[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/PyCQA/autoflake
-    rev: v2.2.1
+    rev: v2.3.3
     hooks:
       - id: autoflake
         name: Remove unused variables and imports
@@ -18,7 +18,7 @@ repos:
         files: \.py$
 
   - repo: https://github.com/PyCQA/isort
-    rev: 5.13.2
+    rev: 8.0.1
     hooks:
       - id: isort
         name: (isort) Sorting import statements
@@ -27,8 +27,8 @@ repos:
         types: [python]
         files: \.py$
 
-  - repo: https://github.com/psf/black
-    rev: 23.12.1
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 26.3.0
     hooks:
       - id: black
         name: (black) Format Python code
@@ -43,7 +43,7 @@ repos:
         types: [jupyter]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.1.11"
+    rev: "v0.15.5"
     hooks:
       - id: ruff
         args: ["--config", "pyproject.toml", "--fix", "./sheeprl"]

notebooks/dreamer_v3_imagination.ipynb

@@ -60,7 +60,6 @@
     "import torchvision\n",
     "from lightning.fabric import Fabric\n",
     "from omegaconf import OmegaConf\n",
-    "from PIL import Image\n",
     "\n",
     "from sheeprl.algos.dreamer_v3.agent import build_agent\n",
     "from sheeprl.data.buffers import SequentialReplayBuffer\n",

sheeprl/algos/dreamer_v3/agent.py

@@ -83,9 +83,7 @@ def __init__(
                 layer_args={"kernel_size": 4, "stride": 2, "padding": 1, "bias": layer_norm_cls == nn.Identity},
                 activation=activation,
                 norm_layer=[layer_norm_cls] * stages,
-                norm_args=[
-                    {**layer_norm_kw, "normalized_shape": (2**i) * channels_multiplier} for i in range(stages)
-                ],
+                norm_args=[{**layer_norm_kw, "normalized_shape": (2**i) * channels_multiplier} for i in range(stages)],
             ),
             nn.Flatten(-3, -1),
         )

sheeprl/algos/p2e_dv3/p2e_dv3_finetuning.py

@@ -129,7 +129,7 @@ def main(fabric: Fabric, cfg: Dict[str, Any], exploration_cfg: Dict[str, Any]):
         fabric.print("Decoder MLP keys:", cfg.algo.mlp_keys.decoder)
     obs_keys = cfg.algo.cnn_keys.encoder + cfg.algo.mlp_keys.encoder
 
-    (world_model, _, actor_task, critic_task, target_critic_task, actor_exploration, _, player) = build_agent(
+    world_model, _, actor_task, critic_task, target_critic_task, actor_exploration, _, player = build_agent(
         fabric,
         actions_dim,
         is_continuous,

sheeprl/algos/sac/loss.py

@@ -1,5 +1,4 @@
-"""Based on "Soft Actor-Critic Algorithms and Applications": https://arxiv.org/abs/1812.05905
-"""
+"""Based on "Soft Actor-Critic Algorithms and Applications": https://arxiv.org/abs/1812.05905"""
 
 from numbers import Number
 

sheeprl/data/buffers.py

@@ -135,12 +135,10 @@ def to_tensor(
         return buf
 
     @typing.overload
-    def add(self, data: "ReplayBuffer", validate_args: bool = False) -> None:
-        ...
+    def add(self, data: "ReplayBuffer", validate_args: bool = False) -> None: ...
 
     @typing.overload
-    def add(self, data: Dict[str, np.ndarray], validate_args: bool = False) -> None:
-        ...
+    def add(self, data: Dict[str, np.ndarray], validate_args: bool = False) -> None: ...
 
     def add(self, data: "ReplayBuffer" | Dict[str, np.ndarray], validate_args: bool = False) -> None:
         """Add data to the replay buffer. If the replay buffer is full, then the oldest data is overwritten.
@@ -617,12 +615,10 @@ def __len__(self) -> int:
         return self.buffer_size
 
     @typing.overload
-    def add(self, data: "ReplayBuffer", validate_args: bool = False) -> None:
-        ...
+    def add(self, data: "ReplayBuffer", validate_args: bool = False) -> None: ...
 
     @typing.overload
-    def add(self, data: Dict[str, np.ndarray], validate_args: bool = False) -> None:
-        ...
+    def add(self, data: Dict[str, np.ndarray], validate_args: bool = False) -> None: ...
 
     def add(
         self,
@@ -860,17 +856,17 @@ def __len__(self) -> int:
         return self._cum_lengths[-1] if len(self._buf) > 0 else 0
 
     @typing.overload
-    def add(self, data: "ReplayBuffer", env_idxes: Sequence[int] | None = None, validate_args: bool = False) -> None:
-        ...
+    def add(
+        self, data: "ReplayBuffer", env_idxes: Sequence[int] | None = None, validate_args: bool = False
+    ) -> None: ...
 
     @typing.overload
     def add(
         self,
         data: Dict[str, np.ndarray],
         env_idxes: Sequence[int] | None = None,
         validate_args: bool = False,
-    ) -> None:
-        ...
+    ) -> None: ...
 
     def add(
         self,

sheeprl/optim/rmsprop_tf.py

@@ -1,4 +1,4 @@
-""" RMSProp modified to behave like Tensorflow impl
+"""RMSProp modified to behave like Tensorflow impl
 
 Originally cut & paste from PyTorch RMSProp
 https://github.com/pytorch/pytorch/blob/063946d2b3f3f1e953a2a3b54e0b34f1393de295/torch/optim/rmsprop.py