[Formatting] Update pre-commit (#3108)

vmoens · web-flow · commit 009f4ce1692b · 2025-08-01T15:25:12.000+01:00
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.0.1
+    rev: v5.0.0
     hooks:
       - id: check-docstring-first
       - id: check-toml
@@ -11,7 +11,7 @@ repos:
       - id: end-of-file-fixer
 
   - repo: https://github.com/omnilib/ufmt
-    rev: v2.0.0b2
+    rev: v2.8.0
     hooks:
       - id: ufmt
         additional_dependencies:
@@ -20,7 +20,7 @@ repos:
           - libcst == 0.4.7
 
   - repo: https://github.com/pycqa/flake8
-    rev: 6.0.0
+    rev: 7.3.0
     hooks:
       - id: flake8
         args: [--config=setup.cfg]
@@ -31,13 +31,13 @@ repos:
           - flake8-print==5.0.0
 
   - repo: https://github.com/PyCQA/pydocstyle
-    rev: 6.1.1
+    rev: 6.3.0
     hooks:
       - id: pydocstyle
         files: ^torchrl/
 
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.9.0
+    rev: v3.20.0
     hooks:
       - id: pyupgrade
         args: [--py38-plus]
diff --git a/benchmarks/conftest.py b/benchmarks/conftest.py
@@ -10,7 +10,7 @@
 import pytest
 from torchrl._utils import logger as torchrl_logger
 
-CALL_TIMES = defaultdict(lambda: 0.0)
+CALL_TIMES = defaultdict(float)
 
 
 def pytest_sessionfinish(maxprint=50):
diff --git a/test/_utils_internal.py b/test/_utils_internal.py
@@ -261,7 +261,7 @@ def __init__(self, old_emit):
             self.old_emit = old_emit
 
         def __call__(self, record):
-            nonlocal records
+            nonlocal records  # noqa: F824
             self.old_emit(record)
             if record_name in record.name:
                 records.append(record)
diff --git a/test/conftest.py b/test/conftest.py
@@ -14,7 +14,7 @@
 import pytest
 import torch
 
-CALL_TIMES = defaultdict(lambda: 0.0)
+CALL_TIMES = defaultdict(float)
 IS_OSX = sys.platform == "darwin"
 
 
diff --git a/test/llm/test_wrapper.py b/test/llm/test_wrapper.py
@@ -2386,7 +2386,7 @@ def test_batching_continuous_throughput(
             assert len(processing_events) > 0, "No processing occurred"
 
             # Check that processing happened across multiple threads (indicating concurrent processing)
-            thread_ids = {event["thread_id"] for event in processing_events}  # noqa
+            thread_ids = set(event["thread_id"] for event in processing_events)
             assert (
                 len(thread_ids) > 1
             ), f"All processing happened in single thread: {thread_ids}"
diff --git a/test/test_env.py b/test/test_env.py
@@ -107,7 +107,7 @@
     _atari_found = True
 except FileNotFoundError:
     _atari_found = False
-    atari_confs = defaultdict(lambda: "")
+    atari_confs = defaultdict(str)
 
 if os.getenv("PYTORCH_TEST_FBCODE"):
     from pytorch.rl.test._utils_internal import (
diff --git a/test/test_libs.py b/test/test_libs.py
@@ -3410,7 +3410,7 @@ def test_d4rl_iteration(self, task, split_trajs):
 
 def _minari_init() -> tuple[bool, Exception | None]:
     """Initialize Minari datasets list. Returns True if already initialized."""
-    global _MINARI_DATASETS
+    global _MINARI_DATASETS  # noqa: F824
     if _MINARI_DATASETS and not all(
         isinstance(x, str) and x.isdigit() for x in _MINARI_DATASETS
     ):
diff --git a/torchrl/_utils.py b/torchrl/_utils.py
@@ -1176,7 +1176,7 @@ def auto_unwrap_transformed_env(allow_none=False):
         bool or None: The current setting for automatically unwrapping TransformedEnv
             instances.
     """
-    global _AUTO_UNWRAP
+    global _AUTO_UNWRAP  # noqa: F824
     if _AUTO_UNWRAP is None and allow_none:
         return None
     elif _AUTO_UNWRAP is None:
diff --git a/torchrl/data/llm/history.py b/torchrl/data/llm/history.py
@@ -246,7 +246,7 @@ def add_chat_template(
           `name_or_path` attribute.
         - Templates are stored globally and persist for the duration of the Python session.
     """
-    global _CHAT_TEMPLATES, _CUSTOM_INVERSE_PARSERS, _CUSTOM_MODEL_FAMILY_KEYWORDS
+    global _CHAT_TEMPLATES, _CUSTOM_INVERSE_PARSERS, _CUSTOM_MODEL_FAMILY_KEYWORDS  # noqa: F824
 
