zhanwenchen

import os
import tensorflow as tf

trained_checkpoint_prefix = 'checkpoints/dev'
export_dir = os.path.join('models', '0') # IMPORTANT: each model folder must be named '0', '1', ... Otherwise it will fail!

loaded_graph = tf.Graph()
with tf.Session(graph=loaded_graph) as sess:
    # Restore from checkpoint
    loader = tf.train.import_meta_graph(trained_checkpoint_prefix + '.meta')

heyalexej

>>> import pytz
>>> 
>>> for tz in pytz.all_timezones:
...     print tz
...     
... 
Africa/Abidjan
Africa/Accra
Africa/Addis_Ababa
Africa/Algiers

natanfelles

# Location: /etc/nginx/sites-available/domain.tld.conf
server {
	listen 80;

	# listen 443 ssl;
	# include snippets/snakeoil.conf;

	root /var/www/domain.tld/public;

	index index.html index.php;

benmarwick

# Reproducible Research using Docker and R

# Challenges of reproducibility 

- dependencies
- isolation and transparency 
- portability of computationational environment
- extendability and resuse 
- ease of use

skranz

# Helper functions that allow string arguments for  dplyr's data modification functions like arrange, select etc. 
# Author: Sebastian Kranz

# Examples are below

#' Modified version of dplyr's filter that uses string arguments
#' @export
s_filter = function(.data, ...) {
  eval.string.dplyr(.data,"filter", ...)
}

zr-tex8r

Moved

This package is now distributed at [GitHub:zr-tex8r/BXcjkjatpye] (https://github.com/zr-tex8r/BXcjkjatype).

dsparks

CoefficientPlot <- function(models, alpha = 0.05, modelnames = ""){
  # models must be a list()

  Multiplier <- qnorm(1 - alpha / 2)
  CoefficientTables <- lapply(models, function(x){summary(x)$coef})
  TableRows <- unlist(lapply(CoefficientTables, nrow))

  if(modelnames[1] == ""){
    ModelNameLabels <- rep(paste("Model", 1:length(TableRows)), TableRows)
    } else {