John Bradshaw john-bradshaw

## flax_mem_leak.py
"""
Simple demonstration of memory leak.
 XLA_PYTHON_CLIENT_PREALLOCATE=false CUDA_VISIBLE_DEVICES=0 python  flax_mem_leak.py
 Breaks on last iter through loop.

# Tested on version:

    Name: flax
    Version: 0.4.1
    Summary: Flax: A neural network library for JAX designed for flexibility

## different_smiles_same_fp.ipynb

      
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                john-bradshaw
                / different_smiles_same_fp.ipynb
            
            
              Last active
              April 28, 2022 00:26
            
              
                Notebook showing how different SMILES can sometimes have the same fingerprint
              
          
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## split_reagents.py
"""
Module for identifying for RDKit functions working with reaction SMILES strings.
"""


import collections
import itertools
import functools
import typing

## tf_control_dep_demo2.py


import tensorflow as tf

def main1():

    sess = tf.Session()
    x = tf.Variable(1.)
    sess.run(tf.initialize_variables([x]))

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

def main1():
    x = tf.get_variable("x", initializer=np.float64(0))

    x_id = tf.identity(x)
    x_rd = x.read_value()
    x_p0 = x + 0
    with tf.control_dependencies([x_id, x_rd, x_p0]):

## gpdnns.py

import os

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data as mnist_input_data
import numpy as np
from sklearn import cluster
from scipy.spatial import distance
import pandas as pd

## bayesian_optimisation_simple_demo.py

import enum

import numpy as np
from scipy import stats
import fire
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from matplotlib.widgets import Button

## mnist_gpdnn_example.py

import os

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data as mnist_input_data
import numpy as np
from sklearn import cluster
from scipy.spatial import distance
import pandas as pd

## mixture_of_gaussians_morphing.py
"""
Code for Figure 1c of
Saul, L.K. and Jordan, M.I., 1997. A variational principle for model-based morphing.
In Advances in Neural Information Processing Systems (pp. 267-273).

Note not exactly the same setup and do not know settings of ell and variance to use
Also not sure how to deal with the change points

Written in a bit of a rush and not thoroughly tested so use with caution
"""

## gaussian_morphing.py
"""
Code for Figure 1a of
Saul, L.K. and Jordan, M.I., 1997. A variational principle for model-based morphing.
In Advances in Neural Information Processing Systems (pp. 267-273).
"""

import numpy as np
from scipy.integrate import odeint
from scipy.optimize import fsolve
from scipy import stats
	"""
	Simple demonstration of memory leak.
	XLA_PYTHON_CLIENT_PREALLOCATE=false CUDA_VISIBLE_DEVICES=0 python flax_mem_leak.py
	Breaks on last iter through loop.

	# Tested on version:

	Name: flax
	Version: 0.4.1
	Summary: Flax: A neural network library for JAX designed for flexibility
	"""
	Module for identifying for RDKit functions working with reaction SMILES strings.
	"""


	import collections
	import itertools
	import functools
	import typing


	import tensorflow as tf

	def main1():

	sess = tf.Session()
	x = tf.Variable(1.)
	sess.run(tf.initialize_variables([x]))
	import numpy as np
	import tensorflow as tf

	def main1():
	x = tf.get_variable("x", initializer=np.float64(0))

	x_id = tf.identity(x)
	x_rd = x.read_value()
	x_p0 = x + 0
	with tf.control_dependencies([x_id, x_rd, x_p0]):

	import os

	import tensorflow as tf
	from tensorflow.examples.tutorials.mnist import input_data as mnist_input_data
	import numpy as np
	from sklearn import cluster
	from scipy.spatial import distance
	import pandas as pd

	import enum

	import numpy as np
	from scipy import stats
	import fire
	import matplotlib
	matplotlib.use('TkAgg')
	import matplotlib.pyplot as plt
	from matplotlib.widgets import Button
	"""
	Code for Figure 1c of
	Saul, L.K. and Jordan, M.I., 1997. A variational principle for model-based morphing.
	In Advances in Neural Information Processing Systems (pp. 267-273).

	Note not exactly the same setup and do not know settings of ell and variance to use
	Also not sure how to deal with the change points

	Written in a bit of a rush and not thoroughly tested so use with caution
	"""
	"""
	Code for Figure 1a of
	Saul, L.K. and Jordan, M.I., 1997. A variational principle for model-based morphing.
	In Advances in Neural Information Processing Systems (pp. 267-273).
	"""

	import numpy as np
	from scipy.integrate import odeint
	from scipy.optimize import fsolve
	from scipy import stats