soumith

import torch
import torch.nn as nn
import torch.nn.functional as F

class Model(nn.Module):
  def __init__(self):
    super(Model, self).__init__()
    # self.conv1 = nn.Conv2d(1, 31, 3, 2)
    self.bn1 = nn.BatchNorm2d(1)
  def forward(self, x):

soumith

import torch
import torch.nn as nn

class Model(nn.Module):
  def __init__(self):
    super(Model, self).__init__()
    
  def forward(self, x):
    y = torch.sigmoid(x + x * x)
    return y

soumith

import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision as vision

class XlaMNIST(nn.Module):
  def __init__(self):
    super(XlaMNIST, self).__init__()
    # self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
    # self.conv2 = nn.Conv2d(10, 20, kernel_size=5)

soumith

import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision as vision

class XlaMNIST(nn.Module):
  def __init__(self):
    super(XlaMNIST, self).__init__()
    
  def forward(self, x):

soumith

import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision as vision

class XlaMNIST(nn.Module):
  def __init__(self):
    super(XlaMNIST, self).__init__()
    self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
    self.conv2 = nn.Conv2d(10, 20, kernel_size=5)

soumith

FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04

WORKDIR /packages

RUN apt-get update --fix-missing && \
    apt-get install -y cmake git wget bzip2 ca-certificates curl software-properties-common && \
    add-apt-repository ppa:ubuntu-toolchain-r/test && \
    apt-get update && \
    apt-get install -y gcc-7 libgfortran4 && \
    apt-get clean

soumith

graph(%0 : Float(4, 3, 224, 224)
      %1 : Float(64, 3, 7, 7)
      %2 : Float(64)
      %3 : Float(64)
      %4 : Float(64)
      %5 : Float(64)
      %6 : Long()
      %7 : Float(64, 64, 1, 1)
      %8 : Float(64)
      %9 : Float(64)

soumith

from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import datasets, transforms

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(1, 10, kernel_size=5)

soumith

conda uninstall --force pillow -y

# install libjpeg-turbo to $HOME/turbojpeg
git clone https://github.com/libjpeg-turbo/libjpeg-turbo
pushd libjpeg-turbo
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX:PATH=$HOME/turbojpeg
make
make install

soumith

================================================================================
General dependencies
================================================================================
libc.so.6 imported symbols from:
	python
	ld-linux-x86-64.so.2
	libpthread.so.0
	sh
libm.so.6 imported symbols from:
	libc.so.6