[Formatting] Upgrade formatting libs (pytorch#705)

* init * amend * amend * amend * amend * lint * itertools.islice
ai4co · Nov 24, 2022 · d27d070 · d27d070
1 parent f1ad6cf
commit d27d070
Show file tree

Hide file tree

Showing 91 changed files with 460 additions and 513 deletions.
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -11,18 +11,23 @@ repos:
       - id: end-of-file-fixer
 
   - repo: https://github.com/omnilib/ufmt
-    rev: v1.3.2
+    rev: v2.0.0b2
     hooks:
       - id: ufmt
         additional_dependencies:
-          - black == 21.9b0
-          - usort == 0.6.4
+          - black == 22.3.0
+          - usort == 1.0.3
+          - libcst == 0.4.7
 
   - repo: https://github.com/pycqa/flake8
-    rev: 3.9.2
+    rev: 4.0.1
     hooks:
       - id: flake8
         args: [--config=setup.cfg]
+        additional_dependencies:
+          - flake8-bugbear==22.10.27
+          - flake8-comprehensions==3.10.1
+
 
   - repo: https://github.com/PyCQA/pydocstyle
     rev: 6.1.1

diff --git a/benchmarks/storage/benchmark_sample_latency_over_rpc.py b/benchmarks/storage/benchmark_sample_latency_over_rpc.py
@@ -44,9 +44,9 @@
 }
 
 storage_arg_options = {
-    "LazyMemmapStorage": dict(scratch_dir="/tmp/", device=torch.device("cpu")),
-    "LazyTensorStorage": dict(),
-    "ListStorage": dict(),
+    "LazyMemmapStorage": {"scratch_dir": "/tmp/", "device": torch.device("cpu")},
+    "LazyTensorStorage": {},
+    "ListStorage": {},
 }
 parser = argparse.ArgumentParser(
     description="RPC Replay Buffer Example",

diff --git a/build_tools/setup_helpers/__init__.py b/build_tools/setup_helpers/__init__.py
@@ -3,4 +3,4 @@
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
 
-from .extension import get_ext_modules, CMakeBuild  # noqa
+from .extension import CMakeBuild, get_ext_modules  # noqa
diff --git a/build_tools/setup_helpers/extension.py b/build_tools/setup_helpers/extension.py
@@ -8,7 +8,7 @@
 import platform
 import subprocess
 from pathlib import Path
-from subprocess import check_output, STDOUT, CalledProcessError
+from subprocess import CalledProcessError, check_output, STDOUT
 
 import torch
 from setuptools import Extension

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -150,7 +150,7 @@
 }
 
 
-aafig_default_options = dict(scale=1.5, aspect=1.0, proportional=True)
+aafig_default_options = {"scale": 1.5, "aspect": 1.0, "proportional": True}
 
 # -- Generate knowledge base references -----------------------------------
 current_path = os.path.dirname(os.path.realpath(__file__))

diff --git a/examples/ddpg/ddpg.py b/examples/ddpg/ddpg.py
@@ -12,7 +12,7 @@
 import hydra
 import torch.cuda
 from hydra.core.config_store import ConfigStore
-from torchrl.envs import ParallelEnv, EnvCreator
+from torchrl.envs import EnvCreator, ParallelEnv
 from torchrl.envs.transforms import RewardScaling, TransformedEnv
 from torchrl.envs.utils import set_exploration_mode
 from torchrl.modules import OrnsteinUhlenbeckProcessWrapper
@@ -23,21 +23,15 @@
 )
 from torchrl.trainers.helpers.envs import (
     correct_for_frame_skip,
+    EnvConfig,
     get_stats_random_rollout,
     parallel_env_constructor,
     transformed_env_constructor,
-    EnvConfig,
 )
 from torchrl.trainers.helpers.logger import LoggerConfig
-from torchrl.trainers.helpers.losses import make_ddpg_loss, LossConfig
-from torchrl.trainers.helpers.models import (
-    make_ddpg_actor,
-    DDPGModelConfig,
-)
-from torchrl.trainers.helpers.replay_buffer import (
-    make_replay_buffer,
-    ReplayArgsConfig,
-)
+from torchrl.trainers.helpers.losses import LossConfig, make_ddpg_loss
+from torchrl.trainers.helpers.models import DDPGModelConfig, make_ddpg_actor
+from torchrl.trainers.helpers.replay_buffer import make_replay_buffer, ReplayArgsConfig
 from torchrl.trainers.helpers.trainers import make_trainer, TrainerConfig
 
