def set_quantization_dataset_path(self, dataset_path: str) -> None:
"""Update dataset path in quantization config."""
if dataset_path == "no_dataset_location":
return
if (self.quantization and self.quantization.calibration
and self.quantization.calibration.dataloader
and self.quantization.calibration.dataloader.dataset):
self.quantization.calibration.dataloader.dataset.params.update(
{"root": dataset_path}, )
else:
log.warning("Could not set quantization dataset path.")
def set_quantization_dataloader(self, dataloader: dict) -> None:
"""Udpate dataloader in quantization config."""
if (self.quantization and self.quantization.calibration
and self.quantization.calibration.dataloader):
calib_dataloader = {
dataloader.get("name", "Unknown"):
dataloader.get("params", {}),
}
self.quantization.calibration.dataloader.set_dataset(
calib_dataloader)
else:
log.warning("Could not set performance dataloader.")
def set_evaluation_dataloader(self, dataloader: dict) -> None:
"""Udpate dataloader in evaluation config."""
dataset = {
dataloader.get("name", "Unknown"): dataloader.get("params", {}),
}
if self.evaluation and self.evaluation.accuracy and self.evaluation.accuracy.dataloader:
self.evaluation.accuracy.dataloader.set_dataset(deepcopy(dataset))
else:
log.warning("Could not set accuracy dataloader.")
if (self.evaluation and self.evaluation.performance
and self.evaluation.performance.dataloader):
self.evaluation.performance.dataloader.set_dataset(
deepcopy(dataset))
else:
log.warning("Could not set performance dataloader.")
def set_evaluation_dataset_path(self, dataset_path: str) -> None:
"""Update dataset path in evaluation config."""
if dataset_path == "no_dataset_location":
return
if (self.evaluation and self.evaluation.accuracy
and self.evaluation.accuracy.dataloader
and self.evaluation.accuracy.dataloader.dataset):
self.evaluation.accuracy.dataloader.dataset.params.update(
{"root": dataset_path}, )
else:
log.warning("Could not set accuracy dataset path.")
if (self.evaluation and self.evaluation.performance
and self.evaluation.performance.dataloader
and self.evaluation.performance.dataloader.dataset):
self.evaluation.performance.dataloader.dataset.params.update(
{"root": dataset_path}, )
else:
log.warning("Could not set performance dataset path.")
def __init__(self) -> None:
"""Initialize HW Info class and gather information platform hardware."""
cpu_info = cpuinfo.get_cpu_info()
self.sockets: int = get_number_of_sockets()
self.cores: int = psutil.cpu_count(logical=False)
self.cores_per_socket: int = int(
psutil.cpu_count(logical=False) / self.sockets)
self.threads_per_socket: int = int(
psutil.cpu_count(logical=True) / self.sockets)
self.total_memory: str = f"{psutil.virtual_memory().total / (1024 ** 3):.3f}GB"
self.system: str = get_distribution()
self.ip = determine_ip()
if cpu_info.get("brand"):
self.platform = cpu_info.get("brand")
elif cpu_info.get("brand_raw"):
self.platform = cpu_info.get("brand_raw")
else:
self.platform = ""
self.hyperthreading_enabled: bool = psutil.cpu_count(
logical=False) != psutil.cpu_count(logical=True, )
self.turboboost_enabled = is_turbo_boost_enabled()
self.bios_version = get_bios_version()
self.kernel: str = get_kernel_version()
try:
min_cpu_freq = int(psutil.cpu_freq(percpu=False).min)
max_cpu_freq = int(psutil.cpu_freq(percpu=False).max)
except Exception:
log.warning("Cannot collect cpu frequency information.")
min_cpu_freq = 0
max_cpu_freq = 0
finally:
if min_cpu_freq == 0:
self.min_cpu_freq = "n/a"
else:
self.min_cpu_freq = f"{min_cpu_freq}Hz"
if max_cpu_freq == 0:
self.max_cpu_freq = "n/a"
else:
self.max_cpu_freq = f"{max_cpu_freq}Hz"
def serialize(
self,
serialization_type: str = "default",
) -> Union[Dict[str, Any], List[Dict[str, Any]]]:
"""
Serialize class to dict.
:param serialization_type: serialization type, defaults to "default"
:type serialization_type: str, optional
:return: serialized class
:rtype: Union[dict, List[dict]]
"""
result = {}
for key, value in self.__dict__.items():
if key in self._skip:
continue
if value is None:
continue
variable_name = re.sub(r"^_", "", key)
getter_value = value
try:
getter_value = getattr(self, variable_name)
except AttributeError:
log.warning(
f"Found f{key} attribute without {variable_name} getter.")
serialized_value = self._serialize_value(
getter_value,
serialization_type,
)
if serialized_value is not None:
result[variable_name] = serialized_value
return result
def report_deprecated(*args: str, **kwargs: str) -> Any:
log.warning(f"Call to deprecated function {func.__name__}.")
return func(*args, **kwargs)