#=========================================================================================
here = utils.get_here(__file__)
parent = utils.get_parent(here)
dopath = join(parent, 'examples')
modelspath = join(parent, 'examples', 'models')
analysispath = join(parent, 'examples', 'analysis')
paperpath = join(parent, 'paper')
timespath = join(paperpath, 'times')
paperdatapath = join(paperpath, 'work', 'data')
paperfigspath = join(paperpath, 'work', 'figs')
# Make paths
for path in [timespath, paperdatapath, paperfigspath]:
utils.mkdir_p(path)
def call(s):
if simulate:
print(3*' ' + s)
else:
rval = subprocess.call(s.split())
if rval != 0:
sys.stdout.flush()
print("Something went wrong (return code {}).".format(rval))
sys.exit(1)
def train(model, seed=None, main=False):
if seed is None:
extra = ''
else:
name = os.path.splitext(os.path.basename(modelfile))[0] + suffix
# Scratch
scratchpath = os.environ.get('SCRATCH')
if scratchpath is None:
scratchpath = os.path.join(os.environ['USERPROFILE'], 'scratch')
trialspath = os.path.join(scratchpath, 'work', 'pyrl', prefix, name)
# Paths
workpath = os.path.join(here, 'work')
datapath = os.path.join(workpath, 'data', name)
figspath = os.path.join(workpath, 'figs', name)
# Create necessary directories
for path in [datapath, figspath, trialspath]:
utils.mkdir_p(path)
# File to store model in
savefile = os.path.join(datapath, name + '.pkl')
#=========================================================================================
# Info
#=========================================================================================
if action == 'info':
# Model specification
model = Model(modelfile)
# Create a PolicyGradient instance
pg = model.get_pg(savefile, seed)