def _parse_timeline_data(self, timeline, min_cycle_counter):
"""Parse timeline data."""
# factor to convert the time unit of start_time(ts) from 1ns to 1us for timeline display
factor = 1000
op_meta = TimelineContainer(timeline)
timeline_dict = {}
timeline_dict['name'] = op_meta.op_name
timeline_dict['ph'] = 'X'
timeline_dict['tid'] = op_meta.stream_id
timeline_dict['ts'] = (op_meta.start_time - min_cycle_counter) / factor
dur = op_meta.duration
timeline_dict['dur'] = dur
if op_meta.pid is None:
timeline_dict['pid'] = int(self._device_id)
else: # AllReduce and AI CPU pid
timeline_dict['pid'] = op_meta.pid
if len(timeline) > 4:
# len(timeline) > 4 refers to activity data, else op data.
# Add args for activity data
args_dict = {}
for ix, value in enumerate(timeline[4:]):
args_dict[self._activity_keys_list[ix]] = value
timeline_dict['args'] = args_dict
else:
# Update total time of operator execution.
self._timeline_summary['total_time'] += dur / factor
self._timeline_summary['op_exe_times'] += 1
self._timeline_meta.append(timeline_dict)
def _parse_timeline_data(self, timeline, min_cycle_counter):
"""Parse timeline data."""
# factor to convert the time unit from 1ms to 1us for timeline display
factor = 1000
op_meta = TimelineContainer(timeline)
timeline_dict = {}
timeline_dict['name'] = op_meta.op_name
timeline_dict['ph'] = 'X'
timeline_dict['tid'] = op_meta.stream_id
timeline_dict['ts'] = (op_meta.start_time - min_cycle_counter) * factor
dur = op_meta.duration * factor
timeline_dict['dur'] = dur
if op_meta.pid is None:
timeline_dict['pid'] = int(self._device_id)
# Update total time of operator execution.
self._timeline_summary['total_time'] += dur
else: # AllReduce and AI CPU pid
timeline_dict['pid'] = op_meta.pid
self._timeline_meta.append(timeline_dict)