def _process_graph_def(self, graph_def):
for node_def in graph_def.node:
if (debug_graphs.is_debug_node(node_def.name) and
node_def.attr["gated_grpc"].b):
node_name, output_slot, _, debug_op = (
debug_graphs.parse_debug_node_name(node_def.name))
self._gated_grpc_debug_watches.add(
DebugWatch(node_name, output_slot, debug_op))
def testParseDebugNodeName_valid(self):
debug_node_name_1 = "__dbg_ns_a/ns_b/node_c:1_0_DebugIdentity"
(watched_node, watched_output_slot, debug_op_index,
debug_op) = debug_graphs.parse_debug_node_name(debug_node_name_1)
self.assertEqual("ns_a/ns_b/node_c", watched_node)
self.assertEqual(1, watched_output_slot)
self.assertEqual(0, debug_op_index)
self.assertEqual("DebugIdentity", debug_op)
def get_gated_grpc_tensors(self, matching_debug_op=None):
"""Extract all nodes with gated-gRPC debug ops attached.
Uses cached values if available.
This method is thread-safe.
Args:
graph_def: A tf.GraphDef proto.
matching_debug_op: Return tensors and nodes with only matching the
specified debug op name (optional). If `None`, will extract only
`DebugIdentity` debug ops.
Returns:
A list of (node_name, op_type, output_slot, debug_op) tuples.
"""
with self._grpc_gated_lock:
matching_debug_op = matching_debug_op or "DebugIdentity"
if matching_debug_op not in self._grpc_gated_tensors:
# First, construct a map from node name to op type.
node_name_to_op_type = dict(
(node.name, node.op) for node in self._graph_def.node)
# Second, populate the output list.
gated = []
for node in self._graph_def.node:
if node.op == matching_debug_op:
for attr_key in node.attr:
if (attr_key == "gated_grpc"
and node.attr[attr_key].b):
(
node_name,
output_slot,
_,
debug_op,
) = debug_graphs.parse_debug_node_name(
node.name)
gated.append((
node_name,
node_name_to_op_type[node_name],
output_slot,
debug_op,
))
break
self._grpc_gated_tensors[matching_debug_op] = gated
return self._grpc_gated_tensors[matching_debug_op]
def get_gated_grpc_tensors(self, matching_debug_op=None):
"""Extract all nodes with gated-gRPC debug ops attached.
Uses cached values if available.
This method is thread-safe.
Args:
graph_def: A tf.GraphDef proto.
matching_debug_op: Return tensors and nodes with only matching the
specified debug op name (optional). If `None`, will extract only
`DebugIdentity` debug ops.
Returns:
A list of (node_name, op_type, output_slot, debug_op) tuples.
"""
with self._grpc_gated_lock:
matching_debug_op = matching_debug_op or 'DebugIdentity'
if matching_debug_op not in self._grpc_gated_tensors:
# First, construct a map from node name to op type.
node_name_to_op_type = dict(
(node.name, node.op) for node in self._graph_def.node)
# Second, populate the output list.
gated = []
for node in self._graph_def.node:
if node.op == matching_debug_op:
for attr_key in node.attr:
if attr_key == 'gated_grpc' and node.attr[attr_key].b:
node_name, output_slot, _, debug_op = (
debug_graphs.parse_debug_node_name(node.name))
gated.append(
(node_name, node_name_to_op_type[node_name], output_slot,
debug_op))
break
self._grpc_gated_tensors[matching_debug_op] = gated
return self._grpc_gated_tensors[matching_debug_op]
def testParseDebugNodeName_invalidWatchedTensorName(self):
invalid_debug_node_name_1 = "__dbg_node1_0_DebugIdentity"
with self.assertRaisesRegexp(ValueError,
"Invalid tensor name in debug node name"):
debug_graphs.parse_debug_node_name(invalid_debug_node_name_1)
def testParseDebugNodeName_missingDebugOpIndex(self):
invalid_debug_node_name_1 = "__dbg_node1:0_DebugIdentity"
with self.assertRaisesRegexp(ValueError, "Invalid debug node name"):
debug_graphs.parse_debug_node_name(invalid_debug_node_name_1)
def testParseDebugNodeName_invalidPrefix(self):
invalid_debug_node_name_1 = "__copy_ns_a/ns_b/node_c:1_0_DebugIdentity"
with self.assertRaisesRegexp(ValueError, "Invalid prefix"):
debug_graphs.parse_debug_node_name(invalid_debug_node_name_1)
