# Copyright 2022 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""JitConfig for compile."""
[文档]class JitConfig:
"""
Jit config for compile.
Note:
This is an experimental function that is subject to change or deletion.
Args:
jit_level (str): Option for argument `level` for Optimization of lift graph.
Supports ["O0", "O1", "O2"]. Default: "O1".
- "O0": Basic optimization.
- "O1": Manual optimization.
- "O2": Manual optimization and graph computation fusion.
task_sink (bool): Determines whether to pass the data through dataset channel. Default: True.
**kwargs (dict): A dictionary of keyword arguments that the class needs.
Examples:
>>> from mindspore import JitConfig
>>>
>>> jitconfig = JitConfig(jit_level="O1")
>>> net = LeNet5()
>>>
>>> net.set_jit_config(jitconfig)
"""
def __init__(self, jit_level="O1", task_sink=True, **kwargs):
if jit_level not in ["O0", "O1", "O2"]:
raise ValueError("For 'jit_level' must be one of ['O0', 'O1', 'O2'].")
if not isinstance(task_sink, bool):
raise TypeError("For 'task_sink' must be bool.")
self.jit_config_dict = dict()
self.jit_config_dict["jit_level"] = jit_level
self.jit_config_dict["task_sink"] = str(int(task_sink))
for key, value in kwargs.items():
self.jit_config_dict[key] = value