Merge pull request #1335 from NiklasGustafsson/missing

Fixed issue #1334

Author: NiklasGustafsson

RELEASENOTES.md

@@ -10,10 +10,11 @@ When creating a tensor from a 1-D array, and passing in a shape, there is now an
 
 __API Changes__:
 
- #1326 Allow arrays used to create tensors to be larger than the tensor. Create tensors from a Memory instance<br/>
+ #1326 Allow arrays used to create tensors to be larger than the tensor. Create tensors from a Memory instance.<br/>
 
 __Bug Fixes__:
 
+#1334 MultivariateNormal.log_prob() exception in TorchSharp but works in pytorch.<br/>
 
 # NuGet Version 0.102.5
 

src/TorchSharp/Distributions/MultiVariateNormal.cs

@@ -218,7 +218,7 @@ private Tensor BatchMahalanobis(Tensor bL, Tensor bx)
                 var old_batch_dims = outer_batch_dims + bL_batch_dims;
                 var new_batch_dims = outer_batch_dims + 2 * bL_batch_dims;
 
-                var bx_new_shape = TakeAllBut(bx.shape, outer_batch_dims).ToList();
+                var bx_new_shape = bx.shape.Take(outer_batch_dims).ToList();
 
                 for (int i = 0; i < bL.ndim - 2; i++) {
                     var sL = bL.shape[i];

test/TorchSharpTest/TestDistributions.cs

@@ -1332,6 +1332,21 @@ public void TestMultivariateNormal()
             }
         }
 
+        [Fact]
+        public void TestMultivariateNormal_1334()
+        {
+            var actionMean = torch.tensor(new double[]{0.2025, -0.0714, 0.1417});
+            var covMat = torch.tensor(new double[,]
+            {
+                { 0.36, 0, 0 },
+                { 0, 0.36, 0 },
+                { 0, 0, 0.36 },
+            });
+            var dist = torch.distributions.MultivariateNormal(actionMean, covariance_matrix: covMat);
+            torch.Tensor action = dist.sample();
+            torch.Tensor actionLogProb = dist.log_prob(action);
+        }
+
         [Fact]
         public void TestWeibull()
         {