def max_available_cores() -> int:
"""
:return: the maximum number of physical cores detected on the system
"""
if cpu_details is not None:
_LOGGER.debug("retrieving physical core count per socket "
"from deepsparse.cpu.cpu_details()")
return cpu_details()[0]
_LOGGER.debug("retrieving physical core count using psutil")
physical_cores = psutil.cpu_count(logical=False)
return physical_cores if physical_cores else -1
def __init__(
self,
model_info: ModelInfo,
batch_size: int = 1,
num_cores: Optional[int] = None,
iterations_per_check: int = 10,
warmup_iterations_per_check: int = 5,
):
self._batch_size = batch_size
self._iterations_per_check = iterations_per_check
self._warmup_iterations_per_check = warmup_iterations_per_check
# try grabbing default max cores if needed; for tracking purposes
try:
from deepsparse.cpu import cpu_details
self._num_cores = num_cores or cpu_details()[0]
except Exception:
self._num_cores = num_cores
super().__init__(model_info)
except Exception:
Model = object
File = object
try:
# flake8: noqa
from deepsparse.cpu import cpu_details
from deepsparse.lib import init_deepsparse_lib
from deepsparse.version import *
except ImportError:
raise ImportError("Unable to import deepsparse python apis. "
"Please contact [email protected]")
__all__ = ["Engine", "compile_model", "benchmark_model", "analyze_model"]
CORES_PER_SOCKET, AVX_TYPE, VNNI = cpu_details()
LIB = init_deepsparse_lib()
def _model_to_path(model: Union[str, Model, File]) -> str:
if not model:
raise ValueError(
"model must be a path, sparsezoo.Model, or sparsezoo.File")
if isinstance(model, str):
pass
elif Model is not object and isinstance(model, Model):
# default to the main onnx file for the model
model = model.onnx_file.downloaded_path()
elif File is not object and isinstance(model, File):
import time
import onnxruntime
from deepsparse import compile_model, cpu
from deepsparse.benchmark import BenchmarkResults
from deepsparse.utils import (
generate_random_inputs,
get_input_names,
get_output_names,
override_onnx_batch_size,
verify_outputs,
)
CORES_PER_SOCKET, AVX_TYPE, _ = cpu.cpu_details()
def parse_args():
parser = argparse.ArgumentParser(
description=(
"Benchmark an ONNX model, comparing between DeepSparse and ONNXRuntime"
)
)
parser.add_argument(
"onnx_filepath",
type=str,
help="The full filepath of the ONNX model file being benchmarked",
)