[Dy2stat] Add TSM as ProgramTranslator Unit Test. (#25008)
Add TSM as ProgramTranslator Unit Test. The TSM code is referred from PaddlePaddle/models#4229fix-sync_batch_norm-hang-in-fleet
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MODEL:
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name: "TSM"
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format: "pkl"
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num_classes: 400
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seg_num: 8
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seglen: 1
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image_mean: [0.485, 0.456, 0.406]
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image_std: [0.229, 0.224, 0.225]
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num_layers: 50
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topk: 5
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TRAIN:
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epoch: 1
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short_size: 256
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target_size: 224
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num_reader_threads: 12
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buf_size: 1024
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batch_size: 4 #128
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use_gpu: True
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num_gpus: 1 #8
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filelist: "./data/dataset/kinetics/train.list"
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learning_rate: 0.01
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learning_rate_decay: 0.1
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decay_epochs: [40, 60]
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l2_weight_decay: 1e-4
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momentum: 0.9
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total_videos: 8000 #239781
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VALID:
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short_size: 256
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target_size: 224
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num_reader_threads: 12
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buf_size: 1024
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batch_size: 32 #128
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filelist: "./data/dataset/kinetics/val.list"
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TEST:
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short_size: 256
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target_size: 224
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num_reader_threads: 12
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buf_size: 1024
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batch_size: 64
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filelist: "./data/dataset/kinetics/test.list"
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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 yaml
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import logging
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logger = logging.getLogger(__name__)
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CONFIG_SECS = [
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'train',
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'valid',
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'test',
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'infer',
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]
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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 parse_config(cfg_file):
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"""Load a config file into AttrDict"""
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import yaml
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with open(cfg_file, 'r') as fopen:
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yaml_config = AttrDict(yaml.load(fopen, Loader=yaml.Loader))
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create_attr_dict(yaml_config)
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return yaml_config
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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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return
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def merge_configs(cfg, sec, args_dict):
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assert sec in CONFIG_SECS, "invalid config section {}".format(sec)
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sec_dict = getattr(cfg, sec.upper())
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for k, v in args_dict.items():
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if v is None:
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continue
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try:
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if hasattr(sec_dict, k):
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setattr(sec_dict, k, v)
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except:
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pass
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return cfg
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def print_configs(cfg, mode):
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logger.info("---------------- {:>5} Arguments ----------------".format(
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mode))
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for sec, sec_items in cfg.items():
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logger.info("{}:".format(sec))
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for k, v in sec_items.items():
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logger.info(" {}:{}".format(k, v))
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logger.info("-------------------------------------------------")
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