Replaced use of isposinf and isneginf op with existing ops

Author: Dhruvanshu-Joshi

pytensor/scalar/basic.py

@@ -1533,56 +1533,6 @@ def c_code_cache_version(self):
 isinf = IsInf()
 
 
-class IsPosInf(FixedLogicalComparison):
-    nfunc_spec = ("isposinf", 1, 1)
-
-    def impl(self, x):
-        return np.isposinf(x)
-
-    def c_code(self, node, name, inputs, outputs, sub):
-        (x,) = inputs
-        (z,) = outputs
-        if node.inputs[0].type in complex_types:
-            raise NotImplementedError()
-        # Discrete type can never be posinf
-        if node.inputs[0].type in discrete_types:
-            return f"{z} = false;"
-
-        return f"{z} = isinf({x}) && !signbit({x});"
-
-    def c_code_cache_version(self):
-        scalarop_version = super().c_code_cache_version()
-        return (*scalarop_version, 4)
-
-
-isposinf = IsPosInf()
-
-
-class IsNegInf(FixedLogicalComparison):
-    nfunc_spec = ("isneginf", 1, 1)
-
-    def impl(self, x):
-        return np.isneginf(x)
-
-    def c_code(self, node, name, inputs, outputs, sub):
-        (x,) = inputs
-        (z,) = outputs
-        if node.inputs[0].type in complex_types:
-            raise NotImplementedError()
-        # Discrete type can never be neginf
-        if node.inputs[0].type in discrete_types:
-            return f"{z} = false;"
-
-        return f"{z} = isinf({x}) && signbit({x});"
-
-    def c_code_cache_version(self):
-        scalarop_version = super().c_code_cache_version()
-        return (*scalarop_version, 4)
-
-
-isneginf = IsNegInf()
-
-
 class InRange(LogicalComparison):
     nin = 3
 

pytensor/tensor/math.py

@@ -881,46 +881,6 @@ def isinf(a):
     return isinf_(a)
 
 
-@scalar_elemwise
-def isposinf(a):
-    """isposinf(a)"""
-
-
-# Rename isposnan to isposnan_ to allow to bypass it when not needed.
-# glibc 2.23 don't allow isposnan on int, so we remove it from the graph.
-isposinf_ = isposinf
-
-
-def isposinf(a):
-    """isposinf(a)"""
-    a = as_tensor_variable(a)
-    if a.dtype in discrete_dtypes:
-        return alloc(
-            np.asarray(False, dtype="bool"), *[a.shape[i] for i in range(a.ndim)]
-        )
-    return isposinf_(a)
-
-
-@scalar_elemwise
-def isneginf(a):
-    """isneginf(a)"""
-
-
-# Rename isnegnan to isnegnan_ to allow to bypass it when not needed.
-# glibc 2.23 don't allow isnegnan on int, so we remove it from the graph.
-isneginf_ = isneginf
-
-
-def isneginf(a):
-    """isneginf(a)"""
-    a = as_tensor_variable(a)
-    if a.dtype in discrete_dtypes:
-        return alloc(
-            np.asarray(False, dtype="bool"), *[a.shape[i] for i in range(a.ndim)]
-        )
-    return isneginf_(a)
-
-
 def allclose(a, b, rtol=1.0e-5, atol=1.0e-8, equal_nan=False):
     """
     Implement Numpy's ``allclose`` on tensors.
@@ -3117,8 +3077,8 @@ def nan_to_num(x, nan=0.0, posinf=None, neginf=None):
     """
     # Replace NaN's with nan keyword
     is_nan = isnan(x)
-    is_pos_inf = isposinf(x)
-    is_neg_inf = isneginf(x)
+    is_pos_inf = eq(x, np.inf)
+    is_neg_inf = eq(x, -np.inf)
 
     if not any(is_nan) and not any(is_pos_inf) and not any(is_neg_inf):
         return