multimodal/YOLOX/yolox/exp/base_exp.py

#!/usr/bin/env python3
# Copyright (c) Megvii Inc. All rights reserved.

import ast
import pprint
from abc import ABCMeta, abstractmethod
from typing import Dict, List, Tuple
from tabulate import tabulate

import torch
from torch.nn import Module

from yolox.utils import LRScheduler


class BaseExp(metaclass=ABCMeta):
    """Basic class for any experiment."""

    def __init__(self):
        self.seed = None
        self.output_dir = "./YOLOX_outputs"
        self.print_interval = 100
        self.eval_interval = 10
        self.dataset = None

    @abstractmethod
    def get_model(self) -> Module:
        pass

    @abstractmethod
    def get_dataset(self, cache: bool = False, cache_type: str = "ram"):
        pass

    @abstractmethod
    def get_data_loader(
        self, batch_size: int, is_distributed: bool
    ) -> Dict[str, torch.utils.data.DataLoader]:
        pass

    @abstractmethod
    def get_optimizer(self, batch_size: int) -> torch.optim.Optimizer:
        pass

    @abstractmethod
    def get_lr_scheduler(
        self, lr: float, iters_per_epoch: int, **kwargs
    ) -> LRScheduler:
        pass

    @abstractmethod
    def get_evaluator(self):
        pass

    @abstractmethod
    def eval(self, model, evaluator, weights):
        pass

    def __repr__(self):
        table_header = ["keys", "values"]
        exp_table = [
            (str(k), pprint.pformat(v))
            for k, v in vars(self).items()
            if not k.startswith("_")
        ]
        return tabulate(exp_table, headers=table_header, tablefmt="fancy_grid")

    def merge(self, cfg_list):
        assert len(cfg_list) % 2 == 0, f"length must be even, check value here: {cfg_list}"
        for k, v in zip(cfg_list[0::2], cfg_list[1::2]):
            # only update value with same key
            if hasattr(self, k):
                src_value = getattr(self, k)
                src_type = type(src_value)

                # pre-process input if source type is list or tuple
                if isinstance(src_value, (List, Tuple)):
                    v = v.strip("[]()")
                    v = [t.strip() for t in v.split(",")]

                    # find type of tuple
                    if len(src_value) > 0:
                        src_item_type = type(src_value[0])
                        v = [src_item_type(t) for t in v]

                if src_value is not None and src_type != type(v):
                    try:
                        v = src_type(v)
                    except Exception:
                        v = ast.literal_eval(v)
                setattr(self, k, v)