Added distribution-related nodes.

2025-03-18 01:11:46 -07:00
parent b7d2ea5346
commit 39421a4f8b
51 changed files with 2196 additions and 1 deletions
@@ -0,0 +1,52 @@
+from typing import Any, Dict
+import torch
+from torch.distributions import *
+import ast
+
+class PtdmPmf:
+    """
+    Computes the probability for the input distribution.
+
+    Args:
+            distribution (torch.distributions.distribution.Distribution): Distribution.
+            k (int): Number of successes.
+
+    category: PyTorch wrapper - Distribution
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying the required input types.
+        """
+        return {
+            "required": {
+                "distribution": ("PTDISTRIBUTION", {}),
+                "k": ("INT", {"default": 0, "min": -2**31, "max": 2**31})
+            }
+        }
+
+    RETURN_TYPES: tuple = ("TENSOR",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "Distribution"
+
+    def f(self, distribution: torch.distributions.Distribution, k: int) -> tuple:
+        """
+        Computes the probability for the input distribution.
+
+        Args:
+            distribution (torch.distributions.Distribution): Distribution.
+            k (int): Number of successes.
+
+        Returns:
+            tuple containing the probability
+        """
+        if isinstance(distribution, (Poisson, Categorical, Multinomial, Binomial, NegativeBinomial)):
+            tens = torch.tensor(k, dtype=torch.int64)
+        else:
+            tens = torch.tensor(k, dtype=torch.float32)
+
+        return (torch.exp(distribution.log_prob(tens)),)