PaddleX/paddlex/modules/base/predictor/kernel_option.py

# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
#
# 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 functools import wraps, partial

from ....utils import logging


def register(register_map, key):
    """register the option setting func"""

    def decorator(func):
        register_map[key] = func

        @wraps(func)
        def wrapper(self, *args, **kwargs):
            return func(self, *args, **kwargs)

        return wrapper

    return decorator


class PaddleInferenceOption(object):
    """Paddle Inference Engine Option"""

    SUPPORT_RUN_MODE = (
        "paddle",
        "trt_fp32",
        "trt_fp16",
        "trt_int8",
        "mkldnn",
        "mkldnn_bf16",
    )
    SUPPORT_DEVICE = ("gpu", "cpu", "npu", "xpu", "mlu")
    _REGISTER_MAP = {}

    register2self = partial(register, _REGISTER_MAP)

    def __init__(self, **kwargs):
        super().__init__()
        self._cfg = {}
        self._init_option(**kwargs)

    def _init_option(self, **kwargs):
        for k, v in kwargs.items():
            if k not in self._REGISTER_MAP:
                raise Exception(
                    f"{k} is not supported to set! The supported option is: \
{list(self._REGISTER_MAP.keys())}"
                )
            self._REGISTER_MAP.get(k)(self, v)
        for k, v in self._get_default_config().items():
            self._cfg.setdefault(k, v)

    def _get_default_config(cls):
        """get default config"""
        return {
            "run_mode": "paddle",
            "batch_size": 1,
            "device": "gpu",
            "device_id": 0,
            "min_subgraph_size": 3,
            "shape_info_filename": None,
            "trt_calib_mode": False,
            "cpu_threads": 1,
            "trt_use_static": False,
            "enable_new_ir": True,
        }

    @register2self("run_mode")
    def set_run_mode(self, run_mode: str):
        """set run mode"""
        if run_mode not in self.SUPPORT_RUN_MODE:
            support_run_mode_str = ", ".join(self.SUPPORT_RUN_MODE)
            raise ValueError(
                f"`run_mode` must be {support_run_mode_str}, but received {repr(run_mode)}."
            )
        self._cfg["run_mode"] = run_mode

    @register2self("batch_size")
    def set_batch_size(self, batch_size: int):
        """set batch size"""
        if not isinstance(batch_size, int) or batch_size < 1:
            raise Exception()
        self._cfg["batch_size"] = batch_size

    @register2self("device")
    def set_device(self, device_setting: str):
        """set device"""
        if len(device_setting.split(":")) == 1:
            device = device_setting.split(":")[0]
            device_id = 0
        else:
            assert len(device_setting.split(":")) == 2
            device = device_setting.split(":")[0]
            device_id = device_setting.split(":")[1].split(",")[0]
            logging.warning(f"The device id has been set to {device_id}.")

        if device.lower() not in self.SUPPORT_DEVICE:
            support_run_mode_str = ", ".join(self.SUPPORT_DEVICE)
            raise ValueError(
                f"`device` must be {support_run_mode_str}, but received {repr(device)}."
            )
        self._cfg["device"] = device.lower()
        self._cfg["device_id"] = int(device_id)

    @register2self("min_subgraph_size")
    def set_min_subgraph_size(self, min_subgraph_size: int):
        """set min subgraph size"""
        if not isinstance(min_subgraph_size, int):
            raise Exception()
        self._cfg["min_subgraph_size"] = min_subgraph_size

    @register2self("shape_info_filename")
    def set_shape_info_filename(self, shape_info_filename: str):
        """set shape info filename"""
        self._cfg["shape_info_filename"] = shape_info_filename

    @register2self("trt_calib_mode")
    def set_trt_calib_mode(self, trt_calib_mode):
        """set trt calib mode"""
        self._cfg["trt_calib_mode"] = trt_calib_mode

    @register2self("cpu_threads")
    def set_cpu_threads(self, cpu_threads):
        """set cpu threads"""
        if not isinstance(cpu_threads, int) or cpu_threads < 1:
            raise Exception()
        self._cfg["cpu_threads"] = cpu_threads

    @register2self("trt_use_static")
    def set_trt_use_static(self, trt_use_static):
        """set trt use static"""
        self._cfg["trt_use_static"] = trt_use_static

    @register2self("enable_new_ir")
    def set_enable_new_ir(self, enable_new_ir: bool):
        """set run mode"""
        self._cfg["enable_new_ir"] = enable_new_ir

    def get_support_run_mode(self):
        """get supported run mode"""
        return self.SUPPORT_RUN_MODE

    def get_support_device(self):
        """get supported device"""
        return self.SUPPORT_DEVICE

    def get_device(self):
        """get device"""
        return f"{self._cfg['device']}:{self._cfg['device_id']}"

    def __str__(self):
        return ",  ".join([f"{k}: {v}" for k, v in self._cfg.items()])

    def __getattr__(self, key):
        if key not in self._cfg:
            raise Exception()
        return self._cfg.get(key)