implemented _log_prob in normal.py

Author: PppBr

src/TensorFlowNET.Core/Operations/Distributions/distribution.py.cs

@@ -35,7 +35,7 @@ public class Distribution : _BaseDistribution
         /// <param name="name"> Python `str` prepended to names of ops created by this function.</param>
         /// <returns>log_prob: a `Tensor` of shape `sample_shape(x) + self.batch_shape` with values of type `self.dtype`.</returns>
 
-        /*
+        
         public Tensor log_prob(Tensor value, string name = "log_prob")
         {
             return _call_log_prob(value, name);
@@ -45,18 +45,39 @@ private Tensor _call_log_prob (Tensor value, string name)
         {
             with(ops.name_scope(name, "moments", new { value }), scope =>
             {
-                value = _convert_to_tensor(value, "value", _dtype);
+                try
+                {
+                    return _log_prob(value);
+                }
+                catch (Exception e1)
+                {
+                    try
+                    {
+                        return math_ops.log(_prob(value));
+                    } catch (Exception e2)
+                    {
+                        throw new NotImplementedException();
+                    }
+                }
             });
+            return null;
+        }
 
+        private Tensor _log_prob(Tensor value)
+        {
             throw new NotImplementedException();
-
         }
 
-        private Tensor _convert_to_tensor(Tensor value, string name = null, TF_DataType preferred_dtype)
+        private Tensor _prob(Tensor value)
         {
             throw new NotImplementedException();
         }
-        */
+
+        public TF_DataType dtype()
+        {
+            return this._dtype;
+        }
+        
 
         /// <summary>
         /// Constructs the `Distribution'     

src/TensorFlowNET.Core/Operations/Distributions/normal.py.cs

@@ -1,3 +1,4 @@
+using System;
 using System.Collections.Generic;
 using Tensorflow;
 
@@ -80,7 +81,7 @@ public Tensor _batch_shape()
 
         private Tensor _log_prob(Tensor x)
         {
-            return _log_unnormalized_prob(_z(x));
+            return _log_unnormalized_prob(_z(x)) -_log_normalization();
         }
 
         private Tensor _log_unnormalized_prob (Tensor x)
@@ -92,5 +93,11 @@ private Tensor _z (Tensor x)
         {
             return (x - this._loc) / this._scale;
         }
+
+        private Tensor _log_normalization()
+        {
+            Tensor t = new Tensor(Math.Log(2.0 * Math.PI));
+            return 0.5 * t + math_ops.log(scale());
+        }
     }
 }

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -48,13 +48,32 @@ public static Tensor squared_difference(Tensor x, Tensor y, string name = null)
             return _op.outputs[0];
         }
 
+        /// <summary>
+        /// Computes square of x element-wise.
+        /// </summary>
+        /// <param name="x"> A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`.</param>
+        /// <param name="name"> A name for the operation (optional).</param>
+        /// <returns> A `Tensor`. Has the same type as `x`.</returns>
         public static Tensor square(Tensor x, string name = null)
         {
             var _op = _op_def_lib._apply_op_helper("Square", name, args: new { x });
 
             return _op.outputs[0];
         }
 
+        /// <summary>
+        /// Computes natural logarithm of x element-wise.
+        /// </summary>
+        /// <param name="x"> A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `complex64`, `complex128`.</param>
+        /// <param name="name"> name: A name for the operation (optional).</param>
+        /// <returns> A `Tensor`. Has the same type as `x`.</returns>
+        public static Tensor log(Tensor x, string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("Log", name, args: new { x });
+
+            return _op.outputs[0];
+        }
+
         public static Tensor cast(Tensor x, TF_DataType DstT, bool Truncate= false, string name= "")
         {
             var _op = _op_def_lib._apply_op_helper("Cast", name, args: new { x, DstT, Truncate });

src/TensorFlowNET.Core/Operations/math_ops.py.cs

@@ -60,6 +60,11 @@ public static Tensor square(Tensor x, string name = null)
             return gen_math_ops.square(x, name);
         }
 
+        public static Tensor log(Tensor x, string name = null)
+        {
+            return gen_math_ops.log(x, name);
+        }
+
         /// <summary>
         /// Helper function for reduction ops.
         /// </summary>