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def learn2(optimizee, unroll_train_steps, retain_graph_flag = False, reset_theta = False):
    """retain_graph_flag=False   
    By default, the dynamic graph is released after each loss_backward
    #  reset_theta = False   
    By default, parameters are not initialized randomly before each learning.
    """
    if reset_theta == True:
        theta_new = torch.empty(dim)
        torch.nn.init.uniform_(theta_new, a = -1 , b = 1.0)
        theta_init_new = torch.tensor(theta, dtype=torch.float32, requires_grad=True)

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## TensorFlow
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import state_ops
from tensorflow.python.framework import ops
from tensorflow.contrib import rnn
import tensorflow as tf

class NLayerPerceptron:

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from NeuralNetwork import NLayerPerceptron
import sys
import warnings

import tensorflow as tf
#It will download and read in the data automatically
from tensorflow.examples.tutorials.mnist import input_data

mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

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#!/usr/bin/env python

import rospy
import subprocess
import os
import signal


class RosbagRecord:
    def __init__(self):

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material road
{
  technique
  {
    pass
    {
        ambient 0.1 0.1 0.1 1.0
        diffuse 0.8 0.8 0.8 1.0
        specular 0.01 0.01 0.01 1.0 2.0

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@tf.function
def tfgamma(z):
    g = tf.exp(tf.math.lgamma(z))
    return g

@tf.function
def NB(x, mu, phi):
    numerator = tfgamma(x + phi)*tf.math.pow(mu,x)*tf.math.pow(phi, phi)
    denominator = tfgamma(phi)*tfgamma(x+1) *tf.math.pow((mu + phi),(x+phi))
    return (numerator/denominator)

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How to use MATLAB Functionality from within Python

Install MATLAB Engine for Python

• Source your python environment. For me, it is anaconda with the name of virtual environment base.

source activate base

• Change your directory to where you installed MATLAB

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How to use MATLAB Functionality from within Python

Install MATLAB Engine for Python

• Source your python environment. For me, it is anaconda with the name of virtual environment base.

source activate base

• Change your directory to where you installed MATLAB

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import scanpy
ad = sc.read(filename="Zeisel.h5")
X = ad.X # X is the count matrix

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# How to install bagpy:
# pip install bagpy
# documentation: https://jmscslgroup.github.io/bagpy/
# Repo: https://github.com/jmscslgroup/bagpy

import bagpy
from bagpy import bagreader
b = bagreader('/home/ivory/Downloads/2020-06-18-17-30-23.bag')
print(b.topic_table)