     # Validate template contains generation blocks
     if "{% generation %}" not in template:
diff --git a/torchrl/data/tensor_specs.py b/torchrl/data/tensor_specs.py
@@ -523,7 +523,7 @@ def __eq__(self, other):
                 return True
             return False
         return (
-            type(self) == type(other)
+            type(self) is type(other)
             and self.low.dtype == other.low.dtype
             and self.high.dtype == other.high.dtype
             and self.device == other.device
@@ -627,7 +627,7 @@ class TensorSpec(metaclass=abc.ABCMeta):
 
     shape: torch.Size
     space: None | Box
-    device: torch.device | None = None
+    device: torch.device | None = None  # noqa # type: ignore
     dtype: torch.dtype = torch.get_default_dtype()
     domain: str = ""
     _encode_memo_dict: dict[Any, Callable[[Any], Any]] = field(
@@ -679,7 +679,7 @@ def decorator(func):
         return decorator
 
     @property
-    def device(self) -> torch.device:
+    def device(self) -> torch.device:  # noqa # type: ignore
         """The device of the spec.
 
         Only :class:`Composite` specs can have a ``None`` device. All leaves must have a non-null device.
@@ -2163,7 +2163,7 @@ def __eq__(self, other):
             and (self.mask == other.mask).all()
         )
         return (
-            type(self) == type(other)
+            type(self) is type(other)
             and self.shape == other.shape
             and self.space == other.space
             and self.device == other.device
@@ -2444,7 +2444,7 @@ def cardinality(self) -> int:
 
     def __eq__(self, other):
         return (
-            type(other) == type(self)
+            type(other) is type(self)
             and self.device == other.device
             and self.shape == other.shape
             and self.space == other.space
@@ -3443,7 +3443,7 @@ def __eq__(self, other):
             and (self.mask == other.mask).all()
         )
         return (
-            type(self) == type(other)
+            type(self) is type(other)
             and self.shape == other.shape
             and self.space == other.space
             and self.device == other.device
@@ -4042,7 +4042,7 @@ def __eq__(self, other):
             and (self.mask == other.mask).all()
         )
         return (
-            type(self) == type(other)
+            type(self) is type(other)
             and self.shape == other.shape
             and self.space == other.space
             and self.device == other.device
@@ -4731,7 +4731,7 @@ def __eq__(self, other):
             and (self.mask == other.mask).all()
         )
         return (
-            type(self) == type(other)
+            type(self) is type(other)
             and self.shape == other.shape
             and self.space == other.space
             and self.device == other.device
@@ -5585,7 +5585,7 @@ def is_in(self, val: dict | TensorDictBase) -> bool:
         #     return False
         # if val.shape[-self.ndim:] != self.shape:
         #     return False
-        if self.data_cls is not None and type(val) != self.data_cls:
+        if self.data_cls is not None and type(val) is not self.data_cls:
             return False
         for key, item in self._specs.items():
             if item is None or (isinstance(item, Composite) and item.is_empty()):
@@ -5902,7 +5902,7 @@ def zero(self, shape: torch.Size = None) -> TensorDictBase:
 
