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faceswap/lib/gpu_stats/nvidia.py
2022-06-18 02:29:19 +01:00

155 lines
5.6 KiB
Python

#!/usr/bin/env python3
""" Collects and returns Information on available Nvidia GPUs. """
from typing import List
import pynvml
from lib.utils import FaceswapError
from ._base import _GPUStats
class NvidiaStats(_GPUStats):
""" Holds information and statistics about Nvidia GPU(s) available on the currently
running system.
Notes
-----
PyNVML is used for hooking in to Nvidia's Machine Learning Library and allows for pulling
fairly extensive statistics for Nvidia GPUs
Parameters
----------
log: bool, optional
Whether the class should output information to the logger. There may be occasions where the
logger has not yet been set up when this class is queried. Attempting to log in these
instances will raise an error. If GPU stats are being queried prior to the logger being
available then this parameter should be set to ``False``. Otherwise set to ``True``.
Default: ``True``
"""
def _initialize(self) -> None:
""" Initialize PyNVML for Nvidia GPUs.
If :attr:`_is_initialized` is ``True`` then this function just returns performing no
action. Otherwise :attr:`is_initialized` is set to ``True`` after successfully
initializing NVML.
Raises
------
FaceswapError
If the NVML library could not be successfully loaded
"""
if self._is_initialized:
return
try:
self._log("debug", "Initializing PyNVML for Nvidia GPU.")
pynvml.nvmlInit()
except (pynvml.NVMLError_LibraryNotFound, # pylint:disable=no-member
pynvml.NVMLError_DriverNotLoaded, # pylint:disable=no-member
pynvml.NVMLError_NoPermission) as err: # pylint:disable=no-member
msg = ("There was an error reading from the Nvidia Machine Learning Library. The most "
"likely cause is incorrectly installed drivers. If this is the case, Please "
"remove and reinstall your Nvidia drivers before reporting. Original "
f"Error: {str(err)}")
raise FaceswapError(msg) from err
except Exception as err: # pylint: disable=broad-except
msg = ("An unhandled exception occured reading from the Nvidia Machine Learning "
f"Library. Original error: {str(err)}")
raise FaceswapError(msg) from err
super()._initialize()
def _shutdown(self) -> None:
""" Cleanly close access to NVML and set :attr:`_is_initialized` back to ``False``. """
self._log("debug", "Shutting down NVML")
pynvml.nvmlShutdown()
super()._shutdown()
def _get_device_count(self) -> int:
""" Detect the number of GPUs attached to the system.
Returns
-------
int
The total number of GPUs connected to the PC
"""
try:
retval = pynvml.nvmlDeviceGetCount()
except pynvml.NVMLError as err:
self._log("debug", "Error obtaining device count. Setting to 0. "
f"Original error: {str(err)}")
retval = 0
self._log("debug", f"GPU Device count: {retval}")
return retval
def _get_handles(self) -> list:
""" Obtain the device handles for all connected Nvidia GPUs.
Returns
-------
list
The list of pointers for connected Nvidia GPUs
"""
handles = [pynvml.nvmlDeviceGetHandleByIndex(i)
for i in range(self._device_count)]
self._log("debug", f"GPU Handles found: {len(handles)}")
return handles
def _get_driver(self) -> str:
""" Obtain the Nvidia driver version currently in use.
Returns
-------
str
The current GPU driver version
"""
try:
driver = pynvml.nvmlSystemGetDriverVersion().decode("utf-8")
except pynvml.NVMLError as err:
self._log("debug", f"Unable to obtain driver. Original error: {str(err)}")
driver = "No Nvidia driver found"
self._log("debug", f"GPU Driver: {driver}")
return driver
def _get_device_names(self) -> List[str]:
""" Obtain the list of names of connected Nvidia GPUs as identified in :attr:`_handles`.
Returns
-------
list
The list of connected Nvidia GPU names
"""
names = [pynvml.nvmlDeviceGetName(handle).decode("utf-8")
for handle in self._handles]
self._log("debug", f"GPU Devices: {names}")
return names
def _get_vram(self) -> List[int]:
""" Obtain the VRAM in Megabytes for each connected Nvidia GPU as identified in
:attr:`_handles`.
Returns
-------
list
The VRAM in Megabytes for each connected Nvidia GPU
"""
vram = [pynvml.nvmlDeviceGetMemoryInfo(handle).total / (1024 * 1024)
for handle in self._handles]
self._log("debug", f"GPU VRAM: {vram}")
return vram
def _get_free_vram(self) -> List[int]:
""" Obtain the amount of VRAM that is available, in Megabytes, for each connected Nvidia
GPU.
Returns
-------
list
List of `float`s containing the amount of VRAM available, in Megabytes, for each
connected GPU as corresponding to the values in :attr:`_handles
"""
vram = [pynvml.nvmlDeviceGetMemoryInfo(handle).free / (1024 * 1024)
for handle in self._handles]
self._log("debug", f"GPU VRAM free: {vram}")
return vram