clean imports

convlab/__init__.py

@@ -1,17 +1,17 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT license.
 
-from convlab.modules.usr import UserSimulator
-from convlab.modules.nlu.multiwoz import ErrorNLU, OneNetLU, MILU, SVMNLU
+import os
+
 from convlab.modules.dst.multiwoz import RuleDST
-from convlab.modules.word_dst.multiwoz import MDBTTracker
+from convlab.modules.nlg.multiwoz import TemplateNLG, MultiwozTemplateNLG, SCLSTM
+from convlab.modules.nlu.multiwoz import ErrorNLU, OneNetLU, MILU, SVMNLU
 from convlab.modules.policy.system.multiwoz import RuleBasedMultiwozBot, RuleInformBot, VanillaMLEPolicy
 from convlab.modules.policy.user.multiwoz import UserPolicyAgendaMultiWoz
-from convlab.modules.nlg.multiwoz import TemplateNLG, MultiwozTemplateNLG, SCLSTM
+from convlab.modules.usr import UserSimulator
+from convlab.modules.word_dst.multiwoz import MDBTTracker
 from convlab.modules.word_policy.multiwoz import MDRGWordPolicy
 
-import os
-
 os.environ['PY_ENV'] = os.environ.get('PY_ENV') or 'development'
 ROOT_DIR = os.path.normpath(os.path.join(os.path.dirname(__file__), '..'))
 

convlab/agent/__init__.py

@@ -1,21 +1,21 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+from copy import deepcopy
+
 # The agent module
 import numpy as np
 import pandas as pd
 import pydash as ps
 import torch
-from copy import deepcopy
 
+from convlab import evaluator
 from convlab.agent import algorithm, memory
 from convlab.agent.algorithm import policy_util
 from convlab.agent.net import net_util
 from convlab.lib import logger, util
 from convlab.lib.decorator import lab_api
 from convlab.modules import nlu, dst, word_dst, nlg, state_encoder, action_decoder
-from convlab import evaluator
-
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/__init__.py

@@ -10,9 +10,9 @@
 # expose all the classes
 from .actor_critic import *
 from .dqn import *
+from .external import *
 from .ppo import *
 from .random import *
 from .reinforce import *
 from .sarsa import *
 from .sil import *
-from .external import *

convlab/agent/algorithm/actor_critic.py

@@ -1,15 +1,16 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+import numpy as np
+import pydash as ps
+import torch
+
 from convlab.agent import net
 from convlab.agent.algorithm import policy_util
 from convlab.agent.algorithm.reinforce import Reinforce
 from convlab.agent.net import net_util
 from convlab.lib import logger, math_util, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
-import torch
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/base.py

@@ -2,11 +2,13 @@
 # Licensed under the MIT license.
 
 from abc import ABC, abstractmethod
+
+import numpy as np
+import pydash as ps
+
 from convlab.agent.net import net_util
 from convlab.lib import logger, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/dqn.py

@@ -1,16 +1,15 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+import numpy as np
+import torch
+
+from convlab.agent import memory
 from convlab.agent import net
-from convlab.agent import memory 
-from convlab.agent.algorithm import policy_util
 from convlab.agent.algorithm.sarsa import SARSA
 from convlab.agent.net import net_util
-from convlab.lib import logger, math_util, util
+from convlab.lib import logger, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
-import torch
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/external.py

@@ -5,16 +5,16 @@
 The random agent algorithm
 For basic dev purpose.
 '''
-from convlab.agent.algorithm.base import Algorithm
+from copy import deepcopy
+
+import pydash as ps
+
 from convlab.agent.algorithm import policy_util
+from convlab.agent.algorithm.base import Algorithm
 from convlab.lib import logger, util
 from convlab.lib.decorator import lab_api
 from convlab.modules import policy, word_policy, e2e
 
-import numpy as np
-from copy import deepcopy
-import pydash as ps
-
 logger = logger.get_logger(__name__)
 
 

convlab/agent/algorithm/policy_util.py

@@ -1,16 +1,16 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+import numpy as np
+import torch
+import torch.nn.functional as F
 # Action policy module
 # Constructs action probability distribution used by agent to sample action and calculate log_prob, entropy, etc.
 from gym import spaces
+from torch import distributions
+
 # from convlab.env.wrapper import LazyFrames
 from convlab.lib import distribution, logger, math_util, util
-from torch import distributions
-import numpy as np
-import pydash as ps
-import torch
-import torch.nn.functional as F
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/ppo.py

@@ -2,15 +2,15 @@
 # Licensed under the MIT license.
 
 from copy import deepcopy
-from convlab.agent import net
+
+import numpy as np
+import torch
+
 from convlab.agent.algorithm import policy_util
 from convlab.agent.algorithm.actor_critic import ActorCritic
 from convlab.agent.net import net_util
 from convlab.lib import logger, math_util, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
-import torch
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/random.py

