/usr/lib/python3/dist-packages/glances/plugins/glances_gpu.py is in glances 2.11.1-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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#
# This file is part of Glances.
#
# Copyright (C) 2017 Kirby Banman <kirby.banman@gmail.com>
#
# Glances is free software; you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Glances 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 Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
"""GPU plugin (limited to NVIDIA chipsets)"""
from glances.compat import nativestr
from glances.logger import logger
from glances.plugins.glances_plugin import GlancesPlugin
try:
import pynvml
except Exception as e:
logger.error("Could not import pynvml. NVIDIA stats will not be collected.")
logger.debug("pynvml error: {}".format(e))
gpu_nvidia_tag = False
else:
gpu_nvidia_tag = True
class Plugin(GlancesPlugin):
"""Glances GPU plugin (limited to NVIDIA chipsets).
stats is a list of dictionaries with one entry per GPU
"""
def __init__(self, args=None):
"""Init the plugin"""
super(Plugin, self).__init__(args=args)
# Init the NVidia API
self.init_nvidia()
# We want to display the stat in the curse interface
self.display_curse = True
# Init the stats
self.reset()
def reset(self):
"""Reset/init the stats."""
self.stats = []
def init_nvidia(self):
"""Init the NVIDIA API"""
if not gpu_nvidia_tag:
self.nvml_ready = False
try:
pynvml.nvmlInit()
self.device_handles = get_device_handles()
self.nvml_ready = True
except Exception:
logger.debug("pynvml could not be initialized.")
self.nvml_ready = False
return self.nvml_ready
def get_key(self):
"""Return the key of the list."""
return 'gpu_id'
@GlancesPlugin._check_decorator
@GlancesPlugin._log_result_decorator
def update(self):
"""Update the GPU stats"""
self.reset()
# !!! JUST FOR TEST
# self.stats = [{"key": "gpu_id", "mem": None, "proc": 60, "gpu_id": 0, "name": "GeForce GTX 560 Ti"}]
# self.stats = [{"key": "gpu_id", "mem": 10, "proc": 60, "gpu_id": 0, "name": "GeForce GTX 560 Ti"}]
# self.stats = [{"key": "gpu_id", "mem": 48.64645, "proc": 60.73, "gpu_id": 0, "name": "GeForce GTX 560 Ti"},
# {"key": "gpu_id", "mem": 70.743, "proc": 80.28, "gpu_id": 1, "name": "GeForce GTX 560 Ti"},
# {"key": "gpu_id", "mem": 0, "proc": 0, "gpu_id": 2, "name": "GeForce GTX 560 Ti"}]
# self.stats = [{"key": "gpu_id", "mem": 48.64645, "proc": 60.73, "gpu_id": 0, "name": "GeForce GTX 560 Ti"},
# {"key": "gpu_id", "mem": None, "proc": 80.28, "gpu_id": 1, "name": "GeForce GTX 560 Ti"},
# {"key": "gpu_id", "mem": 0, "proc": 0, "gpu_id": 2, "name": "ANOTHER GPU"}]
# !!! TO BE COMMENTED
if not self.nvml_ready:
return self.stats
if self.input_method == 'local':
self.stats = self.get_device_stats()
elif self.input_method == 'snmp':
# not available
pass
return self.stats
def update_views(self):
"""Update stats views."""
# Call the father's method
super(Plugin, self).update_views()
# Add specifics informations
# Alert
for i in self.stats:
# Init the views for the current GPU
self.views[i[self.get_key()]] = {'proc': {}, 'mem': {}}
# Processor alert
if 'proc' in i:
alert = self.get_alert(i['proc'], header='proc')
self.views[i[self.get_key()]]['proc']['decoration'] = alert
# Memory alert
if 'mem' in i:
alert = self.get_alert(i['mem'], header='mem')
self.views[i[self.get_key()]]['mem']['decoration'] = alert
return True
def msg_curse(self, args=None, max_width=None):
"""Return the dict to display in the curse interface."""
