ihoromi4

import os
import zipfile
import numpy as np
import cv2


def images_to_zip(images: list, out_filename: str):
    if os.path.exists(out_filename):
        print('File', out_filename, 'already exists. Abort.')
        return

ihoromi4

def seed_everything(seed: int):
    import random, os
    import numpy as np
    import torch
    
    random.seed(seed)
    os.environ['PYTHONHASHSEED'] = str(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)

ihoromi4

from torch import nn


class NN(nn.Module):
    def device(self):
        return next(self.parameters()).device

ihoromi4

import functools
import operator
from torch import nn


def get_n_params(model: nn.Module) -> int:
    return sum((functools.reduce(operator.mul, p.size()) for p in model.parameters()))

ihoromi4

import tensorflow as tf
from keras.backend.tensorflow_backend

config = tf.ConfigProto(device_count={'CPU': 1})
session = tf.Session(config=config)
tensorflow_backend.set_session(session)

ihoromi4

package main

import (
    "encoding/hex"
    "log"
    "net"
    "time"
)

const (