diff --git a/handyrl/environment.py b/handyrl/environment.py
index 080a27b1..72bbecc6 100755
--- a/handyrl/environment.py
+++ b/handyrl/environment.py
@@ -14,17 +14,6 @@
 }
 
 
-def prepare_env(env_args):
-    env_name = env_args['env']
-    env_source = ENVS.get(env_name, env_name)
-    env_module = importlib.import_module(env_source)
-
-    if env_module is None:
-        print("No environment %s" % env_name)
-    elif hasattr(env_module, 'prepare'):
-        env_module.prepare()
-
-
 def make_env(env_args):
     env_name = env_args['env']
     env_source = ENVS.get(env_name, env_name)
diff --git a/handyrl/evaluation.py b/handyrl/evaluation.py
index 64f3306a..58f88387 100755
--- a/handyrl/evaluation.py
+++ b/handyrl/evaluation.py
@@ -7,7 +7,7 @@
 import time
 import multiprocessing as mp
 
-from .environment import prepare_env, make_env
+from .environment import make_env
 from .connection import send_recv, accept_socket_connections, connect_socket_connection
 from .agent import RandomAgent, RuleBasedAgent, Agent, EnsembleAgent, SoftAgent
 
@@ -367,7 +367,6 @@ def client_mp_child(env_args, model_path, conn):
 
 def eval_main(args, argv):
     env_args = args['env_args']
-    prepare_env(env_args)
     env = make_env(env_args)
 
     model_path = argv[0] if len(argv) >= 1 else 'models/latest.pth'
@@ -393,7 +392,6 @@ def eval_main(args, argv):
 def eval_server_main(args, argv):
     print('network match server mode')
     env_args = args['env_args']
-    prepare_env(env_args)
     env = make_env(env_args)
 
     num_games = int(argv[0]) if len(argv) >= 1 else 100
diff --git a/handyrl/train.py b/handyrl/train.py
index 07dbf81f..5355635c 100755
--- a/handyrl/train.py
+++ b/handyrl/train.py
@@ -21,7 +21,7 @@
 import torch.optim as optim
 import psutil
 
-from .environment import prepare_env, make_env
+from .environment import make_env
 from .util import map_r, bimap_r, trimap_r, rotate
 from .model import to_torch, to_gpu, ModelWrapper
 from .losses import compute_target
@@ -648,7 +648,6 @@ def run(self):
 
 
 def train_main(args):
-    prepare_env(args['env_args'])  # preparing environment is needed in stand-alone mode
     learner = Learner(args=args)
     learner.run()
 
diff --git a/handyrl/worker.py b/handyrl/worker.py
index 7fe28bc7..9a88aa31 100755
--- a/handyrl/worker.py
+++ b/handyrl/worker.py
@@ -13,7 +13,7 @@
 import pickle
 import copy
 
-from .environment import prepare_env, make_env
+from .environment import make_env
 from .connection import QueueCommunicator
 from .connection import send_recv, open_multiprocessing_connections
 from .connection import connect_socket_connection, accept_socket_connections
@@ -245,7 +245,6 @@ def __init__(self, args):
     def run(self):
         args = entry(self.args)
         print(args)
-        prepare_env(args['env'])
 
         # open worker
         process = []