def test_generate_specs(self):
multiple_spec = MultipleSpecEntity({
'problem_names':
self.problem_names,
'dim_xs':
self.dim_xs,
'choose_noises':
self.choose_noises,
'bounds_domain_xs': [[self.bound]],
'number_points_each_dimensions':
self.number_points_each_dimensions,
'method_optimizations':
self.method_optimizations,
'training_names': [self.training_name],
'bounds_domains':
self.bounds_domain_xs,
'type_boundss': [[0]],
'n_trainings': [10],
'type_kernels': [self.type_kernel],
'dimensionss': [self.dimensions],
})
specs = SpecService.generate_specs(1, multiple_spec)
assert len(specs) == 1
for s in specs:
s.validate()
default=5)
parser.add_argument('--output_file',
type=str,
help='output file',
default='output.json')
args = parser.parse_args()
output_file = args.output_file
n_spec = int(args.spec)
output_file = 'spec_%d' % n_spec + '_' + output_file
multiple_spec = MultipleSpecEntity.from_json(args.multiple_spec)
spec = SpecService.generate_specs(n_spec, multiple_spec)
result = BGO.run_spec(spec)
with open(args.output_file, 'w') as f:
ujson.dump(result, f)
# results = []
# for spec in specs:
# result = {
# 'problem_name': spec.problem_name,
# 'method_optimization': spec.method_optimization,
# 'result': BGO.run_spec(spec)
# }
# results.append(result)