Rename sgn to sign (#228)

* Rename sgn to sign

Author: sudarsan2k5

doc/library/sparse/index.rst

@@ -196,7 +196,7 @@ List of Implemented Operations
     - ``ceil``
     - ``floor``
     - ``trunc``
-    - ``sgn``
+    - ``sign``
     - ``log1p``
     - ``expm1``
     - ``sqr``

doc/library/tensor/basic.rst

@@ -1462,7 +1462,7 @@ Mathematical
 
     Returns a variable representing the base e, 2 or 10 logarithm of a.
 
-.. function:: sgn(a)
+.. function:: sign(a)
 
     Returns a variable representing the sign of a.
 

pytensor/compile/profiling.py

@@ -1509,7 +1509,7 @@ def print_tips(self, file):
             aes.Second,
             aes.Identity,
             aes.Cast,
-            aes.Sgn,
+            aes.Sign,
             aes.Neg,
             aes.Reciprocal,
             aes.Sqr,

pytensor/scalar/basic.py

@@ -2566,7 +2566,7 @@ def L_op(self, inputs, outputs, gout):
                 return [x.zeros_like()]
 
         if x.type in float_types:
-            return (gz * sgn(x),)
+            return (gz * sign(x),)
         return (gz * x / _abs(x),)  # formula works for complex and real
 
     def c_code(self, node, name, inputs, outputs, sub):
@@ -2590,7 +2590,7 @@ def c_code(self, node, name, inputs, outputs, sub):
 abs = Abs(same_out)
 
 
-class Sgn(UnaryScalarOp):
+class Sign(UnaryScalarOp):
     nfunc_spec = ("sign", 1, 1)
 
     @staticmethod
@@ -2625,7 +2625,7 @@ def c_code(self, node, name, inputs, outputs, sub):
             )
         if type in int_types:
             return f"{z} = ({x} >= 0) ? ({x} == 0) ? 0 : 1 : -1;"
-        raise ComplexError("complex has no sgn")
+        raise ComplexError("complex has no sign")
 
     def c_code_cache_version(self):
         s = super().c_code_cache_version()
@@ -2635,7 +2635,7 @@ def c_code_cache_version(self):
             return s
 
 
-sgn = Sgn(name="sgn")
+sign = Sign(name="sign")
 
 
 class Ceil(UnaryScalarOp):

pytensor/sparse/basic.py

@@ -36,8 +36,8 @@
 from pytensor.tensor.math import (
     rad2deg,
     round_half_to_even,
-    sgn,
     sigmoid,
+    sign,
     sin,
     sinh,
     sqr,
@@ -3184,8 +3184,8 @@ def rint(x):
 rint.__name__ = "rint"
 
 
-@structured_monoid(sgn)  # type: ignore[no-redef]
-def sgn(x):
+@structured_monoid(sign)  # type: ignore[no-redef]
+def sign(x):
     """
     Elemwise signe of `x`.
 

pytensor/tensor/inplace.py

@@ -104,7 +104,7 @@ def log10_inplace(a):
 
 
 @scalar_elemwise
-def sgn_inplace(a):
+def sign_inplace(a):
     """sign of `a` (inplace on `a`)"""
 
 

pytensor/tensor/math.py

@@ -982,7 +982,7 @@ def isclose(a, b, rtol=1.0e-5, atol=1.0e-8, equal_nan=False):
     # deal with signed inf values. this will make an array inf_eq of 0's
     # except where inf values have the same sign.
     both_infs = bitwise_and(a_inf, b_inf)
-    inf_signs_eq = eq(a_inf * sgn(a), b_inf * sgn(b))
+    inf_signs_eq = eq(a_inf * sign(a), b_inf * sign(b))
     inf_eq = bitwise_and(both_infs, inf_signs_eq)
 
     # now create the potential result combining close and inf_eq
@@ -1092,9 +1092,19 @@ def log1p(a):
 
 
 @scalar_elemwise
+def sign(a):
+    """sign of a"""
+
+
 def sgn(a):
     """sign of a"""
 
+    warnings.warn(
+        "sgn is deprecated and will stop working in the future, use sign instead.",
+        FutureWarning,
+    )
+    return sign(a)
+
 