 config_fields = [

diff --git a/examples/dqn/dqn.py b/examples/dqn/dqn.py
@@ -12,7 +12,7 @@
 import hydra
 import torch.cuda
 from hydra.core.config_store import ConfigStore
-from torchrl.envs import ParallelEnv, EnvCreator
+from torchrl.envs import EnvCreator, ParallelEnv
 from torchrl.envs.transforms import RewardScaling, TransformedEnv
 from torchrl.modules import EGreedyWrapper
 from torchrl.record import VideoRecorder
@@ -22,21 +22,15 @@
 )
 from torchrl.trainers.helpers.envs import (
     correct_for_frame_skip,
+    EnvConfig,
     get_stats_random_rollout,
     parallel_env_constructor,
     transformed_env_constructor,
-    EnvConfig,
 )
 from torchrl.trainers.helpers.logger import LoggerConfig
-from torchrl.trainers.helpers.losses import make_dqn_loss, LossConfig
-from torchrl.trainers.helpers.models import (
-    make_dqn_actor,
-    DiscreteModelConfig,
-)
-from torchrl.trainers.helpers.replay_buffer import (
-    make_replay_buffer,
-    ReplayArgsConfig,
-)
+from torchrl.trainers.helpers.losses import LossConfig, make_dqn_loss
+from torchrl.trainers.helpers.models import DiscreteModelConfig, make_dqn_actor
+from torchrl.trainers.helpers.replay_buffer import make_replay_buffer, ReplayArgsConfig
 from torchrl.trainers.helpers.trainers import make_trainer, TrainerConfig
 
 

diff --git a/examples/dreamer/dreamer.py b/examples/dreamer/dreamer.py
@@ -8,12 +8,12 @@
 import torch.cuda
 import tqdm
 from dreamer_utils import (
-    parallel_env_constructor,
-    transformed_env_constructor,
     call_record,
+    EnvConfig,
     grad_norm,
     make_recorder_env,
-    EnvConfig,
+    parallel_env_constructor,
+    transformed_env_constructor,
 )
 from hydra.core.config_store import ConfigStore
 
@@ -38,14 +38,8 @@
     get_stats_random_rollout,
 )
 from torchrl.trainers.helpers.logger import LoggerConfig
-from torchrl.trainers.helpers.models import (
-    make_dreamer,
-    DreamerConfig,
-)
-from torchrl.trainers.helpers.replay_buffer import (
-    make_replay_buffer,
-    ReplayArgsConfig,
-)
+from torchrl.trainers.helpers.models import DreamerConfig, make_dreamer
+from torchrl.trainers.helpers.replay_buffer import make_replay_buffer, ReplayArgsConfig
 from torchrl.trainers.helpers.trainers import TrainerConfig
 from torchrl.trainers.trainers import Recorder, RewardNormalizer
 

diff --git a/examples/dreamer/dreamer_utils.py b/examples/dreamer/dreamer_utils.py
@@ -2,9 +2,8 @@
 #
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
-from dataclasses import dataclass
-from dataclasses import field as dataclass_field
-from typing import Callable, Optional, Union, Any, Sequence
+from dataclasses import dataclass, field as dataclass_field
+from typing import Any, Callable, Optional, Sequence, Union
 
 from torchrl.data import NdUnboundedContinuousTensorSpec
 from torchrl.envs import ParallelEnv
@@ -14,6 +13,7 @@
 from torchrl.envs.libs.gym import GymEnv
 from torchrl.envs.transforms import (
     CatFrames,
+    CenterCrop,
     DoubleToFloat,
     GrayScale,
     NoopResetEnv,
@@ -22,12 +22,8 @@
     RewardScaling,
     ToTensorImage,
     TransformedEnv,
-    CenterCrop,
-)
-from torchrl.envs.transforms.transforms import (
-    FlattenObservation,
-    TensorDictPrimer,
 )
+from torchrl.envs.transforms.transforms import FlattenObservation, TensorDictPrimer
 from torchrl.record.recorder import VideoRecorder
 from torchrl.trainers.loggers import Logger
 

