def _get_vram(self):
""" Obtain the total VRAM in Megabytes for each connected GPU.
Returns
-------
list
List of floats containing the total amount of VRAM in Megabytes for each connected GPU
as corresponding to the values in :attr:`_handles
"""
self._initialize()
if self._device_count == 0:
vram = list()
elif self._is_plaidml:
vram = self._plaid.vram
elif IS_MACOS:
vram = [
pynvx.cudaGetMemTotal(handle, ignore=True) / (1024 * 1024)
for handle in self._handles
]
else:
vram = [
pynvml.nvmlDeviceGetMemoryInfo(handle).total / (1024 * 1024)
for handle in self._handles
]
self._log("debug", "GPU VRAM: {}".format(vram))
return vram
def get_vram(self):
""" Return total vram in megabytes per device """
self.initialize()
if IS_MACOS:
vram = [pynvx.cudaGetMemTotal(handle, ignore=True) / (1024 * 1024)
for handle in self.handles]
else:
vram = [pynvml.nvmlDeviceGetMemoryInfo(handle).total /
(1024 * 1024)
for handle in self.handles]
if self.logger:
self.logger.debug("GPU VRAM: %s", vram)
return vram
def get_vram(self):
""" Return total vram in megabytes per device """
self.initialize()
if is_macos:
vram = [
pynvx.cudaGetMemTotal(handle, ignore=True) / (1024 * 1024)
for handle in self.handles
]
else:
vram = [
pynvml.nvmlDeviceGetMemoryInfo(handle).total / (1024 * 1024)
for handle in self.handles
]
return vram
def get_vram(self):
""" Return total vram in megabytes per device """
self.initialize()
if self.device_count == 0:
vram = list()
elif IS_MACOS:
vram = [pynvx.cudaGetMemTotal(handle, ignore=True) / (1024 * 1024)
for handle in self.handles]
else:
vram = [pynvml.nvmlDeviceGetMemoryInfo(handle).total /
(1024 * 1024)
for handle in self.handles]
if self.logger:
self.logger.debug("GPU VRAM: %s", vram)
return vram
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 = [
pynvx.cudaGetMemTotal(handle, ignore=True) / (1024 * 1024) # pylint:disable=no-member
for handle in self._handles
]
self._log("debug", f"GPU VRAM: {vram}")
return vram
def print_info():
try:
pynvx.cudaInit()
except RuntimeError as e:
print(e)
return
print('================ CUDA INFO =====================')
print('Driver Version : {}'.format(pynvx.cudaSystemGetDriverVersion()))
print('Runtime Version : {}'.format(pynvx.cudaSystemGetRuntimeVersion()))
print('Device Count : {}'.format(pynvx.cudaDeviceGetCount()))
handles = pynvx.cudaDeviceGetHandles()
for handle in handles:
print('------------------------------------------------')
print('Device {}:'.format(handle))
print('Device Name : {}'.format(
pynvx.cudaGetName(handle)))
print('Device ClockRate : {} MHz'.format(
pynvx.cudaGetClockRate(handle) / 1024))
print('Device ComputeCapability : {}'.format(
pynvx.cudaGetComputeCapability(handle)))
print('Device ProcessorCount : {}'.format(
pynvx.cudaGetMultiProcessorCount(handle)))
print('Device PciBusID : {}'.format(
pynvx.cudaGetPciBusID(handle)))
print('Device PciDeviceID : {}'.format(
pynvx.cudaGetPciDeviceID(handle)))
print('Device PciDomainID : {}'.format(
pynvx.cudaGetPciDomainID(handle)))
print('Device MemTotal : {} MiB'.format(
pynvx.cudaGetMemTotal(handle) / (1024 * 1024)))
print('Device MemFree : {} MiB'.format(
pynvx.cudaGetMemFree(handle) / (1024 * 1024)))
print('Device MemUsed : {} MiB'.format(
pynvx.cudaGetMemUsed(handle) / (1024 * 1024)))
def test_memory_total():
v = m.cudaGetMemTotal(0, ignore=True)
assert type(v) in integer_types