     def __eq__(self, other: object) -> bool:
         return (
-            type(self) == type(other)
+            type(self) is type(other)
             and self.shape == other.shape
             and self._device == other._device
             and set(self._specs.keys()) == set(other._specs.keys())
diff --git a/torchrl/envs/libs/gym.py b/torchrl/envs/libs/gym.py
@@ -130,7 +130,7 @@ def _call(self):
         """Sets the backend as default."""
         global DEFAULT_GYM
         DEFAULT_GYM = self.backend
-        found_setters = collections.defaultdict(lambda: False)
+        found_setters = collections.defaultdict(bool)
         for setter in copy(implement_for._setters):
             check_module = (
                 callable(setter.module_name)
diff --git a/torchrl/envs/transforms/transforms.py b/torchrl/envs/transforms/transforms.py
@@ -1666,7 +1666,7 @@ def append(
                     f"but received an object of type {type(transform)} instead."
                 )
         transform.eval()
-        if type(self) == type(transform) == Compose:
+        if type(self) is type(transform) is Compose:
             for t in transform:
                 self.append(t)
         else:
@@ -7673,7 +7673,7 @@ def transform_observation_spec(self, observation_spec: Composite) -> Composite:
             # find a matching done key (there might be more than one)
             for done_key in self.done_keys:
                 # check root
-                if type(done_key) != type(step_count_key):
+                if type(done_key) is not type(step_count_key):
                     continue
                 if isinstance(done_key, tuple):
                     if done_key[:-1] == step_count_key[:-1]:
@@ -7704,7 +7704,7 @@ def transform_output_spec(self, output_spec: Composite) -> Composite:
                 # find a matching done key (there might be more than one)
                 for done_key in self.done_keys:
                     # check root
-                    if type(done_key) != type(truncated_key):
+                    if type(done_key) is not type(truncated_key):
                         continue
                     if isinstance(done_key, tuple):
                         if done_key[:-1] == truncated_key[:-1]:
@@ -7727,7 +7727,7 @@ def transform_output_spec(self, output_spec: Composite) -> Composite:
                     # find a matching done key (there might be more than one)
                     for done_key in self.done_keys:
                         # check root
-                        if type(done_key) != type(done_key):
+                        if type(done_key) is not type(done_key):
                             continue
                         if isinstance(done_key, tuple):
                             if done_key[:-1] == done_key[:-1]:
@@ -7763,7 +7763,7 @@ def transform_input_spec(self, input_spec: Composite) -> Composite:
             # find a matching done key (there might be more than one)
             for done_key in self.done_keys:
                 # check root
-                if type(done_key) != type(step_count_key):
+                if type(done_key) is not type(step_count_key):
                     continue
                 if isinstance(done_key, tuple):
                     if done_key[:-1] == step_count_key[:-1]:
@@ -8412,7 +8412,7 @@ def transform_observation_spec(self, observation_spec: TensorSpec) -> TensorSpec
         for init_key in self.init_keys:
             for done_key in self.parent.done_keys:
                 # check root
-                if type(done_key) != type(init_key):
+                if type(done_key) is not type(init_key):
                     continue
                 if isinstance(done_key, tuple):
                     if done_key[:-1] == init_key[:-1]:
@@ -10667,7 +10667,7 @@ def transform_observation_spec(self, observation_spec: Composite) -> Composite:
         # find a matching done key (there might be more than one)
         for done_key in self.parent.done_keys:
             # check root
-            if type(done_key) != type(traj_count_key):
+            if type(done_key) is not type(traj_count_key):
                 continue
             if isinstance(done_key, tuple):
                 if done_key[:-1] == traj_count_key[:-1]:
diff --git a/torchrl/objectives/common.py b/torchrl/objectives/common.py
@@ -304,7 +304,7 @@ def convert_to_functional(
                   provided, the value of the parameters will be resampled uniformly
                   between the minimum and maximum value of the parameter content.
 
-             create_target_params (bool, optional): if ``True``, a detached
+            create_target_params (bool, optional): if ``True``, a detached
                 copy of the parameter will be available to feed a target network
                 under the name ``loss_module.<module_name>_target_params``.
                 If ``False`` (default), this attribute will still be available
diff --git a/torchrl/objectives/gail.py b/torchrl/objectives/gail.py
@@ -121,7 +121,7 @@ def in_keys(self, values):
         self._in_keys = values
 
     @property
-    def out_keys(self):
+    def out_keys(self):  # noqa: F811
         if self._out_keys is None:
             keys = ["loss"]
             if self.use_grad_penalty:
diff --git a/torchrl/record/loggers/csv.py b/torchrl/record/loggers/csv.py
@@ -21,9 +21,9 @@ class CSVExperiment:
     """A CSV logger experiment class."""
 
     def __init__(self, log_dir: str, *, video_format="pt", video_fps: int = 30):
-        self.scalars = defaultdict(lambda: [])
-        self.videos_counter = defaultdict(lambda: 0)
-        self.text_counter = defaultdict(lambda: 0)
+        self.scalars = defaultdict(list)
+        self.videos_counter = defaultdict(int)
+        self.text_counter = defaultdict(int)
         self.log_dir = log_dir
         self.video_format = video_format
         self.video_fps = video_fps
diff --git a/torchrl/trainers/trainers.py b/torchrl/trainers/trainers.py
@@ -196,7 +196,7 @@ def __init__(
         self.save_trainer_interval = save_trainer_interval
         self.save_trainer_file = save_trainer_file
 
-        self._log_dict = defaultdict(lambda: [])
+        self._log_dict = defaultdict(list)
 
         self._batch_process_ops = []
         self._post_steps_ops = []
diff --git a/tutorials/sphinx-tutorials/export.py b/tutorials/sphinx-tutorials/export.py
@@ -436,7 +436,7 @@
 # more lightweight, the ONNX version should be faster than the TorchRL one.
 
 
-def onnx_policy(screen_obs: np.ndarray) -> int:
+def onnx_policy(screen_obs: np.ndarray) -> int:  # noqa: F811
     onnxruntime_input = {ort_session.get_inputs()[0].name: screen_obs}
     onnxruntime_outputs = ort_session.run(None, onnxruntime_input)
     action = int(onnxruntime_outputs[0])