diff --git a/examples/ppo/ppo.py b/examples/ppo/ppo.py
@@ -12,7 +12,7 @@
 import hydra
 import torch.cuda
 from hydra.core.config_store import ConfigStore
-from torchrl.envs import ParallelEnv, EnvCreator
+from torchrl.envs import EnvCreator, ParallelEnv
 from torchrl.envs.transforms import RewardScaling, TransformedEnv
 from torchrl.envs.utils import set_exploration_mode
 from torchrl.objectives.value import GAE
@@ -23,17 +23,14 @@
 )
 from torchrl.trainers.helpers.envs import (
     correct_for_frame_skip,
+    EnvConfig,
     get_stats_random_rollout,
     parallel_env_constructor,
     transformed_env_constructor,
-    EnvConfig,
 )
 from torchrl.trainers.helpers.logger import LoggerConfig
 from torchrl.trainers.helpers.losses import make_ppo_loss, PPOLossConfig
-from torchrl.trainers.helpers.models import (
-    make_ppo_model,
-    PPOModelConfig,
-)
+from torchrl.trainers.helpers.models import make_ppo_model, PPOModelConfig
 from torchrl.trainers.helpers.trainers import make_trainer, TrainerConfig
 
 config_fields = [

diff --git a/examples/redq/redq.py b/examples/redq/redq.py
@@ -12,7 +12,7 @@
 import hydra
 import torch.cuda
 from hydra.core.config_store import ConfigStore
-from torchrl.envs import ParallelEnv, EnvCreator
+from torchrl.envs import EnvCreator, ParallelEnv
 from torchrl.envs.transforms import RewardScaling, TransformedEnv
 from torchrl.envs.utils import set_exploration_mode
 from torchrl.modules import OrnsteinUhlenbeckProcessWrapper
@@ -23,21 +23,15 @@
 )
 from torchrl.trainers.helpers.envs import (
     correct_for_frame_skip,
+    EnvConfig,
     get_stats_random_rollout,
     parallel_env_constructor,
     transformed_env_constructor,
-    EnvConfig,
 )
 from torchrl.trainers.helpers.logger import LoggerConfig
-from torchrl.trainers.helpers.losses import make_redq_loss, LossConfig
-from torchrl.trainers.helpers.models import (
-    make_redq_model,
-    REDQModelConfig,
-)
-from torchrl.trainers.helpers.replay_buffer import (
-    make_replay_buffer,
-    ReplayArgsConfig,
-)
+from torchrl.trainers.helpers.losses import LossConfig, make_redq_loss
+from torchrl.trainers.helpers.models import make_redq_model, REDQModelConfig
+from torchrl.trainers.helpers.replay_buffer import make_replay_buffer, ReplayArgsConfig
 from torchrl.trainers.helpers.trainers import make_trainer, TrainerConfig
 
 config_fields = [

diff --git a/examples/sac/sac.py b/examples/sac/sac.py
@@ -12,7 +12,7 @@
 import hydra
 import torch.cuda
 from hydra.core.config_store import ConfigStore
-from torchrl.envs import ParallelEnv, EnvCreator
+from torchrl.envs import EnvCreator, ParallelEnv
 from torchrl.envs.transforms import RewardScaling, TransformedEnv
 from torchrl.envs.utils import set_exploration_mode
 from torchrl.modules import OrnsteinUhlenbeckProcessWrapper
@@ -23,21 +23,15 @@
 )
 from torchrl.trainers.helpers.envs import (
     correct_for_frame_skip,
+    EnvConfig,
     get_stats_random_rollout,
     parallel_env_constructor,
     transformed_env_constructor,
-    EnvConfig,
 )
 from torchrl.trainers.helpers.logger import LoggerConfig
-from torchrl.trainers.helpers.losses import make_sac_loss, LossConfig
-from torchrl.trainers.helpers.models import (
-    make_sac_model,
-    SACModelConfig,
-)
-from torchrl.trainers.helpers.replay_buffer import (
-    make_replay_buffer,
-    ReplayArgsConfig,
-)
+from torchrl.trainers.helpers.losses import LossConfig, make_sac_loss
+from torchrl.trainers.helpers.models import make_sac_model, SACModelConfig
+from torchrl.trainers.helpers.replay_buffer import make_replay_buffer, ReplayArgsConfig
 from torchrl.trainers.helpers.trainers import make_trainer, TrainerConfig
 
