from pylearn2.config import yaml_parse
from pylearn2.datasets.mjsynth.mjsynth import MJSYNTH
from pylearn2.datasets.mjsynth.config import Config
def output_file_string(params):
string = []
for key in params.keys():
string.append(key + ": " + str(params[key]))
return ' '.join(string)
p = Parser()
while p.has_other_configurations():
with open(Config.getYamlFilename(), 'r') as f:
yaml_file = f.read()
hyper_params = p.get_next_configuration()
outputFile = open('tests/' + p.get_num_configuration().__str__(), 'w')
sys.stdout = outputFile
sys.stderr = outputFile
yaml_file = yaml_file % (hyper_params)
print yaml_file
train = yaml_parse.load(yaml_file)
try:
train.main_loop()
except Exception as e:
from pylearn2.datasets.mjsynth.mjsynth import MJSYNTH
from pylearn2.datasets.mjsynth.config import Config
def output_file_string(params):
string = []
for key in params.keys():
string.append(key + ": " + str(params[key]))
return " ".join(string)
p = Parser()
while p.has_other_configurations():
with open(Config.getYamlFilename(), "r") as f:
yaml_file = f.read()
hyper_params = p.get_next_configuration()
outputFile = open("tests/" + p.get_num_configuration().__str__(), "w")
sys.stdout = outputFile
sys.stderr = outputFile
yaml_file = yaml_file % (hyper_params)
print yaml_file
train = yaml_parse.load(yaml_file)
try:
train.main_loop()
except Exception as e:
