Dan Saunders djsaunde

## add_accelerate_decorator.py
def add_accelerate_options():
    """Create Click options from accelerate's launch command arguments."""
    def decorator(function):
        parser = launch_command_parser()

        # Process each argument group in reverse order for correct option ordering
        for group in reversed(parser._action_groups):
            if group.title in ['positional arguments', 'optional arguments']:
                continue

## mh_mcmc.py
import argparse
import scipy.stats
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt

from tqdm import tqdm
from matplotlib.patches import Ellipse


## LIFNodes vs. CurrentLIFNodes.ipynb

      
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                djsaunde
                / LIFNodes vs. CurrentLIFNodes.ipynb
            
            
              Created
              June 11, 2018 13:53
            
              
                Comparison of simple voltage-based and current-based LIF neurons
              
          
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## cartpole.py
'''
PyTorch tutorial code found at http://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html#sphx-glr-intermediate-reinforcement-q-learning-py.
'''

import gym
import math
import random
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

## tensorflow_mnist_tutorial.py
# coding: utf-8

# imports
from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf

# download and store MNIST data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

# create TensorFlow interactive session
	def add_accelerate_options():
	"""Create Click options from accelerate's launch command arguments."""
	def decorator(function):
	parser = launch_command_parser()

	# Process each argument group in reverse order for correct option ordering
	for group in reversed(parser._action_groups):
	if group.title in ['positional arguments', 'optional arguments']:
	continue
	import argparse
	import scipy.stats
	import numpy as np
	import matplotlib.cm as cm
	import matplotlib.pyplot as plt

	from tqdm import tqdm
	from matplotlib.patches import Ellipse
	'''
	PyTorch tutorial code found at http://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html#sphx-glr-intermediate-reinforcement-q-learning-py.
	'''

	import gym
	import math
	import random
	import numpy as np
	import matplotlib
	import matplotlib.pyplot as plt
	# coding: utf-8

	# imports
	from tensorflow.examples.tutorials.mnist import input_data
	import tensorflow as tf

	# download and store MNIST data
	mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

	# create TensorFlow interactive session