code: def _placeholder_with_default(
      input, shape, name=None
  ):  # pylint: disable=redefined-builtin,unused-argument
      x = convert_to_tensor(input)
      if hasattr(shape, "as_list"):
          shape = shape.as_list()
      if shape is None or any(s is None for s in shape):
          return x
      return np.reshape(x, shape)
  
imports: import collections
  import contextlib
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import _utils
  from tensorflow_probability.python.internal.backend.numpy import initializers
  from tensorflow_probability.python.internal.backend.numpy import linalg_impl
  from tensorflow_probability.python.internal.backend.numpy import numpy_logging
  from tensorflow_probability.python.internal.backend.numpy.gen.tensor_shape import Dimension
  from tensorflow_probability.python.internal.backend.numpy.numpy_array import *
  from tensorflow_probability.python.internal.backend.numpy.ops import convert_to_tensor
  from tensorflow_probability.python.internal.backend.numpy.ops import Module
  from tensorflow_probability.python.internal.backend.numpy.ops import name_scope
  from tensorflow_probability.python.internal.backend.numpy.ops import Variable
  from tensorflow_probability.python.internal.backend.numpy.random_generators import set_seed
  from tensorflow_probability.python.internal.backend.numpy.tensor_array_ops import TensorArray
label_desc: Use image node_id 3 for calling a global function with example usage: _placeholder_with_default(input, shape, name) and returns: np, x