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Source code for mmpretrain.utils.analyze

# Copyright (c) OpenMMLab. All rights reserved.
import json


[docs]def load_json_log(json_log): """load and convert json_logs to log_dicts. Args: json_log (str): The path of the json log file. Returns: dict: The result dict contains two items, "train" and "val", for the training log and validate log. Example: An example output: .. code-block:: python { 'train': [ {"lr": 0.1, "time": 0.02, "epoch": 1, "step": 100}, {"lr": 0.1, "time": 0.02, "epoch": 1, "step": 200}, {"lr": 0.1, "time": 0.02, "epoch": 1, "step": 300}, ... ] 'val': [ {"accuracy/top1": 32.1, "step": 1}, {"accuracy/top1": 50.2, "step": 2}, {"accuracy/top1": 60.3, "step": 2}, ... ] } """ log_dict = dict(train=[], val=[]) with open(json_log, 'r') as log_file: for line in log_file: log = json.loads(line.strip()) # A hack trick to determine whether the line is training log. mode = 'train' if 'lr' in log else 'val' log_dict[mode].append(log) return log_dict
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