Attempting to use uninitialized value FeatureExtractor/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/beta [[{{node _retval_FeatureExtractor/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/beta_0_179}}]]

[vamsikrishnahny]

def _do_run(self, handle, target_list, fetch_list, feed_dict, options,
run_metadata):
"""Runs a step based on the given fetches and feeds.

Args:
  handle: a handle for partial_run. None if this is just a call to run().
  target_list: A list of operations to be run, but not fetched.
  fetch_list: A list of tensors to be fetched.
  feed_dict: A dictionary that maps tensors to numpy ndarrays.
  options: A (pointer to a) [`RunOptions`] protocol buffer, or None
  run_metadata: A (pointer to a) [`RunMetadata`] protocol buffer, or None

Returns:
  A list of numpy ndarrays, corresponding to the elements of
  `fetch_list`.  If the ith element of `fetch_list` contains the
  name of an operation, the first Tensor output of that operation
  will be returned for that element.

Raises:
  tf.errors.OpError: Or one of its subclasses on error.
"""
# pylint: disable=protected-access
feeds = dict((t._as_tf_output(), v) for t, v in feed_dict.items())
fetches = [t._as_tf_output() for t in fetch_list]
targets = [op._c_op for op in target_list]
# pylint: enable=protected-access

def _run_fn(feed_dict, fetch_list, target_list, options, run_metadata):
  # Ensure any changes to the graph are reflected in the runtime.
  self._extend_graph()
  import pdb
  pdb.set_trace()
  return self._call_tf_sessionrun(
      options, feed_dict, fetch_list, target_list, run_metadata)

def _prun_fn(handle, feed_dict, fetch_list):
  if target_list:
    raise RuntimeError('partial_run() requires empty target_list.')
  return self._call_tf_sessionprun(handle, feed_dict, fetch_list)

if handle is None:
  return self._do_call(_run_fn, feeds, fetches, targets, options,
                       run_metadata)
else:
  return self._do_call(_prun_fn, handle, feeds, fetches)

def _do_call(self, fn, *args):
try:
return fn(*args)
except errors.OpError as e:
message = compat.as_text(e.message)
m = BaseSession._NODEDEF_NAME_RE.search(message)
node_def = None
op = None
if m is not None:
node_name = m.group(3)
try:
op = self._graph.get_operation_by_name(node_name)
node_def = op.node_def
except KeyError:
pass
message = error_interpolation.interpolate(message, self._graph)
raise type(e)(node_def, op, message)

[vamsikrishnahny]

please kindly anyone help me in this thanks in advance