Get the test runner operating again.

Models/model_host.py

@@ -1,43 +1,5 @@
-#import sys
-#import os
-#import glob
-#import socket
-#from keras.backend import GraphExecutionFunction
-
-#sys.path.append('c:/git/keras')
-#sys.path.append('c:/git/absl')
-
-# This upgrades all modules
-#py -mpip freeze | %{$_.split('==')[0]} | %{py -mpip install --upgrade $_}
-
-
-# The following worked to install CUDA for using tensorflow with GPU
-# 1) Install CUDA 11.8 Toolkit from here   
-#    https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Windows&target_arch=x86_64&target_version=11&target_type=exe_local
-# 2) The binaries should wind up in C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin
-# 3) Put the above path in the PATH environment variable
-# 4) Also download cuDNN from here https://developer.nvidia.com/cudnn because tensorflow will look for cudnn64_8.dll which is in that package
-#    This download is just a bunch of DLLs with no install program.  I left it in downloads folder.
-# 5) put C:\download\cuDNN\cudnn-windows-x86_64-8.9.7.29_cuda11-archive\bin in the PATH
-# 6) Run the check_gpu.py program and ensure no errors loading DLLs
-
-
-
-
-# installed version
-# py -m pip install keras==2.6.0
-# py -mpip install flask==2.0.1
-# py -mpip install numpy==1.19.5
-# py -mpip show numpy 
-# py -mpip install tensorflow==2.6.0
-# py -mpip show tensorflow
-# py -mpip install matplotlib==3.4.3
-# c:\users\skess\appdata\local\programs\python\python39\lib\site-packages
-
 import keras
-#from keras.preprocessing.image import ImageDataGenerator
 from keras.src.legacy.preprocessing.image import ImageDataGenerator
-
 from flask import Flask, render_template, send_file, request
 import numpy as np
 import tensorflow