new structure
weishengyu
parent
14348acafb
commit
d675b0203c
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def build_engine(config):
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pass
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from ..processor import build_processor
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class POPEngine:
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def __init__(self, config):
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self.processor_list = []
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last_algo_type = "start"
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for processor_config in config["Processors"]:
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processor_config["last_algo_type"] = last_algo_type
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self.processor_list.append(build_processor(processor_config))
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last_algo_type = processor_config["type"]
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def process(self, x):
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for processor in self.processor_list:
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x = processor.process(x)
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return x
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from ..engine import build_engine
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from ..utils import config
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def main():
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args = config.parse_args()
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config_dict = config.get_config(
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args.config, overrides=args.override, show=False)
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config_dict.profiler_options = args.profiler_options
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engine = build_engine(config_dict)
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if __name__ == '__main__':
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main()
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import cv2
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class SingleImageTask:
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def __init__(self, config, engine):
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self.image_path = config.get("image_path")
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self.engine = engine
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def run(self):
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image = cv2.imread(self.image_path)
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output = self.engine.process(image)
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print(output)
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from abc import ABC, abstractmethod
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from algo_mod import build_algo_mod
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from searcher import build_searcher
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from data_processor import build_data_processor
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def build_processor(config):
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processor_type = config.get("processor_type")
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if processor_type == "algo_mod":
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return build_algo_mod(config)
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elif processor_type == "searcher":
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return build_searcher(config)
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elif processor_type == "data_processor":
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return build_data_processor(config)
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else:
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raise NotImplemented("processor_type {} not implemented.".format(processor_type))
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class BaseProcessor(ABC):
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@abstractmethod
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def __init__(self, config):
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pass
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@abstractmethod
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def process(self, input_data):
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pass
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from .fake_cls import FakeClassifier
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def build_algo_mod(config):
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algo_name = config.get("algo_name")
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if algo_name == "fake_clas":
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return FakeClassifier(config)
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from .. import BaseProcessor
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class FakeClassifier(BaseProcessor):
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def __init__(self, config):
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pass
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def process(self, input_data):
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pass
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class FakeDetector:
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def __init__(self):
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pass
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def predict(self):
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pass
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from paddle.inference import create_predictor, Config
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# from bbox_cropper import
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def build_data_processor(config):
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return
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from .. import BaseProcessor
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class BBoxCropper(BaseProcessor):
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def __init__(self, config):
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pass
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def process(self, input_data):
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pass
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from .. import BaseProcessor
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class ImageReader(BaseProcessor):
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def __init__(self):
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pass
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def process(self, input_data):
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pass
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def build_searcher(config):
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pass
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# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import copy
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import argparse
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import yaml
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from utils import logger
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__all__ = ['get_config']
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class AttrDict(dict):
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def __getattr__(self, key):
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return self[key]
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def __setattr__(self, key, value):
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if key in self.__dict__:
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self.__dict__[key] = value
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else:
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self[key] = value
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def __deepcopy__(self, content):
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return copy.deepcopy(dict(self))
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def create_attr_dict(yaml_config):
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from ast import literal_eval
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for key, value in yaml_config.items():
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if type(value) is dict:
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yaml_config[key] = value = AttrDict(value)
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if isinstance(value, str):
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try:
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value = literal_eval(value)
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except BaseException:
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pass
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if isinstance(value, AttrDict):
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create_attr_dict(yaml_config[key])
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else:
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yaml_config[key] = value
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def parse_config(cfg_file):
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"""Load a config file into AttrDict"""
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with open(cfg_file, 'r') as fopen:
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yaml_config = AttrDict(yaml.load(fopen, Loader=yaml.SafeLoader))
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create_attr_dict(yaml_config)
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return yaml_config
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def print_dict(d, delimiter=0):
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"""
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Recursively visualize a dict and
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indenting acrrording by the relationship of keys.
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"""
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placeholder = "-" * 60
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for k, v in sorted(d.items()):
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if isinstance(v, dict):
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logger.info("{}{} : ".format(delimiter * " ", k))
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print_dict(v, delimiter + 4)
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elif isinstance(v, list) and len(v) >= 1 and isinstance(v[0], dict):
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logger.info("{}{} : ".format(delimiter * " ", k))
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for value in v:
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print_dict(value, delimiter + 4)
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else:
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logger.info("{}{} : {}".format(delimiter * " ", k, v))
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if k.isupper():
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logger.info(placeholder)
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def print_config(config):
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"""
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visualize configs
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Arguments:
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config: configs
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"""
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logger.advertise()
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print_dict(config)
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def override(dl, ks, v):
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"""
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Recursively replace dict of list
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Args:
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dl(dict or list): dict or list to be replaced
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ks(list): list of keys
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v(str): value to be replaced
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"""
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def str2num(v):
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try:
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return eval(v)
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except Exception:
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return v
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assert isinstance(dl, (list, dict)), ("{} should be a list or a dict")
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assert len(ks) > 0, ('lenght of keys should larger than 0')
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if isinstance(dl, list):
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k = str2num(ks[0])
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if len(ks) == 1:
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assert k < len(dl), ('index({}) out of range({})'.format(k, dl))
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dl[k] = str2num(v)
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else:
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override(dl[k], ks[1:], v)
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else:
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if len(ks) == 1:
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# assert ks[0] in dl, ('{} is not exist in {}'.format(ks[0], dl))
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if not ks[0] in dl:
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print('A new filed ({}) detected!'.format(ks[0], dl))
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dl[ks[0]] = str2num(v)
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else:
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override(dl[ks[0]], ks[1:], v)
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def override_config(config, options=None):
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"""
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Recursively override the config
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Args:
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config(dict): dict to be replaced
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options(list): list of pairs(key0.key1.idx.key2=value)
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such as: [
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'topk=2',
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'VALID.transforms.1.ResizeImage.resize_short=300'
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]
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Returns:
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config(dict): replaced config
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"""
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if options is not None:
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for opt in options:
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assert isinstance(opt, str), (
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"option({}) should be a str".format(opt))
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assert "=" in opt, (
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"option({}) should contain a ="
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"to distinguish between key and value".format(opt))
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pair = opt.split('=')
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assert len(pair) == 2, ("there can be only a = in the option")
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key, value = pair
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keys = key.split('.')
