KellenSunderland

#include <iostream>
#include <utility>
#include <vector>
#include <cstring>


using namespace std;

class MyType {
public:

KellenSunderland

import mxnet as mx
import numpy as np
import importlib
from collections import namedtuple
import time

def runMx(ctx,mod,data,num_batches,runType):
    print('%s MXNet' % (runType))
    Batch = namedtuple('Batch', ['data'])
    t = 0

KellenSunderland

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#

KellenSunderland

FROM kellens/build.ubuntu_gpu_tensorrt:latest

WORKDIR /work

RUN wget https://gist.githubusercontent.com/KellenSunderland/686522830475dfc7073b5d7a97e89d24/raw/a0b12e63b5fbf51f4c2794a9a8dae22a2ac8cab1/run_model.py && \
    wget https://raw.githubusercontent.com/apache/incubator-mxnet/master/example/fcn-xs/symbol_fcnxs.py

RUN git clone --recursive https://github.com/apache/incubator-mxnet.git --branch v1.4.x mxnet-v1.4.0-cmake && \
    mkdir -p /work/mxnet-v1.4.0-cmake/lib/ && \
    git clone --recursive https://github.com/apache/incubator-mxnet.git --branch v1.4.x mxnet-v1.4.0-make && \

KellenSunderland

#!/bin/bash

wget https://gist.githubusercontent.com/KellenSunderland/219fc25d7f796ae5442cfe162d27cc9c/raw/d9015ebd878391930b5ba186ab4ba77042eee943/Dockerfile
nvidia-docker build -f Dockerfile . -t mxnet/regression
nvidia-docker run -ti -e "PYTHONPATH=/work/mxnet-v1.4.0-cmake/python" mxnet/regression python2 run_model.py
nvidia-docker run -ti -e "PYTHONPATH=/work/mxnet-v1.3.0-cmake/python" mxnet/regression python2 run_model.py
nvidia-docker run -ti -e "PYTHONPATH=/work/mxnet-v1.2.0-cmake/python" mxnet/regression python2 run_model.py
nvidia-docker run -ti -e "PYTHONPATH=/work/mxnet-v1.4.0-cmake-profiler/python" mxnet/regression python2 run_model.py
nvidia-docker run -ti -e "PYTHONPATH=/work/mxnet-v1.4.0-make/python" mxnet/regression python2 run_model.py

KellenSunderland

FROM UBUNTU 18.04

sudo apt-get install tmux htop libssl-dev
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub && sudo apt update
sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo apt update
sudo apt install -y cuda
wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
sudo dpkg -i nvidia-machine-learning-repo-*.deb

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    FILE SIZE        VM SIZE    
 --------------  -------------- 
  73.8%   279Mi  75.2%   279Mi    [section .nv_fatbin]
   7.5%  28.5Mi   4.9%  18.4Mi    [46244 Others]
   1.1%  4.03Mi   1.0%  3.58Mi    mshadow::MapExp<>()
   0.9%  3.56Mi   1.0%  3.56Mi    __sti____cudaRegisterAll()
   0.9%  3.37Mi   0.9%  3.36Mi    mxnet::op::ElemwiseBinaryOp::RspRspOp<>()
   0.0%  2.70Ki   0.7%  2.78Mi    precalc_xorwow_matrix
   0.0%  2.71Ki   0.7%  2.78Mi    precalc_xorwow_offset_matrix
   0.7%  2.78Mi   0.7%  2.78Mi    [section .gcc_except_table]