Anaconda2-2019.03 (Jul. 4, 2019)

Usage
There so many detailed guides of conda/anaconda elsewhere on the internet. Please also check them.

Initialization
You can activate conda settings by loading initialization script.
bash, zsh:
% . /local/apl/lx/anaconda2-2019Jul/conda_init.shcsh (tcsh):% source /local/apl/lx/anaconda2-2019Jul/conda_init.csh

Upon this stage, you may be in the "base" environment. The environment name will be shown at the far left on yourprompt like the following example.
(base) %Environments
base: base environment, can be considered as default environment.
python 2.7.16
numpy 1.16.4, scipy 1.2.1, pandas 0.24.2, pyyaml 5.1.1, pillow 6.0.0
tensorflow 1.14.0, keras 2.2.4, chainer 5.3.0, pytorch 1.1.0
GPU packages are not installed. This contains popular python packages for academic research and CPU
version packages for deep learning (tensorflow, keras, pytorch, chainer).
chainer_gpu: Chainer GPU environment.
python 2.7.16
chainer 5.3.0, cupy 6.0.0, cudatoolkit 9.0
pytorch_gpu: PyTorch GPU environment.
python 2.7.16
pytorch(-gpu) 1.1.0, torchvision(-gpu) 0.3.0, cudatoolkit 9.0
tensorflow_gpu: TensorFlow + Keras GPU environment.
python 2.7.16
tensorflow(-gpu) 1.13.1, keras(-gpu) 2.2.4, cudatoolkit 9.0
The installed packages in the environments above won't be updated. In other word, environments will be kept intact.
New version of packages will be installed upon creating new environments or creating another anaconda installation.

Switching Environments
You can change environment by executing "conda active" command after the initialization of conda itself.
Example:(base) % conda activate pytorch_gpu(pytorch_gpu) %Current environment name will be shown at the leftmost of the prompt regardless of your login shell type (csh or bash orzsh).
You can exit from the conda environment by "conda deactivate" command.
Example:(pytorch_gpu) % conda deactivate

(base) % conda deactivate%

Creating your own environment
Users cannot add packages in this anaconda directory, since this anaconda is installed in the system domain(/local/apl/lx).
Instead, you can build your own conda environment using this pre-installed anaconda.
The new environment files will be placed under ~/.conda directory in the default setting.
Example: new anaconda env creation ("myenv" is your new environment name):(base) % conda create -n myenv anaconda

Example: clone "base" environment ("myenv" is your new environment name):(base) % conda create -n myenv --clone base(note: conda_init.sh, conda_init.csh, samples_rccs/ will also be cloned. You can remove those files after the cloning.)
You can also directly install anaconda (or miniconda) under your home directory.
If you need a very special environment, this way may be a better solution.

Run MNIST sample
MNIST sample scripts are available in /local/apl/lx/anaconda2-2019Jul/samples_rccs directory.
You can run them just by copying directory and submit by using jsub.
The script initializes conda, chooses environment if necessary, and then run MNIST sample.
Note: if your login shell is csh and try to run GPU sample, you may need to modify script (see script).
tensorflow exmaple:% cp -r /local/apl/lx/anaconda2-2019Jul/samples_rccs/tensorflow/ ~/tensorflow_sample_mnist% cd ~/tensorflow_sample_mnist% jsub -q PN sample-tensorflow-cpu.sh(MNIST data is downloaded on /local/apl/lx/anaconda2-2019Jul/samples_rccs/datasets in advance. Please note thatcomputation nodes cannot access internet.)

Extra: Install packages without conda envs
You can also install packages under your home directory via "pip" or "pip3" command without conda.
Example: (--user is the key option, this is required.)% pip install cupy-cuda91 chainer --user(use pip3 instead of pip if you are using Python3)

Installation Details
Webpagehttps://www.anaconda.com/Version
2019.03FilesAnaconda2-2019.03-Linux-x86_64.sh

Installation Procedure
The following commands are run by root. Most of logs are cut, since it is too long.

base environment (non-GPU env)
% sh Anaconda2-2019.02-Linux-x86_64.sh...
Anaconda2 will now be installed into this location:/root/anaconda2- Press ENTER to confirm the location- Press CTRL-C to abort the installation- Or specify a different location below[/root/anaconda2] >>> /local/apl/lx/anaconda2-2019Jul...
Do you wish the installer to initialize Anaconda2
by running conda init? [yes|no][no] >>> no% /local/apl/lx/anaconda2-2019Jul/bin/conda shell.bash hook > /local/apl/lx/anaconda2-2019Jul/conda_init.sh% /local/apl/lx/anaconda2-2019Jul/bin/conda shell.csh hook > /local/apl/lx/anaconda2-2019Jul/conda_init.csh% . /local/apl/lx/anaconda2-2019Jul/conda_init.sh(base) % conda update --all...
The following packages will be DOWNGRADED:
anaconda

