class_docstr: Computes the mean of elements across given dimensions of the input tensor.
  
  Parameters
  ----------
  x: <\*,T> (Required)
      * Must be 1-dimensional or higher.
  
  axes: const<K,i32> (Optional, default="None", reduce on all axes.)
      * The dimensions to reduce.
  
  keep_dims: const<bool> (Optional, default=False)
      * If ``False``, the rank is reduced by ``1`` for each entry in ``axes``,
        otherwise retain reduced axes with length ``1``.
  
  Returns
  -------
  <\*,T>
      * Scalar or tensor: The reduced tensor.
  
  Attributes
  ----------
  T: i32, fp16, fp32
  
  References
  ----------
  For an example, see `tf.math.reduce_mean <https://www.tensorflow.org/api_docs/python/tf/math/reduce_mean?version=stable>`_.
code: def get_operator(self):
      return np.mean
  
imports: import numpy
  from coremltools.converters.mil.mil import Operation, precondition, types
  from coremltools.converters.mil.mil.input_type import DefaultInputs, InputSpec, TensorInputType
  from coremltools.converters.mil.mil.operation import VALUE
  from coremltools.converters.mil.mil.ops.defs._op_reqs import register_op
  from coremltools.converters.mil.mil.types import nptype_from_builtin
label_desc: Use image node_id 1 for calling the reduce_mean obj's underlying member method code with example usage: obj.get_operator() and returns: np