remove pickles used for last friday's presentation

0_04pkls/bad_lenet_baseline.txt

-0.4399999976158142
-0.550000011920929

check_pickles.py

-import pickle
-from pprint import pprint
-
-with open('randomsearch_logs.pkl', 'rb') as file:
-    list = pickle.load(file)
-
-print(len(list))
-
-with open('gru_logs.pkl','rb') as file:
-    list = pickle.load(file)
-
-print(len(list))

plot_pickles.py

-import pickle
-from pprint import pprint
-import matplotlib.pyplot as plt
-from torch import gru
-
-def get_maxacc(log):
-    output = []
-    maxacc = 0
-    for policy, acc in log:
-        maxacc = max(maxacc, acc)
-        output.append(maxacc)
-    return output
-
-with open('randomsearch_logs.pkl', 'rb') as file:
-    rs_list = pickle.load(file)
-
-with open('gru_logs.pkl', 'rb') as file:
-    gru_list = pickle.load(file)
-
-
-plt.plot(get_maxacc(rs_list), label='randomsearcher')
-plt.plot(get_maxacc(gru_list), label='gru learner')
-plt.title('Comparing two agents')
-plt.ylabel('best accuracy to date')
-plt.xlabel('number of policies tested')
-plt.legend()
-plt.show()
-
-plt.plot([acc for pol,acc in rs_list], label='randomsearcher')
-plt.plot([acc for pol,acc in gru_list], label='gru learner')
-plt.title('Comparing two agents')
-plt.ylabel('best accuracy to date')
-plt.xlabel('number of policies tested')
-plt.legend()
-plt.show()
-
-
-def get_best5(log):
-    l = sorted(log, reverse=True, key=lambda x:x[1])
-    return (l[:5])
-
-def get_worst5(log):
-    l = sorted(log, key=lambda x:x[1])
-    return (l[:5])
-
-pprint(get_best5(rs_list))
-pprint(get_best5(gru_list))
\ No newline at end of file