code: def indexed_tensor(
      draw, n, min_value=None, max_value=None, shape=None
  ):
      """Return tensor paired with a set of indices suitable for it."""
  
      formula, shape = draw(tensor_shape_and_indices(n))
      t = draw(
          hpnp.arrays(
              dtype=np.float64,
              shape=shape,
              elements=hps.floats(
                  min_value=min_value, max_value=max_value
              ),
          )
      )
      return formula, t
  
imports: import hypothesis
  from hypothesis.extra import numpy
  import hypothesis.strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.marginalize.logeinsumexp import _binary_einslogsumexp
  from tensorflow_probability.python.experimental.marginalize.logeinsumexp import logeinsumexp
  from tensorflow_probability.python.internal import test_util
  import tensorflow_probability.python.internal.hypothesis_testlib
label_desc: Use image node_id 4 for calling a global function with example usage: indexed_tensor(draw, n, min_value, max_value, shape) and returns: formula,  t