is no sparse_placeholder_with_default, we manually feed in the
      # constituent dense Tensors to create a defacto placeholder SparseTensor.
      if isinstance(x_, tf.SparseTensor):
          indices_placeholder = self._make_placeholder(x_.indices)
          values_placeholder = self._make_placeholder(x_.values)
  
          if self.use_static_shape:
              dense_shape_placeholder = x_.dense_shape
          else:
              dense_shape_placeholder = self._make_placeholder(
                  x_.dense_shape
              )
  
          x_ = tf.SparseTensor(
              indices=indices_placeholder,
              values=values_placeholder,
              dense_shape=dense_shape_placeholder,
          )
      else:
          x_ = self._make_placeholder(x_)
      return x_
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.optimizer import proximal_hessian_sparse
label_desc: Use image node_id 2 for calling the _ProximalHessianTest obj's underlying member method code with example usage: obj._adjust_dtype_and_shape_hints(x) and returns: x_