def METHOD_NAME(csv_dict, metrics_log_file_path, raw_metrics_file_path):
    if metrics_log_file_path is None or raw_metrics_file_path is None:
        return
    with open(metrics_log_file_path, 'r') as logfile:
        lines = logfile.readlines()
    metrics_dict_list = []
    pattern = re.compile(" TS_METRICS | MODEL_METRICS ")
    for line in lines:
        if pattern.search(line):
            segments = line.split("|")
            name, unit, value = parse_segments_0(segments[0])
            if name is None:
                continue
            dimensions = parse_segments_1(csv_dict, segments[1])
            timestamp = parse_segments_2(segments[2])
            metrics_dict_list.append({
                "MetricName": '{}_{}'.format(csv_dict["Model"], name),
                "Dimensions": dimensions,
                "Unit": unit,
                "Value": float(value),
                "Timestamp": timestamp
            })
    with open(raw_metrics_file_path, 'w') as raw_file:
        json.dump(metrics_dict_list, raw_file, indent=4)