remove pylint

.pre-commit-config.yaml

@@ -77,18 +77,6 @@ repos:
     hooks:
     -   id: python-check-mock-methods
 
--   repo: https://github.com/pre-commit/mirrors-pylint
-    rev: v2.4.4
-    hooks:
-    -   id: pylint
-        exclude: >
-            (?x)^(
-                .*_pb2.py|
-                .*_pb2_grpc.py|
-                .*/tests/.*
-            )$
-        args: [--score=n]
-
 - repo: https://github.com/mattlqx/pre-commit-search-and-replace
   rev: v1.0.3
   hooks:

ml-agents-envs/mlagents_envs/environment.py

@@ -468,7 +468,7 @@ def _returncode_to_signal_name(returncode: int) -> Optional[str]:
         """
         try:
             # A negative value -N indicates that the child was terminated by signal N (POSIX only).
-            s = signal.Signals(-returncode)  # pylint: disable=no-member
+            s = signal.Signals(-returncode)
             return s.name
         except Exception:
             # Should generally be a ValueError, but catch everything just in case.

ml-agents-envs/mlagents_envs/registry/binary_utils.py

@@ -38,7 +38,7 @@ def get_local_binary_path(name: str, url: str) -> str:
             break
         try:
             download_and_extract_zip(url, name)
-        except Exception:  # pylint: disable=W0702
+        except Exception:
             if attempt + 1 < NUMBER_ATTEMPTS:
                 logger.warning(
                     f"Attempt {attempt + 1} / {NUMBER_ATTEMPTS}"

ml-agents-envs/mlagents_envs/rpc_utils.py

@@ -220,9 +220,7 @@ def observation_to_np_array(
 def _process_visual_observation(
     obs_index: int,
     shape: Tuple[int, int, int],
-    agent_info_list: Collection[
-        AgentInfoProto
-    ],  # pylint: disable=unsubscriptable-object
+    agent_info_list: Collection[AgentInfoProto],
 ) -> np.ndarray:
     if len(agent_info_list) == 0:
         return np.zeros((0, shape[0], shape[1], shape[2]), dtype=np.float32)
@@ -256,11 +254,7 @@ def _raise_on_nan_and_inf(data: np.array, source: str) -> np.array:
 
 @timed
 def _process_vector_observation(
-    obs_index: int,
-    shape: Tuple[int, ...],
-    agent_info_list: Collection[
-        AgentInfoProto
-    ],  # pylint: disable=unsubscriptable-object
+    obs_index: int, shape: Tuple[int, ...], agent_info_list: Collection[AgentInfoProto]
 ) -> np.ndarray:
     if len(agent_info_list) == 0:
         return np.zeros((0,) + shape, dtype=np.float32)
@@ -277,10 +271,7 @@ def _process_vector_observation(
 
 @timed
 def steps_from_proto(
-    agent_info_list: Collection[
-        AgentInfoProto
-    ],  # pylint: disable=unsubscriptable-object
-    behavior_spec: BehaviorSpec,
+    agent_info_list: Collection[AgentInfoProto], behavior_spec: BehaviorSpec
 ) -> Tuple[DecisionSteps, TerminalSteps]:
     decision_agent_info_list = [
         agent_info for agent_info in agent_info_list if not agent_info.done

ml-agents/mlagents/torch_utils/torch.py

@@ -32,8 +32,6 @@ def assert_torch_installed():
 torch.set_num_threads(cpu_utils.get_num_threads_to_use())
 os.environ["KMP_BLOCKTIME"] = "0"
 
-# Known PyLint compatibility with PyTorch https://github.com/pytorch/pytorch/issues/701
-# pylint: disable=E1101
 if torch.cuda.is_available():
     torch.set_default_tensor_type(torch.cuda.FloatTensor)
     device = torch.device("cuda")

ml-agents/mlagents/trainers/barracuda.py

@@ -1,4 +1,3 @@
-# pylint: skip-file
 # flake8: noqa
 from __future__ import print_function
 from collections import defaultdict

ml-agents/mlagents/trainers/learn.py

@@ -42,7 +42,6 @@
 
 
 def get_version_string() -> str:
-    # pylint: disable=no-member
     return f""" Version information:
   ml-agents: {mlagents.trainers.__version__},
   ml-agents-envs: {mlagents_envs.__version__},

ml-agents/mlagents/trainers/optimizer/torch_optimizer.py

@@ -13,7 +13,7 @@
 from mlagents.trainers.torch.utils import ModelUtils
 
 
-class TorchOptimizer(Optimizer):  # pylint: disable=W0223
+class TorchOptimizer(Optimizer):
     def __init__(self, policy: TorchPolicy, trainer_settings: TrainerSettings):
         super().__init__()
         self.policy = policy

ml-agents/mlagents/trainers/policy/torch_policy.py

@@ -204,9 +204,7 @@ def get_action(
             for agent_id in decision_requests.agent_id
         ]  # For 1-D array, the iterator order is correct.
 
-        run_out = self.evaluate(
-            decision_requests, global_agent_ids
-        )  # pylint: disable=assignment-from-no-return
+        run_out = self.evaluate(decision_requests, global_agent_ids)
         self.save_memories(global_agent_ids, run_out.get("memory_out"))
         self.check_nan_action(run_out.get("action"))
         return ActionInfo(

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

@@ -76,7 +76,7 @@ def forward(
             # ExitStack allows us to enter the torch.no_grad() context conditionally
             with ExitStack() as stack:
                 if not q1_grad:
-                    stack.enter_context(torch.no_grad())  # pylint: disable=E1101
+                    stack.enter_context(torch.no_grad())
                 q1_out, _ = self.q1_network(
                     inputs,
                     actions=actions,
@@ -85,7 +85,7 @@ def forward(
                 )
             with ExitStack() as stack:
                 if not q2_grad:
-                    stack.enter_context(torch.no_grad())  # pylint: disable=E1101
+                    stack.enter_context(torch.no_grad())
                 q2_out, _ = self.q2_network(
                     inputs,
                     actions=actions,

ml-agents/mlagents/trainers/tests/torch/test_ppo.py

@@ -8,7 +8,7 @@
 from mlagents.trainers.tests import mock_brain as mb
 from mlagents.trainers.tests.test_trajectory import make_fake_trajectory
 from mlagents.trainers.settings import NetworkSettings
-from mlagents.trainers.tests.dummy_config import (  # noqa: F401; pylint: disable=unused-variable
+from mlagents.trainers.tests.dummy_config import (  # noqa: F401
     ppo_dummy_config,
     curiosity_dummy_config,
     gail_dummy_config,

ml-agents/mlagents/trainers/tests/torch/test_sac.py

@@ -5,7 +5,7 @@
 from mlagents.trainers.policy.torch_policy import TorchPolicy
 from mlagents.trainers.tests import mock_brain as mb
 from mlagents.trainers.settings import NetworkSettings
-from mlagents.trainers.tests.dummy_config import (  # noqa: F401; pylint: disable=unused-variable
+from mlagents.trainers.tests.dummy_config import (  # noqa: F401
     sac_dummy_config,
     curiosity_dummy_config,
 )

ml-agents/mlagents/trainers/trainer/rl_trainer.py

@@ -32,7 +32,7 @@
 logger = get_logger(__name__)
 
 
-class RLTrainer(Trainer):  # pylint: disable=abstract-method
+class RLTrainer(Trainer):
     """
     This class is the base class for trainers that use Reward Signals.
     """