code: def _prefer_static_shape(x):
      if tensor_shape.TensorShape(x.shape).is_fully_defined():
          return tensor_shape.TensorShape(x.shape)
      return prefer_static.shape(x)
  
imports: from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy import dtype
  from tensorflow_probability.python.internal.backend.numpy import errors
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy.gen import tensor_shape
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy import numpy_array
  from tensorflow_probability.python.internal.backend.numpy import debugging
  from tensorflow_probability.python.internal.backend.numpy import control_flow
  from tensorflow_probability.python.internal.backend.numpy import numpy_math
  from tensorflow_probability.python.internal.backend.numpy import linalg_impl
  from tensorflow_probability.python.internal.backend.numpy.gen import linear_operator
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import linalg_impl
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy.gen import tensor_shape
  from tensorflow_probability.python.internal.backend.numpy import private
label_desc: Use image node_id 1 for calling a global function with example usage: _prefer_static_shape(x) and returns: prefer_static, tensor_shape