<commit_before>#!/usr/bin/env python
"""Example code of learning a large scale convnet from LSVRC2012 dataset
with multiple GPUs using data parallelism.

Prerequisite: To run this example, crop the center of ILSVRC2012 training and
validation images, scale them to 256x256 and convert them to RGB, and make
two lists of space-separated CSV whose first column is full path to image and
second column is zero-origin label (this format is same as that used by Caffe's
ImageDataLayer).

You need to install chainer with NCCL to run this example.
Please see https://github.com/pfnet/chainer#installation .

"""
from __future__ import print_function
import argparse

import numpy as np

import chainer
from chainer import training
from chainer.training import extensions<commit_msg>Replace the URL for the instruction of NCCL<commit_after>#!/usr/bin/env python
"""Example code of learning a large scale convnet from LSVRC2012 dataset
with multiple GPUs using data parallelism.

Prerequisite: To run this example, crop the center of ILSVRC2012 training and
validation images, scale them to 256x256 and convert them to RGB, and make
two lists of space-separated CSV whose first column is full path to image and
second column is zero-origin label (this format is same as that used by Caffe's
ImageDataLayer).

You need to install chainer with NCCL to run this example.
Please see https://github.com/nvidia/nccl#build--run .

"""
from __future__ import print_function
import argparse

import numpy as np

import chainer
from chainer import training
from chainer.training import extensions
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