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Cleanup imports.

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Till now, most of the modules were importing all of the module objects
(variables, classes, functions, other imports) into module namespace,
which potentially could (and was) cause of unintentional use of class or
methods, which was indirect imported.

With this patch, all the star imports were substituted with top-level
module, which provides desired class or function.

Besides, all imports where sorted (where possible) in a way pep8[1]
suggests - first are imports from standard library, than goes third
party imports (like numpy, tensorflow etc) and finally coach modules.
All of those sections are separated by one empty line.

[1] https://www.python.org/dev/peps/pep-0008/#imports
This commit is contained in:
Roman Dobosz
2018-04-12 19:46:32 +02:00
parent cafa152382
commit 1b095aeeca
75 changed files with 1169 additions and 1139 deletions
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36
agents/human_agent.py
View File

@@ -13,31 +13,37 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
import collections
import os
from agents.agent import *
import pygame
from pandas.io import pickle
from agents import agent
import logger
import utils
class HumanAgent(Agent):
class HumanAgent(agent.Agent):
def __init__(self, env, tuning_parameters, replicated_device=None, thread_id=0):
Agent.__init__(self, env, tuning_parameters, replicated_device, thread_id)
agent.Agent.__init__(self, env, tuning_parameters, replicated_device, thread_id)
self.clock = pygame.time.Clock()
self.max_fps = int(self.tp.visualization.max_fps_for_human_control)
screen.log_title("Human Control Mode")
utils.screen.log_title("Human Control Mode")
available_keys = self.env.get_available_keys()
if available_keys:
screen.log("Use keyboard keys to move. Press escape to quit. Available keys:")
screen.log("")
utils.screen.log("Use keyboard keys to move. Press escape to quit. Available keys:")
utils.screen.log("")
for action, key in self.env.get_available_keys():
screen.log("\t- {}: {}".format(action, key))
screen.separator()
utils.screen.log("\t- {}: {}".format(action, key))
utils.screen.separator()
def train(self):
return 0
def choose_action(self, curr_state, phase=RunPhase.TRAIN):
def choose_action(self, curr_state, phase=utils.RunPhase.TRAIN):
action = self.env.get_action_from_user()
# keep constant fps
@@ -49,16 +55,16 @@ class HumanAgent(Agent):
return action, {"action_value": 0}
def save_replay_buffer_and_exit(self):
replay_buffer_path = os.path.join(logger.experiments_path, 'replay_buffer.p')
replay_buffer_path = os.path.join(logger.logger.experiments_path, 'replay_buffer.p')
self.memory.tp = None
to_pickle(self.memory, replay_buffer_path)
screen.log_title("Replay buffer was stored in {}".format(replay_buffer_path))
pickle.to_pickle(self.memory, replay_buffer_path)
utils.screen.log_title("Replay buffer was stored in {}".format(replay_buffer_path))
exit()
def log_to_screen(self, phase):
# log to screen
screen.log_dict(
OrderedDict([
# log to utils.screen
utils.screen.log_dict(
collections.OrderedDict([
("Episode", self.current_episode),
("total reward", self.total_reward_in_current_episode),
("steps", self.total_steps_counter)