fix: Type annotation of prepare_batch()

.flake8

@@ -1,4 +1,4 @@
 [flake8]
 max-line-length = 100
 select = C,E,F,W,B,B950
-ignore = E203, E402, E501, W503
+ignore = E203, E402, E501, E704, W503, BLK100

src/deepali/data/prepare.py

@@ -2,7 +2,7 @@
 
 from collections import abc
 from dataclasses import is_dataclass
-from typing import Any, Mapping, NamedTuple, Optional, Sequence, Union, overload
+from typing import Any, Dict, Mapping, NamedTuple, Optional, Sequence, Union, overload
 
 import torch
 from torch import Tensor
@@ -17,36 +17,33 @@
 
 
 @overload
-def prepare_batch(batch: Sequence[Mapping[str, Any]]) -> Mapping[str, Any]:
-    ...
+def prepare_batch(batch: Mapping) -> Dict[str, Any]: ...
 
 
 @overload
-def prepare_batch(batch: Sequence[Dataclass]) -> Dataclass:
-    ...
+def prepare_batch(batch: Dataclass) -> Dataclass: ...
 
 
 @overload
-def prepare_batch(batch: Sequence[NamedTuple]) -> NamedTuple:
-    ...
+def prepare_batch(batch: NamedTuple) -> NamedTuple: ...
 
 
 def prepare_batch(
-    batch: Batch,
+    batch: Union[Mapping, Dataclass, NamedTuple],
     device: Optional[Union[Device, str]] = None,
     non_blocking: bool = False,
     memory_format=torch.preserve_format,
 ) -> Batch:
     r"""Move batch data to execution device."""
-    names = sample_field_names(batch)
+    names = sample_field_names(batch)  # type: ignore[arg-type]
     values = []
     for name in names:
-        value = sample_field_value(batch, name)
+        value = sample_field_value(batch, name)  # type: ignore[arg-type]
         value = prepare_item(
             value, device=device, non_blocking=non_blocking, memory_format=memory_format
         )
         values.append(value)
-    return replace_all_sample_field_values(batch, values)
+    return replace_all_sample_field_values(batch, values)  # type: ignore[arg-type]
 
 
 def prepare_item(
@@ -56,11 +53,11 @@ def prepare_item(
     memory_format=torch.preserve_format,
 ) -> Any:
     r"""Move batch item data to execution device."""
-    kwargs = dict(device=device, non_blocking=non_blocking, memory_format=memory_format)
+    kwargs: dict = dict(device=device, non_blocking=non_blocking, memory_format=memory_format)
     if isinstance(value, Tensor):
         value = value.to(**kwargs)
     elif isinstance(value, abc.Mapping) or is_dataclass(value) or is_namedtuple(value):
-        value = prepare_batch(value, **kwargs)
+        value = prepare_batch(value, **kwargs)  # type: ignore[arg-type]
     elif isinstance(value, Sequence) and not isinstance(value, str):
         value = [prepare_item(item, **kwargs) for item in value]
     return value

src/deepali/data/sample.py

@@ -16,12 +16,12 @@
 )
 
 
-def sample_field_names(sample: Sample) -> Tuple[str]:
+def sample_field_names(sample: Sample) -> Tuple[str, ...]:
     r"""Get names of fields in data sample."""
     if is_dataclass(sample):
-        return tuple((field.name for field in fields(sample)))
+        return tuple((field.name for field in fields(sample)))  # type: ignore[arg-type]
     if is_namedtuple(sample):
-        return sample._fields
+        return sample._fields  # type: ignore[arg-type]
     if not isinstance(sample, Mapping):
         raise TypeError("Dataset 'sample' must be dataclass, Mapping, or NamedTuple")
     return tuple(sample.keys())
@@ -45,7 +45,7 @@ def replace_all_sample_field_values(sample: Sample, values: Sequence[Any]) -> Sa
             setattr(result, name, value)
         return result
     if is_namedtuple(sample):
-        return sample._replace(**{name: value for name, value in zip(names, values)})
+        return sample._replace(**{name: value for name, value in zip(names, values)})  # type: ignore[arg-type]
     if isinstance(sample, OrderedDict):
         return OrderedDict([(name, value) for name, value in zip(names, values)])
     return {name: value for name, value in zip(names, values)}