class_docstr: Equivalent of numpy.ndarray backed by TensorFlow tensors.
  
  This does not support all features of NumPy ndarrays e.g. strides and
  memory order since, unlike NumPy, the backing storage is not a raw memory
  buffer.
  
  TODO(srbs): Clearly specify which attributes and methods are not supported
  or if there are any differences in behavior.
docstr: Returns a NumPy ndarray.
  
  This allows instances of this class to be directly used in NumPy routines.
  However, doing that may force a copy to CPU.
  
  Args:
    dtype: A NumPy compatible type.
  
  Returns:
    A NumPy ndarray.
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code: def __array__(self, dtype=None):
      """Returns a NumPy ndarray.
  
      This allows instances of this class to be directly used in NumPy routines.
      However, doing that may force a copy to CPU.
  
      Args:
        dtype: A NumPy compatible type.
  
      Returns:
        A NumPy ndarray.
      """
      return np.asarray(self.data, dtype)
  
imports: import numpy
  import six
  import tensorflow.compat.v2
  from trax.tf_numpy.numpy_impl import dtypes
label_desc: Use image node_id 18 for calling the ndarray obj's underlying member method code with example usage: obj.__array__(dtype) and returns: np