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"""A context manager for enforcing (integer) timeouts of a code block."""
import contextlib


@contextlib.contextmanager
def Timeout(timeout: Optional[int]) -> ContextManager[None]:
  """Raises TimeoutError() if block isn't completed within `timeout` seconds.

  Args:
    timeout: Seconds. If None, there is no timeout.

cfperez

Open jupyter with

$ xvfb-run -s "-screen 0 1400x900x24" jupyter notebook

In Jupyter

import matplotlib.pyplot as plt
%matplotlib inline

After each step

def show_state(env, step=0):

cfperez

def combined_legend(*axes):
    """Creates combines legends from provided axes.
    
    Usually used for ax and ax.twinx()
    """
    lines, labels = [], []
    for ax in axes:
        line, label = ax.get_legend_handles_labels()
        lines.extend(line)
        labels.extend(label)

cfperez

#!/bin/bash

CUDNN_FILE="cudnn-9.2-linux-x64-v7.1.tgz"
[ -e $CUDNN_FILE ] || echo "Please download CUDNN 7.1 from https://developer.nvidia.com/rdp/cudnn-download" && exit 1

sudo apt-get install linux-headers-$(uname -r)

# get CUDA 9.0 toolkit
PKG="cuda-repo-ubuntu1604_9.2.88-1_amd64.deb"
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/$PKG

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# From https://github.com/fchollet/keras/issues/5400#issuecomment-314747992
from keras import backend as K

 def mcor(y_true, y_pred):
     #matthews_correlation
     y_pred_pos = K.round(K.clip(y_pred, 0, 1))
     y_pred_neg = 1 - y_pred_pos
 
 
     y_pos = K.round(K.clip(y_true, 0, 1))

cfperez

#!/bin/bash

ENV=${1:-"$CONDA_DEFAULT_ENV"}
if [ -z "$ENV" ]; then
  echo Must specify conda environment
  exit 1
fi
DISPLAY_NAME=${2:-$ENV}

echo Installing kernel for enviroment $ENV using display name \"$DISPLAY_NAME\"

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#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda

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#!/bin/bash

ssh $@ -t -- 'tmux a || tmux new-session'

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from keras.callbacks import LearningRateScheduler

def scheduler(schedule):
    def lr_schedule(epoch):
        epoch += 1
        for ep,lr in sorted(schedule, reverse=True):
            if epoch >= ep:
                return lr
        raise ValueError()
    return lr_schedule

cfperez

" If using YADR: ~/.vim/settings/path.vim
" Or else in .vimrc
set shell=/bin/zsh\ -l