Remove unused return value from helper functions

pymc-devs · Jan 8, 2022 · 2fe5e93 · 2fe5e93
1 parent 664a447
commit 2fe5e93
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Showing 2 changed files with 12 additions and 16 deletions.
diff --git a/pymc/distributions/distribution.py b/pymc/distributions/distribution.py
@@ -232,9 +232,9 @@ def __new__(
         # `dims` are only available with this API, because `.dist()` can be used
         # without a modelcontext and dims are not tracked at the Aesara level.
         if dims is not None:
-            ndim_resize, resize_shape, dims = resize_from_dims(dims, ndim_actual, model)
+            resize_shape, dims = resize_from_dims(dims, ndim_actual, model)
         elif observed is not None:
-            ndim_resize, resize_shape, observed = resize_from_observed(observed, ndim_actual)
+            resize_shape, observed = resize_from_observed(observed, ndim_actual)
 
         if resize_shape:
             # A batch size was specified through `dims`, or implied by `observed`.
@@ -482,9 +482,9 @@ def __new__(
         # # `dims` are only available with this API, because `.dist()` can be used
         # # without a modelcontext and dims are not tracked at the Aesara level.
         if dims is not None:
-            ndim_resize, resize_shape, dims = resize_from_dims(dims, ndim_actual, model)
+            resize_shape, dims = resize_from_dims(dims, ndim_actual, model)
         elif observed is not None:
-            ndim_resize, resize_shape, observed = resize_from_observed(observed, ndim_actual)
+            resize_shape, observed = resize_from_observed(observed, ndim_actual)
 
         if resize_shape:
             # A batch size was specified through `dims`, or implied by `observed`.

diff --git a/pymc/distributions/shape_utils.py b/pymc/distributions/shape_utils.py
@@ -487,9 +487,7 @@ def convert_size(size: Size) -> Optional[StrongSize]:
     return size
 
 
-def resize_from_dims(
-    dims: WeakDims, ndim_implied: int, model
-) -> Tuple[int, StrongSize, StrongDims]:
+def resize_from_dims(dims: WeakDims, ndim_implied: int, model) -> Tuple[StrongSize, StrongDims]:
     """Determines a potential resize shape from a `dims` tuple.
 
     Parameters
@@ -503,10 +501,10 @@ def resize_from_dims(
 
     Returns
     -------
-    ndim_resize : int
-        Number of dimensions that should be added through resizing.
     resize_shape : array-like
-        The shape of the new dimensions.
+        Shape of new dimensions that should be prepended.
+    dims : tuple of (str or None)
+        Names or None for all dimensions after resizing.
     """
     if Ellipsis in dims:
         # Auto-complete the dims tuple to the full length.
@@ -525,12 +523,12 @@ def resize_from_dims(
 
     # The numeric/symbolic resize tuple can be created using model.RV_dim_lengths
     resize_shape = tuple(model.dim_lengths[dname] for dname in dims[:ndim_resize])
-    return ndim_resize, resize_shape, dims
+    return resize_shape, dims
 
 
 def resize_from_observed(
     observed, ndim_implied: int
-) -> Tuple[int, StrongSize, Union[np.ndarray, Variable]]:
+) -> Tuple[StrongSize, Union[np.ndarray, Variable]]:
     """Determines a potential resize shape from observations.
 
     Parameters
@@ -542,18 +540,16 @@ def resize_from_observed(
 
     Returns
     -------
-    ndim_resize : int
-        Number of dimensions that should be added through resizing.
     resize_shape : array-like
-        The shape of the new dimensions.
+        Shape of new dimensions that should be prepended.
     observed : scalar, array-like
         Observations as numpy array or `Variable`.
     """
     if not hasattr(observed, "shape"):
         observed = pandas_to_array(observed)
     ndim_resize = observed.ndim - ndim_implied
     resize_shape = tuple(observed.shape[d] for d in range(ndim_resize))
-    return ndim_resize, resize_shape, observed
+    return resize_shape, observed
 
 
 def find_size(shape=None, size=None, ndim_supp=None):