diff --git a/tensorflow_probability/python/experimental/distributions/BUILD b/tensorflow_probability/python/experimental/distributions/BUILD
index c6d3b45c87..4b98195ec0 100644
--- a/tensorflow_probability/python/experimental/distributions/BUILD
+++ b/tensorflow_probability/python/experimental/distributions/BUILD
@@ -205,12 +205,12 @@ multi_substrate_py_test(
     srcs = ["multitask_gaussian_process_test.py"],
     shard_count = 3,
     deps = [
+        ":multitask_gaussian_process",
+        ":multitask_gaussian_process_regression_model",
         # absl/testing:parameterized dep,
         # numpy dep,
         # tensorflow dep,
         "//tensorflow_probability/python/distributions:gaussian_process",
-        "//tensorflow_probability/python/experimental/distributions:multitask_gaussian_process",
-        "//tensorflow_probability/python/experimental/distributions:multitask_gaussian_process_regression_model",
         "//tensorflow_probability/python/experimental/psd_kernels:multitask_kernel",
         "//tensorflow_probability/python/internal:test_util",
         "//tensorflow_probability/python/math/psd_kernels:exponentiated_quadratic",
diff --git a/tensorflow_probability/python/experimental/distributions/multitask_gaussian_process.py b/tensorflow_probability/python/experimental/distributions/multitask_gaussian_process.py
index 9609f63444..6d54186388 100644
--- a/tensorflow_probability/python/experimental/distributions/multitask_gaussian_process.py
+++ b/tensorflow_probability/python/experimental/distributions/multitask_gaussian_process.py
@@ -249,11 +249,11 @@ def __init__(self,
     parameters = dict(locals())
     with tf.name_scope(name) as name:
       input_dtype = dtype_util.common_dtype(
-          dict(
-              kernel=kernel,
-              index_points=index_points),
+          dict(index_points=index_points),
           dtype_hint=nest_util.broadcast_structure(
-              kernel.feature_ndims, tf.float32))
+              kernel.feature_ndims, tf.float32
+          ),
+      )
 
       # If the input dtype is non-nested float, we infer a single dtype for the
       # input and the float parameters, which is also the dtype of the MTGP's