notebook_utils.py

import os
from pathlib import Path

import io
import torch
import pickle

def print_models(base_path, model_string):
    print(model_string)

    for i in range(80):
        for e in range(50):
            exists = Path(os.path.join(base_path, f'models_diff/prior_diff_real_checkpoint{model_string}_n_{i}_epoch_{e}.cpkt')).is_file()
            if exists:
                print(os.path.join(base_path, f'models_diff/prior_diff_real_checkpoint{model_string}_n_{i}_epoch_{e}.cpkt'))
        print()

class CustomUnpickler(pickle.Unpickler):
    def find_class(self, module, name):
        if name == 'Manager':
            from settings import Manager
            return Manager
        try:
            return self.find_class_cpu(module, name)
        except:
            return None

    def find_class_cpu(self, module, name):
        if module == 'torch.storage' and name == '_load_from_bytes':
            return lambda b: torch.load(io.BytesIO(b), map_location='cpu')
        else:
            return super().find_class(module, name)