def _CreateEventWithDebugNumericSummary(
self, device_name, op_name, output_slot, wall_time, step, list_of_values):
"""Creates event with a health pill summary.
Args:
device_name: The name of the op's device.
op_name: The name of the op to which a DebugNumericSummary was attached.
output_slot: The numeric output slot for the tensor.
wall_time: The numeric wall time of the event.
step: The step of the event.
list_of_values: A python list of values within the tensor.
Returns:
A `tf.Event` with a health pill summary.
"""
event = tf.Event(step=step, wall_time=wall_time)
value = event.summary.value.add(
tag=op_name,
node_name='%s:%d:DebugNumericSummary' % (op_name, output_slot),
tensor=tf.make_tensor_proto(
list_of_values, dtype=tf.float64, shape=[len(list_of_values)]))
content_proto = debugger_event_metadata_pb2.DebuggerEventMetadata(
device=device_name, output_slot=output_slot)
value.metadata.plugin_data.plugin_name = constants.DEBUGGER_PLUGIN_NAME
value.metadata.plugin_data.content = tf.compat.as_bytes(
json_format.MessageToJson(
content_proto, including_default_value_fields=True))
return event
def _create_event_with_float_tensor(self, node_name, output_slot, debug_op,
list_of_values):
"""Creates event with float64 (double) tensors.
Args:
node_name: The string name of the op. This lacks both the output slot as
well as the name of the debug op.
output_slot: The number that is the output slot.
debug_op: The name of the debug op to use.
list_of_values: A python list of values within the tensor.
Returns:
A `tf.Event` with a summary containing that node name and a float64
tensor with those values.
"""
event = tf.Event()
value = event.summary.value.add(
tag=node_name,
node_name="%s:%d:%s" % (node_name, output_slot, debug_op),
tensor=tensor_util.make_tensor_proto(
list_of_values, dtype=tf.float64, shape=[len(list_of_values)]))
plugin_content = debugger_event_metadata_pb2.DebuggerEventMetadata(
device="/job:localhost/replica:0/task:0/cpu:0", output_slot=output_slot)
value.metadata.plugin_data.plugin_name = constants.DEBUGGER_PLUGIN_NAME
value.metadata.plugin_data.content = tf.compat.as_bytes(
json_format.MessageToJson(
plugin_content, including_default_value_fields=True))
return event
