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}}]] #192
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)
def _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata): """Runs a step based on the given fetches and feeds.
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)