tf_wgan_bds_test.py

# -*- coding: utf-8 -*-
"""
Runs max_iters tests of tf_wgan_bds and saves results to a log file
    
@author: Joseph Pedersen
"""

import sys
old_stdout = sys.stdout
from datetime import datetime
dt = datetime.now().strftime('%Y%m%d_%H%M')
log_file = open("logs/test_tf_wgan_bds_"+dt,"w")
sys.stdout = log_file

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'

import pickle as pkl
import tf_wgan_bds as twb

# Create array to store results
resultsQ = []
resultsD = []
max_iters = 1000

# Arguments for np_wgan_bds.setup()
eps = 0.01
layers = 3
random=True
max_nodes=1000

# Print settings
print(f'  max_iters: {max_iters}')
print(f'  eps: {eps}')
print(f'  layers: {layers}')
print(f'  random: {random}')
print(f'  max_nodes: {max_nodes}')

# Test the bounds `max_iters` times
for i in range(max_iters):
    if i % max(1,max_iters//10) == 0:
        print(f"iteration {i}",file=old_stdout)
        
    # compute bounds and grads on practice data
    d = twb.setup(eps = eps, 
                  layers = layers, 
                  random=random, 
                  max_nodes=max_nodes)
    
    # test the bounds and grads
    c = twb.test(d)
    resultsQ.append(c['overallQ'])
    resultsD.append(c['overallD'])
    if resultsQ[-1] != True:
        dump_dict = {
            'd' : d,
            'c' : c}
        break

# If the bounds are violated, record the results
if resultsQ[-1] != True:
    print(f'bounds failed on iteration {i}')
    with open('bad_results_'+dt+'.pkl','wb') as f:
        pkl.dump(dump_dict,f)
else:
    print("all grads within bounds")
    print(f"max of all D is {max(resultsD)}")

sys.stdout = old_stdout
log_file.close()