 @scalar_elemwise
 def ceil(a):
@@ -3038,6 +3048,7 @@ def matmul(x1: "ArrayLike", x2: "ArrayLike", dtype: Optional["DTypeLike"] = None
     "log10",
     "log1p",
     "sgn",
+    "sign",
     "ceil",
     "floor",
     "trunc",

pytensor/tensor/rewriting/math.py

@@ -72,8 +72,8 @@
 from pytensor.tensor.math import (
     prod,
     reciprocal,
-    sgn,
     sigmoid,
+    sign,
     softplus,
     sqr,
     sqrt,
@@ -2289,7 +2289,7 @@ def check_for_x_over_absX(numerators, denominators):
             else:
                 denominators.remove(den)
                 numerators.remove(den.owner.inputs[0])
-                numerators.append(sgn(den.owner.inputs[0]))
+                numerators.append(sign(den.owner.inputs[0]))
     return numerators, denominators
 
 

pytensor/tensor/subtensor.py

@@ -199,7 +199,7 @@ def get_canonical_form_slice(
     if the resulting set of numbers needs to be reversed or not.
 
     """
-    from pytensor.tensor import ge, lt, sgn, switch
+    from pytensor.tensor import ge, lt, sign, switch
 
     if not isinstance(theslice, slice):
         try:
@@ -317,7 +317,7 @@ def switch_neg_step(a, b):
             return switch(is_step_neg, a, b)
 
         abs_step = abs(step)
-        sgn_step = sgn(step)
+        sgn_step = sign(step)
 
     defstart = switch_neg_step(length - 1, 0)
     defstop = switch_neg_step(-1, length)

tests/sparse/test_basic.py

@@ -3111,7 +3111,7 @@ def structured_function(*args):
 )
 
 SgnTester = elemwise_checker(
-    sparse.sgn,
+    sparse.sign,
     np.sign,
     grad_test=False,
     test_dtypes=[

tests/tensor/rewriting/test_math.py

@@ -74,8 +74,8 @@
     prod,
     rad2deg,
     reciprocal,
-    sgn,
     sigmoid,
+    sign,
     sinh,
     softplus,
     sqr,
@@ -877,7 +877,7 @@ def test_abs_mul_div(self):
             assert np.isfinite(f(0))
 
         assert len(f.maker.fgraph.toposort()) == 2
-        assert f.maker.fgraph.toposort()[0].op == sgn
+        assert f.maker.fgraph.toposort()[0].op == sign
 
         f = function([x], [(4 * x) / abs(x / 2)], mode=mode)
         f(0.1)
@@ -886,7 +886,7 @@ def test_abs_mul_div(self):
             assert np.isfinite(f(0))
 
         assert len(f.maker.fgraph.toposort()) == 2
-        assert f.maker.fgraph.toposort()[0].op == sgn
+        assert f.maker.fgraph.toposort()[0].op == sign
 
     @pytest.mark.skip(
         reason="Current implementation of AlgebraicCanonizer does not "

tests/tensor/test_inplace.py

@@ -38,7 +38,7 @@
     reciprocal_inplace,
     round_half_away_from_zero_inplace,
     round_half_to_even_inplace,
-    sgn_inplace,
+    sign_inplace,
     sin_inplace,
     sinh_inplace,
     sqr_inplace,
@@ -177,7 +177,7 @@
 )
 
 TestSgnInplaceBroadcast = makeBroadcastTester(
-    op=sgn_inplace,
+    op=sign_inplace,
     expected=np.sign,
     good=_good_broadcast_unary_normal_no_complex,
     inplace=True,

tests/tensor/test_math.py

@@ -99,8 +99,8 @@
     reciprocal,
     round_half_away_from_zero,
     round_half_to_even,
-    sgn,
     sigmoid,
+    sign,
     sin,
     sinh,
     smallest,
@@ -386,7 +386,7 @@ def test_maximum_minimum_grad():
 )
 
 TestSgnBroadcast = makeBroadcastTester(
-    op=sgn,
+    op=sign,
     expected=np.sign,
     good=_good_broadcast_unary_normal_no_complex,
     grad=_grad_broadcast_unary_normal,