# Data Parallel Control (dpctl)
#
# Copyright 2020-2022 Intel Corporation
#
# 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.
from contextlib import contextmanager
from os import environ, getenv
from platform import system as sys_platform
__doc__ = (
"Implementation module of :class:`dpctl.utils.onetrace_enabled` "
"context manager."
)
_UNCHECKED = sys_platform() == "Linux"
del sys_platform
[docs]@contextmanager
def onetrace_enabled():
"""Enable `onetrace` collection for kernels executed in this context.
N.B.: Proper working of this utility assumes that Python interpreter
has been launched by `onetrace` tool from intel/pti-gpu project.
:Example:
Launch the Python interpreter using `onetrace` tool: ::
$ onetrace --conditional-collection -v -t --demangle python app.py
Now using the context manager in the Python sessions enables
data collection and its output for every offloaded kernel ::
import dpctl.tensor as dpt
from dpctl.utils import onetrace_enabled
# onetrace output reporting on execution of the kernel
# should be seen, starting with "Device Timeline"
with onetrace_enabled():
dpt.arange(100, dtype='int16')
"""
global _UNCHECKED
if _UNCHECKED:
_UNCHECKED = False
if not (
getenv("PTI_ENABLE", None) == "1"
and "onetrace_tool" in getenv("LD_PRELOAD", "")
):
import warnings
warnings.warn(
"It looks like Python interpreter was not started using "
"`onetrace` utility. Using `onetrace_enabled` may have "
"no effect. See `onetrace_enabled.__doc__` for usage.",
RuntimeWarning,
stacklevel=2,
)
_env_var_name = "PTI_ENABLE_COLLECTION"
saved = getenv(_env_var_name, None)
try:
environ[_env_var_name] = "1"
yield
finally:
if saved is None:
del environ[_env_var_name]
else:
environ[_env_var_name] = saved