Misc. refactoring in aesara.tensor.basic

aesara/tensor/basic.py

@@ -6,7 +6,6 @@ manipulation of tensors.
 """
 
 import builtins
-import logging
 import warnings
 from collections.abc import Sequence
 from functools import partial
@@ -65,11 +64,6 @@ from aesara.tensor.type import (
 from aesara.tensor.var import TensorConstant, TensorVariable, get_unique_value
 
 
-_logger = logging.getLogger("aesara.tensor.basic")
-
-__docformat__ = "restructuredtext en"
-
-
 def __oplist_tag(thing, tag):
     tags = getattr(thing, "__oplist_tags", [])
     tags.append(tag)
@@ -900,24 +894,14 @@ def cast(x, dtype: Union[str, np.dtype]) -> TensorVariable:
     return _cast_mapping[dtype_name](x)
 
 
-##########################
-# Condition
-##########################
-
-
 @scalar_elemwise
 def switch(cond, ift, iff):
     """if cond then ift else iff"""
 
 
 where = switch
-##########################
-# Misc
-##########################
 
 
-# fill, _fill_inplace = _elemwise(aes.second, 'fill',
-# """fill WRITEME (elemwise)""")
 @scalar_elemwise
 def second(a, b):
     """Create a matrix by filling the shape of a with b"""
@@ -1899,11 +1883,6 @@ class Default(Op):
 default = Default()
 
 
-##########################
-# View Operations
-##########################
-
-
 def extract_constant(x, elemwise=True, only_process_constants=False):
     """
     This function is basically a call to tensor.get_scalar_constant_value.
@@ -2783,16 +2762,11 @@ def stack(*tensors, **kwargs):
     # And DebugMode can't detect error in this code as it is not in an
     # optimization.
     # See ticket #660
-    if np.all(
-        [  # in case there is direct int in tensors.
-            isinstance(t, (np.number, float, int, builtins.complex))
-            or (
-                isinstance(t, Variable)
-                and isinstance(t.type, TensorType)
-                and t.ndim == 0
-            )
-            for t in tensors
-        ]
+    if all(
+        # In case there are explicit ints in tensors
+        isinstance(t, (np.number, float, int, builtins.complex))
+        or (isinstance(t, Variable) and isinstance(t.type, TensorType) and t.ndim == 0)
+        for t in tensors
     ):
         # in case there is direct int
         tensors = list(map(as_tensor_variable, tensors))
@@ -4036,7 +4010,7 @@ def swapaxes(y, axis1, axis2):
     return y.dimshuffle(li)
 
 
-def choose(a, choices, out=None, mode="raise"):
+def choose(a, choices, mode="raise"):
     """
     Construct an array from an index array and a set of arrays to choose from.
 
@@ -4080,9 +4054,6 @@ def choose(a, choices, out=None, mode="raise"):
         the same shape. If choices is itself an array (not recommended),
         then its outermost dimension (i.e., the one corresponding to
         choices.shape[0]) is taken as defining the ``sequence``.
-    out : array, optional
-        If provided, the result will be inserted into this array.
-        It should be of the appropriate shape and dtype.
     mode : {``raise`` (default), ``wrap``, ``clip``}, optional
         Specifies how indices outside [0, n-1] will be treated:
         ``raise`` : an exception is raised
@@ -4100,8 +4071,6 @@ def choose(a, choices, out=None, mode="raise"):
         If a and each choice array are not all broadcastable to the same shape.
 
     """
-    # This is done to keep the same function signature then NumPy.
-    assert out is None
     return Choose(mode)(a, choices)
 
 
@@ -4365,9 +4334,9 @@ def expand_dims(
 
 def _make_along_axis_idx(arr_shape, indices, axis):
     """Take from `numpy.lib.shape_base`."""
-    # compute dimensions to iterate over
     if str(indices.dtype) not in int_dtypes:
         raise IndexError("`indices` must be an integer array")
+
     shape_ones = (1,) * indices.ndim
     dest_dims = list(range(axis)) + [None] + list(range(axis + 1, indices.ndim))
 

aesara/tensor/var.py

@@ -788,13 +788,13 @@ class _tensor_py_operators:
         """Fill inputted tensor with the assigned value."""
         return at.basic.fill(self, value)
 
-    def choose(self, choices, out=None, mode="raise"):
+    def choose(self, choices, mode="raise"):
         """
         Construct an array from an index array and a set of arrays to choose
         from.
 
         """
-        return at.basic.choose(self, choices, out=None, mode="raise")
+        return at.basic.choose(self, choices, mode="raise")
 
     def squeeze(self):
         """