fixed documentation

Author: tanish1729

pytensor/tensor/nlinalg.py

@@ -11,6 +11,7 @@
 from pytensor.gradient import DisconnectedType
 from pytensor.graph.basic import Apply
 from pytensor.graph.op import Op
+from pytensor.tensor import TensorLike
 from pytensor.tensor import basic as ptb
 from pytensor.tensor import math as ptm
 from pytensor.tensor.basic import as_tensor_variable, diagonal
@@ -266,7 +267,7 @@ def __str__(self):
         return "SLogDet"
 
 
-def slogdet(x: ptb.TensorVariable) -> tuple[ptb.TensorVariable, ptb.TensorVariable]:
+def slogdet(x: TensorLike) -> tuple[ptb.TensorVariable, ptb.TensorVariable]:
     """
     Compute the sign and (natural) logarithm of the determinant of an array.
 
@@ -279,12 +280,11 @@ def slogdet(x: ptb.TensorVariable) -> tuple[ptb.TensorVariable, ptb.TensorVariab
 
     Returns
     -------
-    A namedtuple with the following attributes:
+    A tuple with the following attributes:
 
     sign : (...) tensor_like
         A number representing the sign of the determinant. For a real matrix,
-        this is 1, 0, or -1. For a complex matrix, this is a complex number
-        with absolute value 1 (i.e., it is on the unit circle), or else 0.
+        this is 1, 0, or -1.
     logabsdet : (...) tensor_like
         The natural log of the absolute value of the determinant.
 

tests/tensor/rewriting/test_linalg.py

@@ -939,6 +939,7 @@ def test_slogdet_specialization():
     log_det_x, log_det_a = pt.log(det_x), np.log(det_a)
     sign_det_x, sign_det_a = pt.sign(det_x), np.sign(det_a)
     exp_det_x = pt.exp(det_x)
+
     # REWRITE TESTS
     # sign(det(x))
     f = function([x], [sign_det_x], mode="FAST_RUN")
@@ -952,6 +953,7 @@ def test_slogdet_specialization():
         atol=1e-3 if config.floatX == "float32" else 1e-8,
         rtol=1e-3 if config.floatX == "float32" else 1e-8,
     )
+
     # log(abs(det(x)))
     f = function([x], [log_abs_det_x], mode="FAST_RUN")
     nodes = f.maker.fgraph.apply_nodes
@@ -964,6 +966,7 @@ def test_slogdet_specialization():
         atol=1e-3 if config.floatX == "float32" else 1e-8,
         rtol=1e-3 if config.floatX == "float32" else 1e-8,
     )
+
     # log(det(x))
     f = function([x], [log_det_x], mode="FAST_RUN")
     nodes = f.maker.fgraph.apply_nodes
@@ -976,17 +979,20 @@ def test_slogdet_specialization():
         atol=1e-3 if config.floatX == "float32" else 1e-8,
         rtol=1e-3 if config.floatX == "float32" else 1e-8,
     )
-    # more than 1 valid function
+
+    # More than 1 valid function
     f = function([x], [sign_det_x, log_abs_det_x], mode="FAST_RUN")
     nodes = f.maker.fgraph.apply_nodes
     assert len([node for node in nodes if isinstance(node.op, SLogDet)]) == 1
     assert not any(isinstance(node.op, Det) for node in nodes)
-    # other functions (rewrite shouldnt be applied to these)
-    # only invalid functions
+
+    # Other functions (rewrite shouldnt be applied to these)
+    # Only invalid functions
     f = function([x], [exp_det_x], mode="FAST_RUN")
     nodes = f.maker.fgraph.apply_nodes
     assert not any(isinstance(node.op, SLogDet) for node in nodes)
-    # invalid + valid function
+
+    # Invalid + Valid function
     f = function([x], [exp_det_x, sign_det_x], mode="FAST_RUN")
     nodes = f.maker.fgraph.apply_nodes
     assert not any(isinstance(node.op, SLogDet) for node in nodes)