Akram Zaytar Akramz

## condor_config.local
#CONDOR_HOST = reynolds-master.reynol.dz
#
#COLLECTOR_NAME = TEFPL at $(FULL_HOSTNAME))
#START = $(CS_START)
#SUSPEND = $(CS_SUSPEND)
#CONTINUE = $(CS_CONTINUE)
#PREEMPT = $(CS_PREEMPT)
#KILL = $(CS_KILL)
#
#DAEMON_LIST = MASTER, SCHEDD, STARTD

## install-tensorflow.sh
# Note – this is not a bash script (some of the steps require reboot)
# I named it .sh just so Github does correct syntax highlighting.
#
# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
#
# The CUDA part is mostly based on this excellent blog post:
# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

# Install various packages
sudo apt-get update

## bobp-python.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                Akramz
                / bobp-python.md
            
            
              Created
              October 9, 2018 09:25
                — forked from sloria/bobp-python.md
            
              
                A "Best of the Best Practices" (BOBP) guide to developing in Python.
              
          
    The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.
In General

Values


"Build tools for others that you want to be built for you." - Kenneth Reitz
"Simplicity is alway better than functionality." - Pieter Hintjens


## generate_gif.py
from matplotlib.animation import FuncAnimation
import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(figsize=(5, 8))


def update(i):
    im_normed = np.random.random((64, 64))
    ax.imshow(im_normed)

## min-char-rnn.py
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
	#CONDOR_HOST = reynolds-master.reynol.dz
	#
	#COLLECTOR_NAME = TEFPL at $(FULL_HOSTNAME))
	#START = $(CS_START)
	#SUSPEND = $(CS_SUSPEND)
	#CONTINUE = $(CS_CONTINUE)
	#PREEMPT = $(CS_PREEMPT)
	#KILL = $(CS_KILL)
	#
	#DAEMON_LIST = MASTER, SCHEDD, STARTD
	# Note – this is not a bash script (some of the steps require reboot)
	# I named it .sh just so Github does correct syntax highlighting.
	#
	# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
	#
	# The CUDA part is mostly based on this excellent blog post:
	# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

	# Install various packages
	sudo apt-get update
	from matplotlib.animation import FuncAnimation
	import matplotlib.pyplot as plt
	import numpy as np

	fig, ax = plt.subplots(figsize=(5, 8))


	def update(i):
	im_normed = np.random.random((64, 64))
	ax.imshow(im_normed)
	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)