style(tensor_distribution): format __init__ method signatures for readability

Break long __init__ method signatures across multiple lines to improve
code readability and maintain consistent formatting standards across
the tensor distribution classes.

Author: Tim Joseph

src/tensorcontainer/tensor_distribution/dirichlet.py

@@ -14,7 +14,9 @@ class TensorDirichlet(TensorDistribution):
     # Annotated tensor parameters
     _concentration: Tensor
 
-    def __init__(self, concentration: Tensor, validate_args: bool | None = None) -> None:
+    def __init__(
+        self, concentration: Tensor, validate_args: bool | None = None
+    ) -> None:
         self._concentration = concentration
         super().__init__(concentration.shape, concentration.device, validate_args)
 

src/tensorcontainer/tensor_distribution/fisher_snedecor.py

@@ -10,7 +10,9 @@
 
 
 class TensorFisherSnedecor(TensorDistribution):
-    def __init__(self, df1: Tensor, df2: Tensor, *, validate_args: bool | None = None) -> None:
+    def __init__(
+        self, df1: Tensor, df2: Tensor, *, validate_args: bool | None = None
+    ) -> None:
         self._df1: Tensor
         self._df2: Tensor
         self._df1, self._df2 = broadcast_all(df1, df2)

src/tensorcontainer/tensor_distribution/half_cauchy.py

@@ -15,7 +15,9 @@ class TensorHalfCauchy(TensorDistribution):
     # Annotated tensor parameters
     _scale: Tensor
 
-    def __init__(self, scale: float | Tensor, validate_args: bool | None = None) -> None:
+    def __init__(
+        self, scale: float | Tensor, validate_args: bool | None = None
+    ) -> None:
         (self._scale,) = broadcast_all(scale)
 
         shape = self._scale.shape

src/tensorcontainer/tensor_distribution/half_normal.py

@@ -14,7 +14,9 @@ class TensorHalfNormal(TensorDistribution):
 
     _scale: Tensor
 
-    def __init__(self, scale: Tensor | float, validate_args: bool | None = None) -> None:
+    def __init__(
+        self, scale: Tensor | float, validate_args: bool | None = None
+    ) -> None:
         (self._scale,) = broadcast_all(scale)
 
         shape = self._scale.shape

src/tensorcontainer/tensor_distribution/logistic_normal.py

@@ -14,7 +14,9 @@ class TensorLogisticNormal(TensorDistribution):
     _loc: Tensor
     _scale: Tensor
 
-    def __init__(self, loc: Tensor, scale: Tensor, validate_args: bool | None = None) -> None:
+    def __init__(
+        self, loc: Tensor, scale: Tensor, validate_args: bool | None = None
+    ) -> None:
         loc, scale = broadcast_all(loc, scale)
 
         if loc.ndim == 0:

src/tensorcontainer/tensor_distribution/poisson.py

@@ -13,7 +13,9 @@
 class TensorPoisson(TensorDistribution):
     _rate: Tensor
 
-    def __init__(self, rate: Number | Tensor, validate_args: bool | None = None) -> None:
+    def __init__(
+        self, rate: Number | Tensor, validate_args: bool | None = None
+    ) -> None:
         (self._rate,) = broadcast_all(rate)
 
         shape = self._rate.shape