forked from yamasakih/reinvent
-
Notifications
You must be signed in to change notification settings - Fork 0
/
reinforce_model.py
203 lines (170 loc) · 9.86 KB
/
reinforce_model.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
# coding=utf-8
import argparse
import contextlib
import json
import logging
import os
import sys
import time
import git
import models.reinvent
import reinforcement
import scoring
from utils import format_help_for_epilog, UnderscoreArgumentParser, FilePath, find_dir_suffix
def get_commit_hash():
try:
repo = git.Repo(search_parent_directories=True)
sha = repo.head.object.hexsha
except git.exc.InvalidGitRepositoryError:
logging.warning(
"Code is not from a valid git repository! Can't log the version of this code. "
"Please use git to have reproducible runs.")
sha = ""
return sha
def main():
strtime = time.strftime("%Y-%m-%d-%H_%M_%S", time.localtime())
logging.basicConfig(level=logging.DEBUG)
fmt = logging.Formatter(
fmt='%(asctime)s: %(module)s.%(funcName)s +%(lineno)s: %(levelname)-8s %(message)s',
datefmt='%H:%M:%S')
for handler in logging.getLogger().handlers:
handler.setFormatter(fmt)
_scoring_help = "\n".join([format_help_for_epilog(scoring.get_scoring_argparse(name), prefix=" scoring: ")
for name in sorted(scoring.allScoringFunctions)]) + "\n"
parser = UnderscoreArgumentParser(formatter_class=argparse.RawDescriptionHelpFormatter, add_help=False,
epilog=_scoring_help)
requiredArgs = parser.add_argument_group('required arguments')
optionalArgs = parser.add_argument_group('optional arguments')
optionalArgs.add_argument('-h', '--help', action='help', default=argparse.SUPPRESS,
help='show this help message and exit')
requiredArgs.add_argument("--scoring-function",
help='Scoring function to use. Allowed values are: ' +
', '.join(sorted(scoring.allScoringFunctions.keys())),
metavar="<scoring>", type=str, required=True,
choices=sorted(list(set(
list(scoring.allScoringFunctions.keys()) + [name.replace("-", "_") for name in
scoring.allScoringFunctions.keys()]))))
optionalArgs.add_argument("--name", help="Name of the experiment. Default: if no name is provided and the "
"script is running within SLURM it uses the name provided by "
"SLURM_JOB_NAME otherwise noname",
type=str,
default=None,
metavar="<str>")
optionalArgs.add_argument("--description", help="Description of the experiment. Currently just used in "
"Vizor. Default N/A", type=str,
default="N/A", metavar="<str>")
optionalArgs.add_argument("--prior", help='Prior to use. Default priors/ChEMBL/Prior.ckpt', type=str,
default='priors/ChEMBL/Prior.ckpt', metavar="<{}>".format(str(FilePath.__name__)))
optionalArgs.add_argument("--agent", help='Agent to use. If None the agent is initialized from the prior.',
type=str, default='None', metavar="<{}>".format(str(FilePath.__name__)))
optionalArgs.add_argument("--steps", help='Iterations to run. Default: 500', type=int, default=500, metavar="<int>")
optionalArgs.add_argument("--reset", help="Number of iteration after which the Agent is reset after the first "
"time the average score is above reset-cutoff-score."
