# Path: deep_architect/searchers/random.py
# class RandomSearcher(Searcher):
# 
#     def __init__(self, search_space_fn, reset_default_scope_upon_sample=True):
#         Searcher.__init__(self, search_space_fn, reset_default_scope_upon_sample)
# 
#     def sample(self):
#         inputs, outputs = self.search_space_fn()
#         vs = random_specify(outputs)
#         return inputs, outputs, vs, {}
# 
#     def update(self, val, searcher_eval_token):
#         pass
# 
#     def save_state(self, folderpath):
#         pass
# 
#     def load_state(self, folderpath):
#         pass


import deep_architect.search_logging as sl
import deep_architect.visualization as vi
import deep_architect.utils as ut
import deep_architect.modules as mo
import deep_architect.contrib.misc.search_spaces.tensorflow.dnn as css_dnn
import search_space as ss
from deep_architect.searchers.random import RandomSearcher



def main():
    # Loading the config file.
    cfg = ut.get_config()
    # Creating the searcher.
    searcher = RandomSearcher(ss.search_space_fn)
    # Creating the search folder for logging information.
    sl.create_search_folderpath(cfg['folderpath'],
                                cfg['search_name'],
                                abort_if_exists=cfg["abort_if_exists"],

# Path: deep_architect/searchers/random.py
# class RandomSearcher(Searcher):
# 
#     def __init__(self, search_space_fn, reset_default_scope_upon_sample=True):
#         Searcher.__init__(self, search_space_fn, reset_default_scope_upon_sample)
# 
#     def sample(self):
#         inputs, outputs = self.search_space_fn()
#         vs = random_specify(outputs)
#         return inputs, outputs, vs, {}
# 
#     def update(self, val, searcher_eval_token):
#         pass
# 
#     def save_state(self, folderpath):
#         pass
# 
#     def load_state(self, folderpath):
#         pass


# Path: examples/simplest_multiworker/master.py
import deep_architect.search_logging as sl
import deep_architect.visualization as vi
import deep_architect.utils as ut
import deep_architect.modules as mo
import deep_architect.contrib.misc.search_spaces.tensorflow.dnn as css_dnn
import search_space as ss
from deep_architect.searchers.random import RandomSearcher




def main():
    # Loading the config file.
    cfg = ut.get_config()
    # Creating the searcher.
    searcher = RandomSearcher(ss.search_space_fn)
    # Creating the search folder for logging information.
    sl.create_search_folderpath(cfg['folderpath'],
                                cfg['search_name'],
                                abort_if_exists=cfg["abort_if_exists"],

                                delete_if_exists=cfg['delete_if_exists'],