Kernel batch size recurses through module lists.

[Fixes #1672]

Author: gpleiss

gpytorch/kernels/kernel.py

@@ -331,8 +331,8 @@ def covar_dist(
         return res
 
     def named_sub_kernels(self):
-        for name, module in self._modules.items():
-            if isinstance(module, Kernel):
+        for name, module in self.named_modules():
+            if module is not self and isinstance(module, Kernel):
                 yield name, module
 
     def num_outputs_per_input(self, x1, x2):

test/kernels/test_additive_and_product_kernels.py

@@ -56,6 +56,23 @@ def test_computes_product_of_radial_basis_function(self):
         res = kernel(a, b).evaluate()
         self.assertLess(torch.norm(res - actual), 2e-5)
 
+    def test_computes_product_of_radial_basis_function_batch(self):
+        a = torch.tensor([4, 2, 8], dtype=torch.float).view(3, 1)
+        b = torch.tensor([0, 2], dtype=torch.float).view(2, 1)
+        lengthscale = 2
+
+        kernel_1 = RBFKernel(batch_shape=torch.Size([4])).initialize(lengthscale=lengthscale)
+        kernel_2 = RBFKernel().initialize(lengthscale=lengthscale)
+        kernel = kernel_1 * kernel_2
+
+        actual = torch.tensor([[16, 4], [4, 0], [64, 36]], dtype=torch.float)
+        actual = actual.mul_(-0.5).div_(lengthscale ** 2).exp() ** 2
+        actual = actual.repeat(4, 1, 1)
+
+        kernel.eval()
+        res = kernel(a, b).evaluate()
+        self.assertLess(torch.norm(res - actual), 2e-5)
+
     def test_computes_sum_of_radial_basis_function(self):
         a = torch.tensor([4, 2, 8], dtype=torch.float).view(3, 1)
         b = torch.tensor([0, 2], dtype=torch.float).view(2, 1)