2019.03-py27_0 --> custom-py27h4a00acb_0

contextlib2

0.5.5-py27hbf4c468_0 --> 0.5.5-py27_0

cycler

0.10.0-py27hc7354d3_0 --> 0.10.0-py27_0

et_xmlfile

1.0.1-py27h75840f5_0 --> 1.0.1-py27_0

locket0.2.0-py27h73929a2_1 --> 0.2.0-py27_1

nbformat

4.4.0-py27hed7f2b2_0 --> 4.4.0-py27_0

prompt_toolkit

1.0.15-py27h1b593e1_0 --> 1.0.15-py27_0

singledispatch

3.4.0.3-py27h9bcb476_0 --> 3.4.0.3-py27_0

traitlets

4.3.2-py27hd6ce930_0 --> 4.3.2-py27_0

unicodecsv

0.14.1-py27h5062da9_0 --> 0.14.1-py27_0

wcwidth

0.1.7-py27h9e3e1ab_0 --> 0.1.7-py27_0...
(base) % conda install tensorflow keras chainer opencv...
chainerpkgs/main/linux-64::chainer-5.3.0-py27_0

keras

pkgs/main/linux-64::keras-2.2.4-0

keras-applications pkgs/main/noarch::keras-applications-1.0.8-py_0
keras-basepkgs/main/linux-64::keras-base-2.2.4-py27_0

keras-preprocessi~ pkgs/main/noarch::keras-preprocessing-1.1.0-py_1
tensorboard

pkgs/main/linux-64::tensorboard-1.14.0-py27hf484d3e_0

tensorflow

pkgs/main/linux-64::tensorflow-1.14.0-mkl_py27h957988d_0

tensorflow-basepkgs/main/linux-64::tensorflow-base-1.14.0-mkl_py27h7ce6ba3_0

tensorflow-estima~ pkgs/main/noarch::tensorflow-estimator-1.14.0-py_0...
The following packages will be REMOVED:
pytables-3.5.2-py27h71ec239_1
The following packages will be DOWNGRADED:
h5py
hdf5
...

2.9.0-py27h7918eee_0 --> 2.8.0-py27h989c5e5_3
1.10.4-hb1b8bf9_0 --> 1.10.2-hba1933b_1

(base) % conda install -c pytorch pytorch-cpu torchvision-cpu...
pytorch-cpu

pytorch/linux-64::pytorch-cpu-1.1.0-py2.7_cpu_0

torchvision-cpu

pytorch/linux-64::torchvision-cpu-0.3.0-py27_cuNone_1...
(base) % conda install pytables...
pytablespkgs/main/linux-64::pytables-3.4.4-py27ha205bf6_0...

Chainer GPU env% . /local/apl/lx/anaconda2-2019Jul/conda_init.sh(base) % conda create --name chainer_gpu --clone base...
(base) % conda activate chainer_gpu(chainer_gpu) % conda remove chainer tensorflow keras pytorch-cpu torchvision-cpu...
(chainer_gpu) % conda install cudatoolkit=9.0 cupy chainer...
The following NEW packages will be INSTALLED:
chainerpkgs/main/linux-64::chainer-5.3.0-py27_0

cudatoolkit

pkgs/main/linux-64::cudatoolkit-9.0-h13b8566_0

cudnn

pkgs/main/linux-64::cudnn-7.6.0-cuda9.0_0

cupy

pkgs/main/linux-64::cupy-6.0.0-py27h686fdb1_0

fastrlocknccl

pkgs/main/linux-64::fastrlock-0.4-py27he6710b0_0
pkgs/main/linux-64::nccl-1.3.5-cuda9.0_0...

PyTorch GPU env% . /local/apl/lx/anaconda2-2019Jul/conda_init.sh(base) % conda create --name pytorch_gpu --clone base...
(base) % conda activate pytorch_gpu(pytorch_gpu) % conda remove chainer tensorflow keras pytorch-cpu torchvision-cpu...
(pytorch_gpu) % conda install -c pytorch cudatoolkit=9.0 pytorch torchvision cudnn...
The following NEW packages will be INSTALLED:
cudatoolkit

pkgs/main/linux-64::cudatoolkit-9.0-h13b8566_0

cudnn

pkgs/main/linux-64::cudnn-7.6.0-cuda9.0_0

pytorchpytorch/linux-64::pytorch-1.1.0-py2.7_cuda9.0.176_cudnn7.5.1_0

torchvision

pytorch/linux-64::torchvision-0.3.0-py27_cu9.0.176_1...

(cudnn may be unnecessary for pytorch-gpu?)

TensorFlow + Keras GPU env% . /local/apl/lx/anaconda2-2019Jul/conda_init.sh(base) % conda create --name tensorflow_gpu anaconda..
(base) % conda activate tensorflow_gpu(tensorflow_gpu) % conda install anaconda=custom=py27h4a00acb_0...
(tensorflow_gpu) % conda install cudatoolkit=9.0 tensorflow-gpu keras-gpu...
keras-applications pkgs/main/noarch::keras-applications-1.0.8-py_0
keras-basepkgs/main/linux-64::keras-base-2.2.4-py37_0

keras-gpu

pkgs/main/linux-64::keras-gpu-2.2.4-0

keras-preprocessi~ pkgs/main/noarch::keras-preprocessing-1.1.0-py_1...

tensorboard

pkgs/main/linux-64::tensorboard-1.13.1-py37hf484d3e_0

tensorflow

pkgs/main/linux-64::tensorflow-1.13.1-gpu_py37hd37c573_0

tensorflow-basepkgs/main/linux-64::tensorflow-base-1.13.1-gpu_py37h8f37b9b_0

tensorflow-estima~ pkgs/main/noarch::tensorflow-estimator-1.13.0-py_0
tensorflow-gpu

pkgs/main/linux-64::tensorflow-gpu-1.13.1-h0d30ee6_0...
(tensorflow_gpu) % conda install opencv...
The following packages will be REMOVED:
pytables-3.5.1-py27h71ec239_0
The following packages will be DOWNGRADED:
h5pyhdf5

2.9.0-py27h7918eee_0 --> 2.8.0-py27h989c5e5_3
1.10.4-hb1b8bf9_0 --> 1.10.2-hba1933b_1...
(tensorflow_gpu) % conda install pytables...
The following NEW packages will be INSTALLED:
pytablespkgs/main/linux-64::pytables-3.4.4-py27ha205bf6_0...

(Cloned environment of "base" encountered dependency problem. So we employed the procedure above unlike the othertwo.)