def test_custom_separator(nested_dict_config):
use_custom_separator("-")
config = Config.from_dict(nested_dict_config)
config.d = Config.from_dict({"d": False})
assert config.identifier == "10-10-1x2x3-a-no_d"
use_default_separator()
config = Config.from_dict(nested_dict_config)
config.d = Config.from_dict({"d": False})
assert config.identifier == "10|10|1x2x3|a|no_d"
def test_custom_separator(nested_dict_config):
use_custom_separator("-")
config = Config.from_dict(nested_dict_config)
config.d = Config.from_dict({"d": False})
assert config.identifier == "10-10-1x2x3-a-no_d"
use_default_separator()
config = Config.from_dict(nested_dict_config)
config.d = Config.from_dict({"d": False})
assert config.identifier == DEFAULT_SEPARATOR.join(
"10 10 1x2x3 a no_d".split())
import argparse
import logging
import os
import mag
import numpy as np
import pandas as pd
import torch
from dataset import get_test_set
from loops import infer
from mag.experiment import Experiment
from misc import target_columns, input_columns
from model import get_model_optimizer
from torch.utils.data import DataLoader
from transformers import BertTokenizer, RobertaTokenizer
mag.use_custom_separator("-")
parser = argparse.ArgumentParser()
parser.add_argument("--experiment", type=str, required=True)
parser.add_argument("--checkpoint", type=str, required=True)
parser.add_argument("--bert_model", type=str, required=True)
parser.add_argument("--dataframe", type=str, required=True)
parser.add_argument("--output_dir", type=str, required=True)
args = parser.parse_args()
experiment = Experiment(resume_from=args.experiment)
config = experiment.config
logging.getLogger("transformers").setLevel(logging.ERROR)
