def run_experiment(self, filename=None):
param_parser = self.agent.agent_get_parameters()
for trial in range(self.num_trials):
parameters = copy.deepcopy(self.configuration['agent']['params'])
# Randomize the parameters, those marked not optimizable get their default
for name, value in randomize_parameters(param_parser):
# Then, set the parameter value, but only if not already set
parameters.setdefault(name, value)
# Set params for current agent
self.agent.params = parameters
# Run a trial...
tmp_file = "rndtrial" + str(numpy.random.randint(1.e10)) + ".dat"
Episodic.run_experiment(self, filename = tmp_file)
# Collect results
locs, means, std = plotExperiment.processFile(tmp_file, self.evaluate, verbose=False, method=self.eval_reduce, kmeans_k=self.k)
json_out = copy.deepcopy(self.configuration)
json_out['agent']['params'] = parameters
json_out['experiment']['episodes'] = locs.tolist()
json_out['experiment']['returns'] = means.tolist()
json_out['experiment']['deviations'] = std.tolist()
if filename is None:
print json.dumps(json_out)
else:
with open(filename, "a") as f:
f.write(json.dumps(json_out) + "\n")
os.remove(tmp_file)
def run_experiment(self, filename=None):
param_parser = self.agent.agent_parameters()
for trial in range(self.num_trials):
parameters = copy.deepcopy(self.configuration['agent']['params'])
# Randomize the parameters, those marked not optimizable get their default
for name, value in randomize_parameters(param_parser):
# Then, set the parameter value, but only if not already set
parameters.setdefault(name, value)
# Set params for current agent
self.agent.params = parameters
# Run a trial...
tmp_file = "rndtrial" + str(numpy.random.randint(1.e10)) + ".dat"
Episodic.run_experiment(self, filename=tmp_file)
# Collect results
locs, means, std = plotExperiment.processFile(
tmp_file,
self.evaluate,
verbose=False,
method=self.eval_reduce,
kmeans_k=self.k)
json_out = copy.deepcopy(self.configuration)
json_out['agent']['params'] = parameters
json_out['experiment']['episodes'] = locs.tolist()
json_out['experiment']['returns'] = means.tolist()
json_out['experiment']['deviations'] = std.tolist()
if filename is None:
print json.dumps(json_out)
else:
with open(filename, "a") as f:
f.write(json.dumps(json_out) + "\n")
os.remove(tmp_file)
def __init__(self, config, **kwargs):
if not kwargs.has_key('agent') or not kwargs.has_key('environment'):
print "ERROR: RandomizedTrial must be run locally in order to randomize parameters."
import sys
sys.exit(1)
self.num_trials = kwargs.setdefault('num_trials', 1)
self.evaluate = kwargs.setdefault('evaluate', 'reward') #reward, steps, time
self.eval_reduce = kwargs.setdefault('evaluate_reduce', 'sum') # None, 'sum', 'final', 'kmeans'
self.k = kwargs.setdefault('kmeans_k', 10)
Episodic.__init__(self, config, **kwargs)
def main(job_id, params):
print "Anything printed here will end up in the output directory for job #:", str(job_id)
parameters = {}
for key in params:
if isinstance(key, unicode):
parameters[key.encode("utf-8")] = params[key]
else:
parameters[key] = params[key]
for key in parameters:
parameters[key] = map(lambda k: k.encode("utf-8") if isinstance(k, unicode) else k, parameters[key])
if len(parameters[key]) == 1:
value = parameters[key][0]
try:
value = float(value)
except:
if value.lower() == "false":
value = False
elif value.lower() == "true":
value = True
parameters[key] = value
print parameters
my_path = os.path.dirname(os.path.abspath(__file__))
tmp_file = os.path.join(my_path, "rndtrial" + str(numpy.random.randint(1.0e10)) + ".dat")
my_path = os.path.abspath(os.path.join(my_path, "experiment.json"))
agent, a_args, env, env_args, exp, exp_args = fromjson(my_path)
for key in parameters:
a_args.setdefault(key, parameters[key])
config = {
"agent": {"name": agent.name, "params": a_args},
"environment": {"name": env.name, "params": env_args},
"experiment": {"name": exp.name, "params": exp_args},
}
experiment = Episodic(config, agent=agent(**a_args), environment=env(**env_args), **exp_args)
# Using this try/except makes debugging in spearmint 1mil times easier
try:
experiment.run_experiment(filename=tmp_file)
except Exception as ex:
import traceback
traceback.print_exc()
locs, means, std = plotExperiment.processFile(tmp_file, "reward", verbose=False, method="sum")
os.remove(tmp_file)
print "Result:", -means[0]
return -means[0]
def __init__(self, config, **kwargs):
if not kwargs.has_key('agent') or not kwargs.has_key('environment'):
print "ERROR: RandomizedTrial must be run locally in order to randomize parameters."
import sys
sys.exit(1)
self.num_trials = kwargs.setdefault('num_trials', 1)
self.evaluate = kwargs.setdefault('evaluate',
'reward') #reward, steps, time
self.eval_reduce = kwargs.setdefault(
'evaluate_reduce', 'sum') # None, 'sum', 'final', 'kmeans'
self.k = kwargs.setdefault('kmeans_k', 10)
Episodic.__init__(self, config, **kwargs)
def main(job_id, params):
print 'Anything printed here will end up in the output directory for job #:', str(
job_id)
parameters = {}
for key in params:
if isinstance(key, unicode):
parameters[key.encode('utf-8')] = params[key]
else:
parameters[key] = params[key]
for key in parameters:
parameters[key] = map(
lambda k: k.encode('utf-8')
if isinstance(k, unicode) else k, parameters[key])
if len(parameters[key]) == 1:
value = parameters[key][0]
try:
value = float(value)
except:
if value.lower() == "false":
value = False
elif value.lower() == "true":
value = True
parameters[key] = value
print parameters
my_path = os.path.dirname(os.path.abspath(__file__))
tmp_file = os.path.join(
my_path, "rndtrial" + str(numpy.random.randint(1.e10)) + ".dat")
my_path = os.path.abspath(os.path.join(my_path, "experiment.json"))
agent, a_args, env, env_args, exp, exp_args = fromjson(my_path)
for key in parameters:
a_args.setdefault(key, parameters[key])
config = {
'agent': {
'name': agent.name,
'params': a_args
},
'environment': {
'name': env.name,
'params': env_args
},
'experiment': {
'name': exp.name,
'params': exp_args
}
}
experiment = Episodic(config,
agent=agent(**a_args),
environment=env(**env_args),
**exp_args)
# Using this try/except makes debugging in spearmint 1mil times easier
try:
experiment.run_experiment(filename=tmp_file)
except Exception as ex:
import traceback
traceback.print_exc()
locs, means, std = plotExperiment.processFile(tmp_file,
"reward",
verbose=False,
method="sum")
os.remove(tmp_file)
print "Result:", -means[0]
return -means[0]