Apoorv Nandan apoorvnandan

I modified Mike Bostock's Bilevel Partition so that only one level is viewable at a time and added labels.
This visualization also accepts negative values in the data, and displays them in Red color. The positive values are displayed in Green color Click on any arc to zoom in. Click in the center to zoom out.

	document.getElementById("editor").addEventListener("keydown", function (event) {
	// Check if Enter is pressed without the Ctrl key
	if (event.key === "Enter" && !event.ctrlKey) {
	event.preventDefault();
	}

	// Check if both Ctrl and Enter are pressed
	if (event.ctrlKey && event.key === "Enter") {
	event.preventDefault();

	class ProgressBar:
	def __init__(self, total, desc='', width=10):
	self.total = total
	self.width = width
	self.header = f"{desc}: " if len(desc) > 0 else ''
	self.i = 0
	self.__print_progress()

	def __print_progress(self):
	p = round((self.i*self.width) / self.total)

	##
	# usage:
	# 1. Add '#export' as the first line of the cells you want to export.
	# This script will ignore all other cells.
	# 2. $python convert_nb_script.py -n sample.ipynb > sample_script.py
	#
	# You can use other tags to selectively export other cells
	# eg. Add tag #test to the cells containing unit tests
	# python convert_nb_script.py -n sample.ipynb -t test > unit_tests.py
	##

	def prefix_beam_search(ctc,
	alphabet,
	blank_token,
	end_token,
	space_token,
	lm,
	k=25,
	alpha=0.30,
	beta=5,
	prune=0.001):

	def create_spectrogram(signals):
	stfts = tf.signal.stft(signals, fft_length=256)
	spectrograms = tf.math.pow(tf.abs(stfts), 0.5)
	return spectrograms

	class ASR(tf.keras.Model):
	def __init__(self, filters, kernel_size, conv_stride, conv_border, n_lstm_units, n_dense_units):
	super(ASR, self).__init__()
	self.conv_layer = tf.keras.layers.Conv1D(filters,
	kernel_size,
	strides=conv_stride,
	padding=conv_border,
	activation='relu')
	self.lstm_layer = tf.keras.layers.LSTM(n_lstm_units,
	return_sequences=True,

	class Cache:
	'''
	class to cache the probability values while performing prefix beam search
	'''
	def __init__(self):
	self.data = {}

	def add(self, key1, key2, value):
	if key1 not in self.data:
	self.data[key1] = {}