Niru Maheswaranathan nirum

## pax.py
"""Save/load pytrees to disk."""

import collections
import h5py
import jax
import numpy as np


def save(filepath, tree):
  """Saves a pytree to an hdf5 file.

## lax_shape_bug.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                nirum
                / lax_shape_bug.ipynb
            
            
              Last active
              April 17, 2019 19:18
            
              
                lax_shape_bug
              
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## cell07.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                nirum
                / cell07.ipynb
            
            
              Created
              December 6, 2018 18:56
                — forked from szapp/cell07.ipynb
            
              
                Attempt to recreate figure 3 from Maheswaranathan et al, 2018
              
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## gist:78bca44c0425081274513114bf8dab5a
# Dark mode
color0  #282828
color1  #cc241d
color2  #98971a
color3  #d79921
color4  #458588
color5  #b16286
color6  #689d6a
color7  #a89984
color8  #928374

## tf_sandbox.py
def tf_graph_wrapper(func):
    """Wraps a class method with a tf.Graph context manager"""
    @wraps(func)
    def wrapper(self, *args, **kwargs):
        with self._graph.as_default():
            return func(self, *args, **kwargs)
    return wrapper


def tf_init(func):

## adaptiveIAF.py
class AdaptiveIAF(tf.nn.rnn_cell.RNNCell):
    def __init__(self, num_units, dt, reuse=False):
        self._dt = tf.constant(dt, dtype=tf.float32)
        self._num_units = num_units
        self._reuse = reuse

    @property
    def state_size(self):
          return (self._num_units, self._num_units)


## noisy_opt_demo.py
import numpy as np
import tensorflow as tf

# initialize variable x=10
x = tf.Variable(10.0, dtype=tf.float32)

# objective is x ** 3 which has a saddle point at x=0
f = x ** 3

# create optimizer and compute gradients

## animations.py
import os
from moviepy.editor import ImageSequenceClip


def gif(filename, array, fps=10, scale=1.0):
    """Creates a gif given a stack of images using moviepy

    Notes
    -----
    works with current Github version of moviepy (not the pip version)

## autotime.py
from __future__ import print_function
from time import perf_counter
from IPython.core.magics.execution import _format_time as fmt


class Timer(object):
    """
    Timer is a simple class to keep track of elapsed time.

    """

## data_imports.py
from numpy.random import rand, randn, shuffle, choice, sample
from numpy import arange, zeros, ones, eye, linspace, pi, inf, nan, cov, array
from scipy.linalg import *
from matplotlib.pyplot import *
	"""Save/load pytrees to disk."""

	import collections
	import h5py
	import jax
	import numpy as np


	def save(filepath, tree):
	"""Saves a pytree to an hdf5 file.
	# Dark mode
	color0 #282828
	color1 #cc241d
	color2 #98971a
	color3 #d79921
	color4 #458588
	color5 #b16286
	color6 #689d6a
	color7 #a89984
	color8 #928374
	def tf_graph_wrapper(func):
	"""Wraps a class method with a tf.Graph context manager"""
	@wraps(func)
	def wrapper(self, args, *kwargs):
	with self._graph.as_default():
	return func(self, args, *kwargs)
	return wrapper


	def tf_init(func):
	class AdaptiveIAF(tf.nn.rnn_cell.RNNCell):
	def __init__(self, num_units, dt, reuse=False):
	self._dt = tf.constant(dt, dtype=tf.float32)
	self._num_units = num_units
	self._reuse = reuse

	@property
	def state_size(self):
	return (self._num_units, self._num_units)
	import numpy as np
	import tensorflow as tf

	# initialize variable x=10
	x = tf.Variable(10.0, dtype=tf.float32)

	# objective is x ** 3 which has a saddle point at x=0
	f = x ** 3

	# create optimizer and compute gradients
	import os
	from moviepy.editor import ImageSequenceClip


	def gif(filename, array, fps=10, scale=1.0):
	"""Creates a gif given a stack of images using moviepy

	Notes
	-----
	works with current Github version of moviepy (not the pip version)
	from __future__ import print_function
	from time import perf_counter
	from IPython.core.magics.execution import _format_time as fmt


	class Timer(object):
	"""
	Timer is a simple class to keep track of elapsed time.

	"""
	from numpy.random import rand, randn, shuffle, choice, sample
	from numpy import arange, zeros, ones, eye, linspace, pi, inf, nan, cov, array
	from scipy.linalg import *
	from matplotlib.pyplot import *