snakers4

FROM nvidia/cuda:8.0-cudnn6-devel

RUN apt-get update && apt-get install -y openssh-server
RUN mkdir /var/run/sshd
RUN echo 'root:YOUR_PASSWORD' | chpasswd
RUN sed -i 's/PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config

# SSH login fix. Otherwise user is kicked off after login
RUN sed 's@session\s*required\s*pam_loginuid.so@session optional pam_loginuid.so@g' -i /etc/pam.d/sshd

snakers4

import torchvision.models as models
import torch
import torch.nn as nn

class FineTuneModel(nn.Module):
    def __init__(self,
                 original_model,
                 arch,
                 num_classes,
                 freeze

snakers4

# add 7z tar and zip archivers
FROM nvidia/cuda:9.0-cudnn7-devel

RUN apt-get update && apt-get install -y openssh-server
RUN mkdir /var/run/sshd
RUN echo 'root:Ubuntu@41' | chpasswd
RUN sed -i 's/PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config

# SSH login fix. Otherwise user is kicked off after login
RUN sed 's@session\s*required\s*pam_loginuid.so@session optional pam_loginuid.so@g' -i /etc/pam.d/sshd

snakers4

import tqdm
import pandas as pd
import numpy as np
from multiprocessing import Pool
import os

# drop all the unknown points and all closed points
# for each SK_ID_CURR calculate the counts of time in each status
# normalize by the max len (we know of) in any of the meaningful statuses 

snakers4

import torch
import torch.nn as nn
from torch.autograd import Variable

class NaiveClassifier(nn.Module):
    def __init__(self,
                 cat_sizes=None,
                 numerical_features=117,
                 mlp_sizes=[1024,2048,1024,512,256,128,2],
                 embedding_factor=3,

snakers4

# add 7z tar and zip archivers
FROM nvidia/cuda:9.0-cudnn7-devel

# https://docs.docker.com/engine/examples/running_ssh_service/
RUN apt-get update && apt-get install -y openssh-server
RUN mkdir /var/run/sshd
RUN echo 'root:Ubuntu@41' | chpasswd
RUN sed -i 's/PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
RUN sed -i 's/#PasswordAuthentication yes/PasswordAuthentication no/' /etc/ssh/sshd_config
RUN mkdir ~/.ssh/

snakers4

import torch
import torch.nn as nn
import torch.nn.functional as F
from utils.PyTorchSSIM import SSIM as SSIMLoss


class AttackerLoss(nn.Module):
    def __init__(self,
                 gamma=0.9,
                 use_running_mean=False,

snakers4

# BASIC SYSTEM SETUP

# First donwload Ubuntu iso file from https://www.ubuntu.com/download/desktop
# Use 16.04 LTS (17 is also ok, but it's better to use LTS versions, also 18 will be very mature in terms of systemd)

# Dowload Linux live USB creator and install the iso to your USB stick https://www.linuxliveusb.com

# Boot your system, go to BIOS on boot (usually Del) or boot menu (usually F12) and choose your USB stick as boot medium
# Install Linux (these steps can be omitted if clean Ubuntu installation is provided as service by admins / cloud provider / etc)
# Minor trick unplug ALL of your hard disks (unless you are an avanced user) except for the disk for your system

snakers4

python3 train.py \
    --epochs 30 --batch-size 512 --seed 42 \
    --model_type fc_conv --dataset_type fmnist --latent_space_size 10 \
    --do_augs False \
    --lr 1e-3 --m1 40 --m2 50 \
    --optimizer adam \
    --do_running_mean False --img_loss_weight 1.0 --kl_loss_weight 1.0 \
    --image_loss_type bce --ssim_window_size 5 \
    --print-freq 10 \
    --lognumber fmnist_fc_conv_l10_rebalance_no_norm \

snakers4

from tqdm import tqdm
import numpy as np
import pandas as pd
from multiprocessing import Pool

def _apply_df(args):
    df, func, num, kwargs = args
    return num, df.apply(func, **kwargs)

def apply_by_multiprocessing(df,func,**kwargs):