# Init the return message
ret = []
# Only process if stats exist, not empty (issue #871) and plugin not disabled
if not self.stats or (self.stats == []) or self.is_disable():
return ret
# Check if all GPU have the same name
same_name = all(s['name'] == self.stats[0]['name'] for s in self.stats)
# gpu_stats contain the first GPU in the list
gpu_stats = self.stats[0]
# Header
header = ''
if len(self.stats) > 1:
header += '{} '.format(len(self.stats))
if same_name:
header += '{} {}'.format('GPU', gpu_stats['name'])
else:
header += '{}'.format('GPU')
msg = header[:17]
ret.append(self.curse_add_line(msg, "TITLE"))
# Build the string message
if len(self.stats) == 1 or args.meangpu:
# GPU stat summary or mono GPU
# New line
ret.append(self.curse_new_line())
# GPU PROC
try:
mean_proc = sum(s['proc'] for s in self.stats if s is not None) / len(self.stats)
except TypeError:
mean_proc_msg = '{:>4}'.format('N/A')
else:
mean_proc_msg = '{:>3.0f}%'.format(mean_proc)
if len(self.stats) > 1:
msg = '{:13}'.format('proc mean:')
else:
msg = '{:13}'.format('proc:')
ret.append(self.curse_add_line(msg))
ret.append(self.curse_add_line(
mean_proc_msg, self.get_views(item=gpu_stats[self.get_key()],
key='proc',
option='decoration')))
# New line
ret.append(self.curse_new_line())
# GPU MEM
try:
mean_mem = sum(s['mem'] for s in self.stats if s is not None) / len(self.stats)
except TypeError:
mean_mem_msg = '{:>4}'.format('N/A')
else:
mean_mem_msg = '{:>3.0f}%'.format(mean_mem)
if len(self.stats) > 1:
msg = '{:13}'.format('mem mean:')
else:
msg = '{:13}'.format('mem:')
ret.append(self.curse_add_line(msg))
ret.append(self.curse_add_line(
mean_mem_msg, self.get_views(item=gpu_stats[self.get_key()],
key='mem',
option='decoration')))
else:
# Multi GPU
for gpu_stats in self.stats:
# New line
ret.append(self.curse_new_line())
# GPU ID + PROC + MEM
id_msg = '{}'.format(gpu_stats['gpu_id'])
try:
proc_msg = '{:>3.0f}%'.format(gpu_stats['proc'])
except ValueError:
proc_msg = '{:>4}'.format('N/A')
try:
mem_msg = '{:>3.0f}%'.format(gpu_stats['mem'])
except ValueError:
mem_msg = '{:>4}'.format('N/A')
msg = '{}: {} mem: {}'.format(id_msg, proc_msg, mem_msg)
ret.append(self.curse_add_line(msg))
return ret
def get_device_stats(self):
"""Get GPU stats"""
stats = []
for index, device_handle in enumerate(self.device_handles):
device_stats = {}
# Dictionnary key is the GPU_ID
device_stats['key'] = self.get_key()
# GPU id (for multiple GPU, start at 0)
device_stats['gpu_id'] = index
# GPU name
device_stats['name'] = get_device_name(device_handle)
# Memory consumption in % (not available on all GPU)
device_stats['mem'] = get_mem(device_handle)
# Processor consumption in %
device_stats['proc'] = get_proc(device_handle)
stats.append(device_stats)
return stats
def exit(self):
"""Overwrite the exit method to close the GPU API"""
if self.nvml_ready:
try:
pynvml.nvmlShutdown()
except Exception as e:
logger.debug("pynvml failed to shutdown correctly ({})".format(e))
# Call the father exit method
super(Plugin, self).exit()
def get_device_handles():
"""
Returns a list of NVML device handles, one per device. Can throw NVMLError.
"""
return [pynvml.nvmlDeviceGetHandleByIndex(i) for i in range(pynvml.nvmlDeviceGetCount())]
def get_device_name(device_handle):
"""Get GPU device name"""
try:
return nativestr(pynvml.nvmlDeviceGetName(device_handle))
except pynvml.NVMlError:
return "NVIDIA"
def get_mem(device_handle):
"""Get GPU device memory consumption in percent"""
try:
memory_info = pynvml.nvmlDeviceGetMemoryInfo(device_handle)
return memory_info.used * 100.0 / memory_info.total
except pynvml.NVMLError:
return None
def get_proc(device_handle):
"""Get GPU device CPU consumption in percent"""
try:
return pynvml.nvmlDeviceGetUtilizationRates(device_handle).gpu
except pynvml.NVMLError:
return None
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