fix partial pre-commit

Signed-off-by: 0oshowero0 <o0shower0o@outlook.com>

Author: 0oshowero0

pyproject.toml

@@ -73,7 +73,9 @@ pretty            = true
 ignore_missing_imports = true
 explicit_package_bases = true
 follow_imports = "skip"
-ignore_errors = false
+
+# Blanket silence
+ignore_errors = true
 
 # -------------------------------
 # tool.pytest - pytest config
@@ -83,6 +85,12 @@ filterwarnings = [
     "ignore:.*PyTorch API of nested tensors.*prototype.*:UserWarning",
 ]
 
+[[tool.mypy.overrides]]
+module = [
+    "transfer_queue.*",
+]
+ignore_errors = false
+
 # -------------------------------
 # tool.setuptools - Additional config
 # -------------------------------

transfer_queue/controller.py

@@ -188,17 +188,17 @@ def release_indexes(self, partition_id: str, indexes_to_release: list[int]):
         if not partition_indexes:
             self.partition_to_indexes.pop(partition_id, None)
 
-    def get_indexes_for_partition(self, partition_id) -> set[int]:
+    def get_indexes_for_partition(self, partition_id) -> list[int]:
         """
         Get all global_indexes for the specified partition.
 
         Args:
             partition_id: Partition ID
 
         Returns:
-            set: Set of global_indexes for this partition
+            list: List of global_indexes for this partition
         """
-        return self.partition_to_indexes.get(partition_id, set()).copy()
+        return list(self.partition_to_indexes.get(partition_id, set()).copy())
 
 
 @dataclass
@@ -216,7 +216,7 @@ class DataPartitionStatus:
 
     # Production status tensor - dynamically expandable
     # Values: 0 = not produced, 1 = ready for consumption
-    production_status: Optional[Tensor] = torch.zeros(TQ_INIT_SAMPLE_NUM, TQ_INIT_FIELD_NUM, dtype=torch.int8)
+    production_status: Tensor = torch.zeros(TQ_INIT_SAMPLE_NUM, TQ_INIT_FIELD_NUM, dtype=torch.int8)
 
     # Consumption status per task - task_name -> consumption_tensor
     # Each tensor tracks which samples have been consumed by that task
@@ -260,7 +260,7 @@ def allocated_samples_num(self) -> int:
 
     # ==================== Dynamic Expansion Methods ====================
 
-    def ensure_samples_capacity(self, required_samples: int) -> bool:
+    def ensure_samples_capacity(self, required_samples: int):
         """
         Ensure the production status tensor has enough rows for the required samples.
         Dynamically expands if needed using unified minimum expansion size.
@@ -498,7 +498,9 @@ def get_consumption_status(self, task_name: str, mask: bool = False) -> tuple[Te
         return partition_global_index, consumption_status
 
     # ==================== Production Status Interface ====================
-    def get_production_status_for_fields(self, field_names: list[str], mask: bool = False) -> tuple[Tensor, Tensor]:
+    def get_production_status_for_fields(
+        self, field_names: list[str], mask: bool = False
+    ) -> tuple[Optional[Tensor], Optional[Tensor]]:
         """
         Check if all samples for specified fields are fully produced and ready.
 
@@ -512,12 +514,12 @@ def get_production_status_for_fields(self, field_names: list[str], mask: bool =
             - Production status tensor for the specified task. 1 for ready, 0 for not ready.
         """
         if self.production_status is None or field_names is None or len(field_names) == 0:
-            return False
+            return None, None
 
         # Check if all requested fields are registered
         for field_name in field_names:
             if field_name not in self.field_name_mapping:
-                return False
+                return None, None
 
         # Create column mask for requested fields
         col_mask = torch.zeros(self.allocated_fields_num, dtype=torch.bool)
@@ -837,15 +839,15 @@ def list_partitions(self) -> list[str]:
 
     # ==================== Partition Index Management API ====================
 
-    def get_partition_index_range(self, partition: DataPartitionStatus) -> set:
+    def get_partition_index_range(self, partition: DataPartitionStatus) -> list[int]:
         """
         Get all indexes for a specific partition.
 
         Args:
             partition: Partition identifier
 
         Returns:
-            Set of indexes allocated to the partition
+            List of indexes allocated to the partition
         """
         return self.index_manager.get_indexes_for_partition(partition)
 
@@ -980,6 +982,9 @@ def get_metadata(
         if mode == "fetch":
             # Find ready samples within current data partition and package into BatchMeta when reading
 
+            if batch_size is None:
+                raise ValueError("must provide batch_size in fetch mode")
+
             start_time = time.time()
             while True:
                 # ready_for_consume_indexes: samples where all required fields are produced

transfer_queue/metadata.py

@@ -265,7 +265,7 @@ def get_all_custom_meta(self) -> dict[int, dict[str, Any]]:
         """Get the entire custom meta dictionary"""
         return copy.deepcopy(self._custom_meta)
 
-    def update_custom_meta(self, new_custom_meta: dict[int, dict[str, Any]] = None):
+    def update_custom_meta(self, new_custom_meta: Optional[dict[int, dict[str, Any]]]):
         """Update custom meta with a new dictionary"""
         if new_custom_meta:
             self._custom_meta.update(new_custom_meta)

transfer_queue/storage/managers/base.py

@@ -60,7 +60,7 @@ class TransferQueueStorageManager(ABC):
     def __init__(self, config: dict[str, Any]):
         self.storage_manager_id = f"TQ_STORAGE_{uuid4().hex[:8]}"
         self.config = config
-        self.controller_info = config.get("controller_info", None)  # type: ZMQServerInfo
+        self.controller_info = config.get("controller_info")  # type: ZMQServerInfo
 
         self.data_status_update_socket = None
         self.controller_handshake_socket = None