How to run deep visualization toolbox on nvidia-Docker Build caffe model

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Venkat

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Nov 13, 2016, 12:44:55 PM11/13/16

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Hi All,

I build caffe using below docker configuration

FROM nvidia/cuda:8.0-cudnn5-devel-ubuntu16.04

MAINTAINER caffe...@googlegroups.com

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

build-essential \

cmake \

git \

wget \

libatlas-base-dev \

libboost-all-dev \

libgflags-dev \

libgoogle-glog-dev \

libhdf5-serial-dev \

libleveldb-dev \

liblmdb-dev \

libopencv-dev \

libprotobuf-dev \

libsnappy-dev \

protobuf-compiler \

python-dev \

python-numpy \

python-pip \

python-scipy && \

rm -rf /var/lib/apt/lists/*

ENV CAFFE_ROOT=/opt/caffe

WORKDIR $CAFFE_ROOT

# FIXME: clone a specific git tag and use ARG instead of ENV once DockerHub supports this.

ENV CLONE_TAG=master

RUN git clone -b ${CLONE_TAG} --depth 1 https://github.com/BVLC/caffe.git . && \

for req in $(cat python/requirements.txt) pydot; do pip install $req; done && \

mkdir build && cd build && \

cmake -DCUDA_ARCH_NAME="Manual" -DCUDA_ARCH_BIN="52 60" -DCUDA_ARCH_PTX="60" -DUSE_CUDNN=1 .. && \

make -j"$(nproc)"

ENV PYCAFFE_ROOT $CAFFE_ROOT/python

ENV PYTHONPATH $PYCAFFE_ROOT:$PYTHONPATH

ENV PATH $CAFFE_ROOT/build/tools:$PYCAFFE_ROOT:$PATH

RUN echo "$CAFFE_ROOT/build/lib" >> /etc/ld.so.conf.d/caffe.conf && ldconfig

WORKDIR /workspace

I wanted to run Deep visualization toolbox (https://github.com/yosinski/deep-visualization-toolbox) on top of docker build caffe.

The settings file to build the Deep visualition tool box looks like below.

# Define critical settings and/or override defaults specified in

# settings.py. Copy this file to settings_local.py in the same

# directory as settings.py and edit. Any settings defined here

# will override those defined in settings.py

# Set this to point to your compiled checkout of caffe

caffevis_caffe_root = '/path/to/caffe'

# Load model: caffenet-yos

# Path to caffe deploy prototxt file. Minibatch size should be 1.

caffevis_deploy_prototxt = '%DVT_ROOT%/models/caffenet-yos/caffenet-yos-deploy.prototxt'

# Path to network weights to load.

caffevis_network_weights = '%DVT_ROOT%/models/caffenet-yos/caffenet-yos-weights'

# Other optional settings; see complete documentation for each in settings.py.

caffevis_data_mean = '%DVT_ROOT%/models/caffenet-yos/ilsvrc_2012_mean.npy'

caffevis_labels = '%DVT_ROOT%/models/caffenet-yos/ilsvrc_2012_labels.txt'

caffevis_label_layers = ('fc8', 'prob')

caffevis_prob_layer = 'prob'

caffevis_unit_jpg_dir = '%DVT_ROOT%/models/caffenet-yos/unit_jpg_vis'

caffevis_jpgvis_layers = ['conv1', 'conv2', 'conv3', 'conv4', 'conv5', 'fc6', 'fc7', 'fc8', 'prob']

caffevis_jpgvis_remap = {'pool1': 'conv1', 'pool2': 'conv2', 'pool5': 'conv5'}

def caffevis_layer_pretty_name_fn(name):

return name.replace('pool','p').replace('norm','n')

# Use GPU? Default is True.

#caffevis_mode_gpu = True

# Display tweaks.

# Scale all window panes in UI by this factor

#global_scale = 1.0

# Scale all fonts by this factor

#global_font_size = 1.0

I don't know how to set the below variable, i.e path of the compiled checkout caffe.

# Set this to point to your compiled checkout of caffe

caffevis_caffe_root = '/path/to/caffe'

Does the above toolbox can be run using nvidia-docker ?. My GPU details are CUDA 8 GTX1080

My need is to run the deep visualization toolbox on a model build using the Docker based caffe.