"Default 0 (not active)",
type=int, default=0, metavar="<int>")
optionalArgs.add_argument("--reset-cutoff-score", help="Average Score which have to be reached to start the "
"reset countdown of the Agent. Default 0.6",
type=float, default=0.6, metavar="<float>")
optionalArgs.add_argument("--sigma", help='Scoring Sigma. Default: 120', type=float, default=120, metavar="<int>")
optionalArgs.add_argument("--temperature", "-t",
help=("Temperature for the sequence sampling. Has to be larger than 0. "
"Values below 1 make the RNN more confident in it's generation, "
"but also more conservative. Values larger than 1 result in more random sequences. "
"[DEFAULT: 1.0]"),
type=float, default=1.0, metavar="<float>")
optionalArgs.add_argument("--debug", "-v", help='Verbose messages', action='store_true', default=False)
optionalArgs.add_argument("--noteset", "-vv", help='More verbose messages', action='store_true', default=False)
optionalArgs.add_argument("--experience", help='Enable experience replay. Default False', type=bool,
default=False, metavar="<bool>")
optionalArgs.add_argument("--lr", help='Optimizer learning rate. Default: 0.0001', type=float, default=0.0001,
metavar="<float>")
optionalArgs.add_argument("--batch-size", help='How many compounds are sampled per step. Default: 128', type=int,
default=128, metavar="<int>")
optionalArgs.add_argument("--logdir",
help="Dictionary to save the log. Default ~/REINVENT/logs/<name>",
type=str, metavar="<{}>".format(str(FilePath.__name__)),
default=None)
optionalArgs.add_argument("--resultdir",
help="Dictionary to save the results. Default ~/REINVENT/results/<name>",
type=str, metavar="<{}>".format(str(FilePath.__name__)),
default=None)
args, extra_args = parser.parse_known_args()
# Setup the name
if args.name is None:
if "SLURM_JOB_NAME" in os.environ:
args.name = os.environ["SLURM_JOB_NAME"]
else:
args.name = "noname"
# Setup the logdir and resultdir
if args.logdir is None:
args.logdir = os.path.join(os.path.expanduser('~'), "REINVENT/logs/{}".format(args.name))
if args.resultdir is None:
args.resultdir = os.path.join(os.path.expanduser('~'), "REINVENT/results/{}".format(args.name))
args.logdir = os.path.normpath(args.logdir)
args.resultdir = os.path.normpath(args.resultdir)
if os.path.exists(args.logdir):
new_logdir = find_dir_suffix(args.logdir)
logging.info("Logdir already exists. Using {} instead".format(new_logdir))
args.logdir = new_logdir
if os.path.exists(args.resultdir):
new_resultdir = find_dir_suffix(args.resultdir)
logging.info("Resultdir already exists. Using {} instead".format(new_resultdir))
args.resultdir = new_resultdir
os.makedirs(args.logdir)
os.makedirs(args.resultdir)
# Set up the logging
fh = logging.FileHandler(os.path.join(args.logdir, 'output.log'))
fh.setLevel(logging.INFO)
dh = logging.FileHandler(os.path.join(args.logdir, 'debug.log'))
dh.setLevel(logging.DEBUG)
ch = logging.StreamHandler(sys.stdout)
if args.noteset:
ch.setLevel(logging.NOTSET)
elif args.debug:
ch.setLevel(logging.DEBUG)
else:
ch.setLevel(logging.INFO)
logginghandler = [fh, dh, ch]
for handler in logging.getLogger().handlers[:]:
logging.getLogger().removeHandler(handler)
for handler in logginghandler:
handler.setFormatter(fmt)
logging.getLogger().addHandler(handler)
# first we get the scoring function
scoring_parser = scoring.get_scoring_argparse(args.scoring_function)
scoring_args, extra_args = scoring_parser.parse_known_args(extra_args)
scoring_function = scoring.get_scoring_function(args.scoring_function, **vars(scoring_args))
# lets hope we have no arguments left. Otherwise we fail
if len(extra_args) > 0:
print("\n\033[91mERROR: unrecognized arguments: " + " ".join(extra_args) + "\033[0m\n")
parser.print_help()
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(args.logdir, 'output.log'))
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(args.logdir, 'debug.log'))
with contextlib.suppress(FileNotFoundError):
os.rmdir(args.logdir)
with contextlib.suppress(FileNotFoundError):
os.rmdir(args.resultdir)
exit(2)
prior = models.reinvent.Model.load_from_file(args.prior)
if args.agent == "None":
agent = models.reinvent.Model.load_from_file(args.prior)
else:
agent = models.reinvent.Model.load_from_file(args.agent)
metadata = {"name": args.name, "description": args.description, "date": strtime, "commit": get_commit_hash(),
'arguments': sys.argv}
metadata = json.dumps(metadata, sort_keys=True, indent=4, separators=(',', ': '))
with open(args.logdir + "/metadata.json", 'w') as f:
f.write(metadata + "\n")
reinforcement.reinforcement_learning(agent=agent, prior=prior,
scoring_function=scoring_function,
n_steps=args.steps,
experience_replay=args.experience, reset=args.reset,
reset_score_cutoff=args.reset_cutoff_score,
logdir=args.logdir, resultdir=args.resultdir,
lr=args.lr, sigma=args.sigma,
batch_size=args.batch_size,
temperature=args.temperature)
if __name__ == "__main__":
main()