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import lmdb
import leveldb

def lmdb_reader(filename, **kwargs):
    with lmdb.open(filename, readonly=True, create=False, **kwargs) as env:
        with env.begin() as txn:
            with txn.cursor() as cursor:
                for key, value in cursor:
                    yield key, value

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// Caffe proto converter.
//
// Build.
//
// mex -I/path/to/matlab-lmdb/include ...
//     -I/path/to/caffe/build/src/caffe/proto ...
//     caffe_proto_.cc ...
//     /path/to/caffe/build/src/caffe/proto/caffe.pb.o ...
//     -lprotobuf CXXFLAGS="$CXXFLAGS -std=c++11"
//

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# set SGE environment if exists
ACTIVE_JOBS_DIR=/var/spool/gridengine/execd/$(hostname)/active_jobs/
if [ -d $ACTIVE_JOBS_DIR ]; then
  PARENT_PID=$(ps -p $(ps -p $$ -o ppid --no-header) -o ppid --no-header)
  for job_dir in $(ls -1 $ACTIVE_JOBS_DIR); do
    JOB_PID=$(cat $ACTIVE_JOBS_DIR$job_dir/job_pid)
    if [ $JOB_PID -eq $PARENT_PID ]; then
      echo . $ACTIVE_JOBS_DIR$job_dir/environment
      . $ACTIVE_JOBS_DIR$job_dir/environment
      break

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name: "celeba_alexnet_independent"
layer {
  name: "data"
  type: "Data"
  top: "data"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true

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'''
Plot iteration information from the log file.

Usage

    python examples/message_passing/plot_iteration.py solver.log

'''

import argparse

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#!/usr/bin/env python

'''Caffe ResNet NetSpec example.

Compatible with Kaiming He's pre-trained models.

https://github.com/KaimingHe/deep-residual-networks
'''

import sys

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#!/usr/bin/env python

'''
Example:

    python data/celeba/scripts/build_dataset.py \
        --output_dir data/celeba/
    ./build/tools/compute_image_mean \
        data/celeba/train-images.lmdb \
        data/celeba/mean.binaryproto

kyamagu

Ubuntu setup

Setup instructions for the Ubuntu 16.04 workstations and servers in the laboratory environment. Replace systemctl with Upstart start|stop for Ubuntu 14.04.

Passwordless sudo

sudo tee /etc/sudoers.d/administrator <<EOF
administrator ALL=(ALL) NOPASSWD: ALL
EOF

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"""
Use in PyTorch.
"""

def accuracy(output, target):
    """Computes the accuracy for multiple binary predictions"""
    pred = output >= 0.5
    truth = target >= 0.5
    acc = pred.eq(truth).sum() / target.numel()
    return acc

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SMBNetFS

Install and setup

sudo apt-get install smbnetfs
mkdir ~/.smb
cp /etc/smbnetfs/smbnetfs.conf ~/.smb
cp /etc/samba/smb.conf ~/.smb