Files
Model-Optimizer/modelopt/torch/_deploy/_runtime/common.py
T

73 lines
2.3 KiB
Python

# SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
import time
from collections.abc import Callable
from pathlib import Path
def timeit(method: Callable) -> Callable:
"""This function is supposed to use as a decorator to measure the execution time of another function.
If the decorator is applied and no changes are done at the call site, this will print out the
timing information on the log console. If the call site wants to get the time info returned, they
should pass a dictionary named log_time like below-
(regular_returns, ...), func_exec_time = func(regular_params, ..., log_time={})
"""
def timed(*args, **kw):
ts = time.time()
result = method(*args, **kw)
te = time.time()
if "log_time" in kw:
name = kw.get("log_name", method.__name__.upper())
kw["log_time"][name] = (te - ts) * 1000
return result, kw["log_time"][name]
else:
logging.info(f"Execution time for {method.__name__}: {(te - ts):.4f}s")
return result
return timed
def init_logging() -> None:
logging.basicConfig(
format="%(asctime)s P%(process)d T%(thread)d %(levelname)-8s %(message)s",
level=logging.INFO,
datefmt="%Y-%m-%d %H:%M:%S",
)
def read_bytes(file_path: str | Path) -> bytes:
path = Path(file_path)
return path.read_bytes()
def read_string(file_path: str | Path) -> str:
path = Path(file_path)
return path.read_text()
def write_bytes(data: bytes, file_path: str | Path) -> None:
path = Path(file_path)
path.write_bytes(data)
def write_string(data: str, file_path: str | Path) -> None:
path = Path(file_path)
path.write_text(data)