Source code for spinn_front_end_common.interface.interface_functions.profile_data_gatherer
# Copyright (c) 2017-2019 The University of Manchester
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import os
import logging
from spinn_utilities.progress_bar import ProgressBar
from spinn_front_end_common.interface.profiling import AbstractHasProfileData
logger = logging.getLogger(__name__)
[docs]class ProfileDataGatherer(object):
__slots__ = []
def __call__(
self, transceiver, placements, provenance_file_path,
machine_time_step):
"""
:param transceiver: the SpiNNMan interface object
:param placements: The placements of the vertices
:param has_ran: token that states that the simulation has ran
:param provenance_file_path: The location to store the profile data
:param machine_time_step: machine time step in ms
"""
# pylint: disable=too-many-arguments
machine_time_step_ms = float(machine_time_step) / 1000.0
progress = ProgressBar(
placements.n_placements, "Getting profile data")
# retrieve provenance data from any cores that provide data
for placement in progress.over(placements.placements):
if isinstance(placement.vertex, AbstractHasProfileData):
# get data
profile_data = placement.vertex.get_profile_data(
transceiver, placement)
if profile_data.tags:
self._write(placement, profile_data, machine_time_step_ms,
provenance_file_path)
def _write(self, p, profile_data, machine_time_step_ms, directory):
# pylint: disable=too-many-arguments
max_tag_len = max(len(tag) for tag in profile_data.tags)
# write data
file_name = os.path.join(
directory, "{}_{}_{}_profile.txt".format(p.x, p.y, p.p))
# set mode of the file based off if the file already exists
mode = "w"
if os.path.exists(file_name):
mode = "a"
# write profile data to file
with open(file_name, mode) as f:
f.write("{: <{}s} {: <7s} {: <14s} {: <14s} {: <14s}\n".format(
"tag", max_tag_len, "n_calls", "mean_ms",
"n_calls_per_ts", "mean_ms_per_ts"))
f.write("{:-<{}s} {:-<7s} {:-<14s} {:-<14s} {:-<14s}\n".format(
"", max_tag_len, "", "", "", ""))
for tag in profile_data.tags:
f.write("{: <{}s} {: >7d} {: >14.6f} {: >14.6f} {: >14.6f}\n"
.format(
tag, max_tag_len,
profile_data.get_n_calls(tag),
profile_data.get_mean_ms(tag),
profile_data.get_mean_n_calls_per_ts(
tag, machine_time_step_ms),
profile_data.get_mean_ms_per_ts(
tag, machine_time_step_ms)))