fix errors from new flake8-comprehensions (#2917)

.pre-commit-config.yaml

             )$
 
 -   repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v0.720
+    rev: v0.740
     hooks:
     -   id: mypy
         name: mypy-ml-agents
         args: [--ignore-missing-imports, --disallow-incomplete-defs]
 
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v2.2.3
+    rev: v2.4.0
     hooks:
     -   id: mixed-line-ending
         exclude: >
         args: [--assume-in-merge]
 
 -   repo: https://github.com/pre-commit/pygrep-hooks
-    rev: v1.4.1  # Use the ref you want to point at
+    rev: v1.4.2
     hooks:
     -   id: python-check-mock-methods
 
-    rev: v2.4.3
+    rev: v2.4.4
     hooks:
     -   id: pylint
         exclude: >

gym-unity/gym_unity/envs/__init__.py

         self._n_agents = None
         self._multiagent = multiagent
         self._flattener = None
-        self.game_over = (
-            False
-        )  # Hidden flag used by Atari environments to determine if the game is over
+        # Hidden flag used by Atari environments to determine if the game is over
+        self.game_over = False
         self._allow_multiple_visual_obs = allow_multiple_visual_obs
 
         # Check brain configuration

ml-agents-envs/mlagents/envs/environment.py

         self.port = base_port + worker_id
         self._buffer_size = 12000
         self._version_ = UnityEnvironment.API_VERSION
-        self._loaded = (
-            False
-        )  # If true, this means the environment was successfully loaded
-        self.proc1 = (
-            None
-        )  # The process that is started. If None, no process was started
+        # If true, this means the environment was successfully loaded
+        self._loaded = False
+        # The process that is started. If None, no process was started
+        self.proc1 = None
         self.timeout_wait: int = timeout_wait
         self.communicator = self.get_communicator(worker_id, base_port, timeout_wait)
         self.worker_id = worker_id

ml-agents/mlagents/trainers/barracuda.py

 # pylint: skip-file
+# flake8: noqa
 from __future__ import print_function
 from collections import defaultdict
 import numpy as np

ml-agents/mlagents/trainers/ppo/models.py

                 )
             )
 
-        self.all_log_probs = tf.concat(
-            [branch for branch in policy_branches], axis=1, name="action_probs"
-        )
+        self.all_log_probs = tf.concat(policy_branches, axis=1, name="action_probs")
 
         self.action_masks = tf.placeholder(
             shape=[None, sum(self.act_size)], dtype=tf.float32, name="action_masks"

ml-agents/mlagents/trainers/sac/models.py

                         kernel_initializer=tf.initializers.variance_scaling(0.01),
                     )
                 )
-            all_logits = tf.concat(
-                [branch for branch in policy_branches], axis=1, name="action_probs"
-            )
+            all_logits = tf.concat(policy_branches, axis=1, name="action_probs")
+
             output, normalized_probs, normalized_logprobs = self.create_discrete_action_masking_layer(
                 all_logits, self.action_masks, self.act_size
             )

ml-agents/mlagents/trainers/tensorflow_to_barracuda.py

 # pylint: skip-file
+# flake8: noqa
 from __future__ import print_function
 import numpy as np
 import struct  # convert from Python values and C structs