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override(config, keys, value)
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return config
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def get_config(fname, overrides=None, show=False):
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"""
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Read config from file
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"""
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assert os.path.exists(fname), (
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'config file({}) is not exist'.format(fname))
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config = parse_config(fname)
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override_config(config, overrides)
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if show:
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print_config(config)
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return config
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def parse_args():
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parser = argparse.ArgumentParser("generic-image-rec train script")
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parser.add_argument(
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'-c',
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'--config',
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type=str,
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default='configs/config.yaml',
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help='config file path')
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parser.add_argument(
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'-o',
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'--override',
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action='append',
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default=[],
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help='config options to be overridden')
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parser.add_argument(
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'-p',
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'--profiler_options',
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type=str,
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default=None,
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help='The option of profiler, which should be in format \"key1=value1;key2=value2;key3=value3\".'
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)
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parser.add_argument(
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'-t',
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'--task_config',
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type=str,
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default="examples/task.yaml",
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help='task config file path'
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)
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args = parser.parse_args()
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return args
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# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import sys
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import logging
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import datetime
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import paddle.distributed as dist
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_logger = None
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def init_logger(name='root', log_file=None, log_level=logging.INFO):
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"""Initialize and get a logger by name.
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If the logger has not been initialized, this method will initialize the
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logger by adding one or two handlers, otherwise the initialized logger will
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be directly returned. During initialization, a StreamHandler will always be
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added. If `log_file` is specified a FileHandler will also be added.
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Args:
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name (str): Logger name.
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log_file (str | None): The log filename. If specified, a FileHandler
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will be added to the logger.
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log_level (int): The logger level. Note that only the process of
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rank 0 is affected, and other processes will set the level to
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"Error" thus be silent most of the time.
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Returns:
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logging.Logger: The expected logger.
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"""
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global _logger
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assert _logger is None, "logger should not be initialized twice or more."
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_logger = logging.getLogger(name)
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formatter = logging.Formatter(
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'[%(asctime)s] %(name)s %(levelname)s: %(message)s',
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datefmt="%Y/%m/%d %H:%M:%S")
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stream_handler = logging.StreamHandler(stream=sys.stdout)
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stream_handler.setFormatter(formatter)
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_logger.addHandler(stream_handler)
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if log_file is not None and dist.get_rank() == 0:
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log_file_folder = os.path.split(log_file)[0]
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os.makedirs(log_file_folder, exist_ok=True)
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file_handler = logging.FileHandler(log_file, 'a')
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file_handler.setFormatter(formatter)
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_logger.addHandler(file_handler)
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if dist.get_rank() == 0:
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_logger.setLevel(log_level)
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else:
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_logger.setLevel(logging.ERROR)
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def log_at_trainer0(log):
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"""
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logs will print multi-times when calling Fleet API.
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Only display single log and ignore the others.
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"""
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def wrapper(fmt, *args):
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if dist.get_rank() == 0:
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log(fmt, *args)
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return wrapper
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@log_at_trainer0
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def info(fmt, *args):
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_logger.info(fmt, *args)
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@log_at_trainer0
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def debug(fmt, *args):
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_logger.debug(fmt, *args)
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@log_at_trainer0
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def warning(fmt, *args):
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_logger.warning(fmt, *args)
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@log_at_trainer0
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def error(fmt, *args):
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_logger.error(fmt, *args)
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def scaler(name, value, step, writer):
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"""
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This function will draw a scalar curve generated by the visualdl.
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Usage: Install visualdl: pip3 install visualdl==2.0.0b4
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and then:
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visualdl --logdir ./scalar --host 0.0.0.0 --port 8830
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to preview loss corve in real time.
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"""
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if writer is None:
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return
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writer.add_scalar(tag=name, step=step, value=value)
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def advertise():
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"""
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Show the advertising message like the following:
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===========================================================
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== PaddleClas is powered by PaddlePaddle ! ==
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===========================================================
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== ==
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== For more info please go to the following website. ==
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== ==
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== https://github.com/PaddlePaddle/PaddleClas ==
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===========================================================
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"""
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copyright = "PaddleClas is powered by PaddlePaddle !"
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ad = "For more info please go to the following website."
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website = "https://github.com/PaddlePaddle/PaddleClas"
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AD_LEN = 6 + len(max([copyright, ad, website], key=len))
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info("\n{0}\n{1}\n{2}\n{3}\n{4}\n{5}\n{6}\n{7}\n".format(
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"=" * (AD_LEN + 4),
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"=={}==".format(copyright.center(AD_LEN)),
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"=" * (AD_LEN + 4),
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"=={}==".format(' ' * AD_LEN),
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"=={}==".format(ad.center(AD_LEN)),
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"=={}==".format(' ' * AD_LEN),
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"=={}==".format(website.center(AD_LEN)),
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"=" * (AD_LEN + 4), ))
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