 config_fields = [

diff --git a/examples/torchrl_features/memmap_td_distributed.py b/examples/torchrl_features/memmap_td_distributed.py
@@ -89,25 +89,25 @@ def tensordict_add_noreturn():
             time.sleep(1)
             t0 = time.time()
             for w in range(1, args.world_size):
-                fut0 = rpc.rpc_async(f"worker{w}", get_tensordict, args=tuple())
+                fut0 = rpc.rpc_async(f"worker{w}", get_tensordict, args=())
                 fut0.wait()
-                fut1 = rpc.rpc_async(f"worker{w}", tensordict_add, args=tuple())
+                fut1 = rpc.rpc_async(f"worker{w}", tensordict_add, args=())
                 tensordict2 = fut1.wait()
                 tensordict2.clone()
             print("time: ", time.time() - t0)
         elif args.task == 1:
             time.sleep(1)
             t0 = time.time()
             waiters = [
-                rpc.remote(f"worker{w}", get_tensordict, args=tuple())
+                rpc.remote(f"worker{w}", get_tensordict, args=())
                 for w in range(1, args.world_size)
             ]
             td = torch.stack([waiter.to_here() for waiter in waiters], 0).contiguous()
             print("time: ", time.time() - t0)
 
             t0 = time.time()
             waiters = [
-                rpc.remote(f"worker{w}", tensordict_add, args=tuple())
+                rpc.remote(f"worker{w}", tensordict_add, args=())
                 for w in range(1, args.world_size)
             ]
             td = torch.stack([waiter.to_here() for waiter in waiters], 0).contiguous()
@@ -118,9 +118,9 @@ def tensordict_add_noreturn():
         elif args.task == 2:
             time.sleep(1)
             t0 = time.time()
-            # waiters = [rpc.rpc_async(f"worker{w}", get_tensordict, args=tuple()) for w in range(1, args.world_size)]
+            # waiters = [rpc.rpc_async(f"worker{w}", get_tensordict, args=()) for w in range(1, args.world_size)]
             waiters = [
-                rpc.remote(f"worker{w}", get_tensordict, args=tuple())
+                rpc.remote(f"worker{w}", get_tensordict, args=())
                 for w in range(1, args.world_size)
             ]
             # td = torch.stack([waiter.wait() for waiter in waiters], 0).clone()
@@ -129,7 +129,7 @@ def tensordict_add_noreturn():
             t0 = time.time()
             if args.memmap:
                 waiters = [
-                    rpc.remote(f"worker{w}", tensordict_add_noreturn, args=tuple())
+                    rpc.remote(f"worker{w}", tensordict_add_noreturn, args=())
                     for w in range(1, args.world_size)
                 ]
                 print("temp t: ", time.time() - t0)
@@ -139,7 +139,7 @@ def tensordict_add_noreturn():
                 print("temp t: ", time.time() - t0)
             else:
                 waiters = [
-                    rpc.remote(f"worker{w}", tensordict_add, args=tuple())
+                    rpc.remote(f"worker{w}", tensordict_add, args=())
                     for w in range(1, args.world_size)
                 ]
                 print("temp t: ", time.time() - t0)
@@ -153,14 +153,14 @@ def tensordict_add_noreturn():
             time.sleep(1)
             t0 = time.time()
             waiters = [
-                rpc.remote(f"worker{w}", get_tensordict, args=tuple())
+                rpc.remote(f"worker{w}", get_tensordict, args=())
                 for w in range(1, args.world_size)
             ]
             td = torch.stack([waiter.to_here() for waiter in waiters], 0)
             print("time to receive objs: ", time.time() - t0)
             t0 = time.time()
             waiters = [
-                rpc.remote(f"worker{w}", tensordict_add, args=tuple())
+                rpc.remote(f"worker{w}", tensordict_add, args=())
                 for w in range(1, args.world_size)
             ]
             print("temp t: ", time.time() - t0)

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,4 +1,5 @@
-#[tool.usort]
+[tool.usort]
+first_party_detection = false
 
 [build-system]
 requires = ["setuptools", "wheel", "torch"]

diff --git a/setup.cfg b/setup.cfg
@@ -17,6 +17,7 @@ per-file-ignores =
     test/opengl_rendering.py: F401
 
 exclude = venv
+extend-select = B901, C401, C408, C409
 
 [pydocstyle]
 ;select = D417 # Missing argument descriptions in the docstring