@@ -1,12 +1,13 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+import numpy as np
+
 # The random agent algorithm
 # For basic dev purpose
 from convlab.agent.algorithm.base import Algorithm
 from convlab.lib import logger
 from convlab.lib.decorator import lab_api
-import numpy as np
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/reinforce.py

@@ -1,13 +1,14 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+import numpy as np
+
 from convlab.agent import net
 from convlab.agent.algorithm import policy_util
 from convlab.agent.algorithm.base import Algorithm
 from convlab.agent.net import net_util
 from convlab.lib import logger, math_util, util
 from convlab.lib.decorator import lab_api
-import numpy as np
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/sarsa.py

@@ -1,15 +1,15 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+import numpy as np
+import torch
+
 from convlab.agent import net
 from convlab.agent.algorithm import policy_util
 from convlab.agent.algorithm.base import Algorithm
 from convlab.agent.net import net_util
 from convlab.lib import logger, math_util, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
-import torch
 
 logger = logger.get_logger(__name__)
 

convlab/agent/algorithm/sil.py

@@ -1,15 +1,15 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
-from convlab.agent import net, memory
+import numpy as np
+import torch
+
+from convlab.agent import memory
 from convlab.agent.algorithm import policy_util
 from convlab.agent.algorithm.actor_critic import ActorCritic
 from convlab.agent.algorithm.ppo import PPO
 from convlab.lib import logger, math_util, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
-import torch
 
 logger = logger.get_logger(__name__)
 

convlab/agent/memory/__init__.py

@@ -6,7 +6,7 @@
 Contains different ways of storing an agents experiences and sampling from them
 '''
 
-# expose all the classes
-from .replay import *
 from .onpolicy import *
 from .prioritized import *
+# expose all the classes
+from .replay import *

convlab/agent/memory/base.py

@@ -2,10 +2,8 @@
 # Licensed under the MIT license.
 
 from abc import ABC, abstractmethod
-from collections import deque
-from convlab.lib import logger, util
-import numpy as np
-import pydash as ps
+
+from convlab.lib import logger
 
 logger = logger.get_logger(__name__)
 

convlab/agent/memory/onpolicy.py

@@ -1,13 +1,9 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
-from collections import deque
-from copy import deepcopy
 from convlab.agent.memory.base import Memory
 from convlab.lib import logger, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
 
 logger = logger.get_logger(__name__)
 

convlab/agent/memory/prioritized.py

@@ -1,11 +1,12 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
+import random
+
+import numpy as np
+
 from convlab.agent.memory.replay import Replay
 from convlab.lib import util
-from convlab.lib.decorator import lab_api
-import numpy as np
-import random
 
 
 class SumTree:

convlab/agent/memory/replay.py

@@ -1,13 +1,11 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
-from collections import deque
-from copy import deepcopy
+import numpy as np
+
 from convlab.agent.memory.base import Memory
-from convlab.lib import logger, math_util, util
+from convlab.lib import logger, util
 from convlab.lib.decorator import lab_api
-import numpy as np
-import pydash as ps
 
 logger = logger.get_logger(__name__)
 

convlab/agent/net/base.py

@@ -1,12 +1,14 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
-from abc import ABC, abstractmethod
-from convlab.agent.net import net_util
+from abc import ABC
+
 import pydash as ps
 import torch
 import torch.nn as nn
 
+from convlab.agent.net import net_util
+
 
 class Net(ABC):
  '''Abstract Net class to define the API methods'''

convlab/agent/net/conv.py

@@ -1,13 +1,14 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
-from convlab.agent.net import net_util
-from convlab.agent.net.base import Net
-from convlab.lib import math_util, util
 import pydash as ps
 import torch
 import torch.nn as nn
 
+from convlab.agent.net import net_util
+from convlab.agent.net.base import Net
+from convlab.lib import math_util, util
+
 
 class ConvNet(Net, nn.Module):
  '''

convlab/agent/net/mlp.py

@@ -1,14 +1,15 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
-from convlab.agent.net import net_util
-from convlab.agent.net.base import Net
-from convlab.lib import math_util, util
 import numpy as np
 import pydash as ps
 import torch
 import torch.nn as nn
 
+from convlab.agent.net import net_util
+from convlab.agent.net.base import Net
+from convlab.lib import math_util, util
+
 
 class MLPNet(Net, nn.Module):
  '''

convlab/agent/net/net_util.py

@@ -1,13 +1,15 @@
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
-from functools import partial, wraps
-from convlab.lib import logger, optimizer, util
 import os
+from functools import partial, wraps
+
 import pydash as ps
 import torch
 import torch.nn as nn
 
+from convlab.lib import logger, optimizer, util
+
 logger = logger.get_logger(__name__)
 
 # register custom torch.optim