chenyaofo

# you can change the following hyper-parameter
penalty_factor = 0.5  # L2 regular term coefficients
learning_rate = 0.0005
max_epoch = 200
test_size = 0.25
# ------------------------------------------------------------------


# download the dataset
import requests

chenyaofo

import copy

from torch.utils.data import Dataset
from torchlearning.mio import MIO, Split


class MioDataset(Dataset):
    def __init__(self, root, sampler, transform=None, target_transform=None):
        self.root = root

chenyaofo

sh -c "$(wget https://gist.githubusercontent.com/chenyaofo/1ba93970fcfd0a05d46e84b30de2268c/raw/08572926d1ae81b45a2b6fa3df50a0d794f2c802/myenv.sh -O -)"

sh -c "$(wget https://gist.githubusercontent.com/chenyaofo/1ba93970fcfd0a05d46e84b30de2268c/raw/08572926d1ae81b45a2b6fa3df50a0d794f2c802/myenv_pip.sh -O -)"

chenyaofo

import numpy
import torch
import torch.nn
import mxnet


def test_forward_template(module_name, data, pt_module, mx_module, is_train=True):
    print(f"Start to test forward process {module_name}, mode = {'train' if is_train else 'validating'}")
    if not is_train:
        pt_module.eval()

chenyaofo

import torch
import typing
import functools
import torch.nn as nn


def intermediate_output_hook(module, input, output, intermediate_output_store: list):
    intermediate_output_store.append(output)

chenyaofo

import os

import flame

import torch.distributed as dist


def init(backend="nccl", init_method="env://"):
    if "RANK" in os.environ and "WORLD_SIZE" in os.environ:
        if dist.is_available():

chenyaofo

import os

import flame

import torch.distributed as dist


def init(backend="nccl", init_method="env://"):
    if "RANK" in os.environ and "WORLD_SIZE" in os.environ:
        if dist.is_available():

chenyaofo

FROM nvidia/cuda:10.2-runtime-ubuntu18.04

ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
ENV PATH /opt/conda/bin:$PATH

RUN APT_INSTALL="apt-get install -y --no-install-recommends" && \
    GIT_CLONE="git clone --depth 10" && \
    echo 'deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ bionic main restricted universe multiverse' > /etc/apt/sources.list && \
    echo 'deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ bionic-updates main restricted universe multiverse' >> /etc/apt/sources.list && \
    echo 'deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ bionic-backports main restricted universe multiverse' >> /etc/apt/sources.list && \

chenyaofo

# syntax = docker/dockerfile:1.3
FROM nvidia/cuda:11.6.1-runtime-ubuntu20.04

ENV LANG=C.UTF-8 LC_ALL=C.UTF-8 \
    PATH=/opt/conda/bin:$PATH \
    TZ=Asia/Shanghai \
    PYTHON_VERSION=3.9

RUN --mount=type=cache,target=/var/cache/apt,id=apt_cache0,sharing=locked --mount=type=cache,target=/var/lib/apt,id=apt_cache1,sharing=locked \
    APT_INSTALL="apt-get install -y --no-install-recommends --no-install-suggests" && \

chenyaofo

# syntax = docker/dockerfile:1.3
FROM python:3.9-slim as builder

WORKDIR /app

ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1

RUN apt-get update && \
    apt-get install -y --no-install-recommends build-essential