Added distribution method nodes that take 2d tensor as input

modules/pytorch_wrapper/ptdm_cdf.py

@@ -12,7 +12,7 @@ class PtdmCdf:
 
     Args:
             distribution (torch.distributions.distribution.Distribution): Distribution.
-            v (float): Value
+            x (float): Value
 
     category: PyTorch wrapper - Distribution
     """
@@ -28,7 +28,7 @@ class PtdmCdf:
         return {
             "required": {
                 "distribution": ("PTDISTRIBUTION", {}),
-                "v": ("STRING", {"default": ""})
+                "x": ("STRING", {"default": ""})
             }
         }
 
@@ -36,18 +36,18 @@ class PtdmCdf:
     FUNCTION: str = "f"
     CATEGORY: str = "Distribution"
 
-    def f(self, distribution: torch.distributions.Distribution, v: str) -> tuple:
+    def f(self, distribution: torch.distributions.Distribution, x: str) -> tuple:
         """
         Computes the cumulative distribution function for the input distribution.
 
         Args:
             distribution (torch.distributions.Distribution): Distribution.
-            v (str): Value
+            x (str): Value
 
         Returns:
             tuple containing the probability
         """
-        v2 = ast.literal_eval(v)
+        v2 = ast.literal_eval(x)
         if isinstance(v2, int) is False and isinstance(v2, float) is False :
             if isinstance(distribution, Dirichlet) is False:
                 raise ValueError("You need to specify a float or an int.")