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import tensorflow as tf

gpu_fraction = 0.1
vector_size = 100
n = 1
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=gpu_fraction)
config = tf.ConfigProto(gpu_options=gpu_options)
for i in range(n):
	with tf.Session(config=config) as sess:
		a = tf.random.normal([vector_size])

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import pyperclip as clipboard

# path of file to open
openFile = "stats.txt"

# row will be populated in this order
L2Size = 2
L3Size = 4
TestSet = "gcc"
keysToLookFor = ['sim_seconds',

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# path of file to open
openFile = "stats.txt"

saveFile = openFile + ".json"



# returns string representations of items in array as a single string joined with joiner
# inserted between each item
def strJoin (sarr, joiner):

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import numpy as np
import wave
import struct

waveFile = "No open file"
path = ""
# 0 is the least verbose
printLevel = 0

def open(input, verbose=0):

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import wave
import struct
import sys

# the only non-default library
import numpy as np

input = "file_path_here.wav"

waveFile = wave.open(input, 'r')