def _register_dead_handle(self, handle):
# Register a dead handle in the session. Delete the dead tensors when
# the number of dead tensors exceeds certain threshold.
tensors_to_delete = None
with self._delete_lock:
self._dead_handles.append(handle)
if len(self._dead_handles) == BaseSession._DEAD_HANDLES_THRESHOLD:
tensors_to_delete = self._dead_handles
self._dead_handles = []
# Delete the dead tensors.
# TODO(yuanbyu): For now we use a sequence of runs to minimize the graph
# size and the overhead of graph construction/partitioning.
if tensors_to_delete:
for tensor_handle in tensors_to_delete:
feeds = {}
fetches = []
holder, deleter = session_ops._get_handle_deleter(self.graph,
tensor_handle)
feeds[holder] = tensor_handle
fetches.append(deleter)
self.run(fetches, feed_dict=feeds)
def _register_dead_handle(self, handle):
# Register a dead handle in the session. Delete the dead tensors when
# the number of dead tensors exceeds certain threshold.
tensors_to_delete = None
with self._delete_lock:
self._dead_handles.append(handle)
if len(self._dead_handles) == BaseSession._DEAD_HANDLES_THRESHOLD:
tensors_to_delete = self._dead_handles
self._dead_handles = []
# Delete the dead tensors.
# TODO(yuanbyu): For now we use a sequence of runs to minimize the graph
# size and the overhead of graph construction/partitioning.
if tensors_to_delete:
for tensor_handle in tensors_to_delete:
feeds = {}
fetches = []
holder, deleter = session_ops._get_handle_deleter(self.graph,
tensor_handle)
feeds[holder] = tensor_handle
fetches.append(deleter)
self.run(fetches, feed_dict=feeds)