code: def assert_is_batch_matrix(tensor):
      """Static assert that `tensor` has rank `2` or higher."""
      sh = tensor_shape.TensorShape(tensor.shape)
      if sh.ndims is not None and sh.ndims < 2:
          raise ValueError(
              f"Expected [batch] matrix to have at least two dimensions. Found: "
              f"{tensor}."
          )
  
imports: import numpy
  from tensorflow_probability.python.internal.backend.numpy import dtype
  from tensorflow_probability.python.internal.backend.numpy import ops
  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 linalg_impl
  from tensorflow_probability.python.internal.backend.numpy import numpy_math
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy import nest
  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 10 for calling a global function with example usage: assert_is_batch_matrix(tensor) without return types