diff --git a/tensorflow/python/keras/losses.py b/tensorflow/python/keras/losses.py
index 8afe2fadce5..1bd9f729c5c 100644
--- a/tensorflow/python/keras/losses.py
+++ b/tensorflow/python/keras/losses.py
@@ -115,8 +115,28 @@ class Loss(object):
     NotImplementedError('Must be implemented in subclasses.')
 
 
+@tf_export('losses.MeanSquaredError', 'keras.losses.MeanSquaredError')
 class MeanSquaredError(Loss):
-  """Computes the mean of squares of errors between labels and predictions."""
+  """Computes the mean of squares of errors between labels and predictions.
+
+  For example, if `y_true` is [0., 0., 1., 1.] and `y_pred` is [1., 1., 1., 0.]
+  then the mean squared error value is 3/4 (0.75).
+
+  Usage:
+
+  ```python
+  mse = tf.losses.MeanSquaredError()
+  loss = mse([0., 0., 1., 1.], [1., 1., 1., 0.])
+  print('Loss: ', loss.numpy())  # Loss: 0.75
+  ```
+
+  Usage with tf.keras API:
+
+  ```python
+  model = keras.models.Model(inputs, outputs)
+  model.compile('sgd', loss=tf.losses.MeanSquaredError())
+  ```
+  """
 
   def call(self, y_true, y_pred):
     """Invokes the `MeanSquaredError` instance.
diff --git a/tensorflow/python/ops/losses/losses_impl.py b/tensorflow/python/ops/losses/losses_impl.py
index 7c52b28b391..1b470937d4a 100644
--- a/tensorflow/python/ops/losses/losses_impl.py
+++ b/tensorflow/python/ops/losses/losses_impl.py
@@ -133,7 +133,7 @@ def _num_elements(losses):
     return math_ops.cast(array_ops.size(losses, name=scope), dtype=losses.dtype)
 
 
-@tf_export("losses.compute_weighted_loss")
+@tf_export(v1=["losses.compute_weighted_loss"])
 def compute_weighted_loss(
     losses, weights=1.0, scope=None, loss_collection=ops.GraphKeys.LOSSES,
     reduction=Reduction.SUM_BY_NONZERO_WEIGHTS):
@@ -203,7 +203,7 @@ def compute_weighted_loss(
       return loss
 
 
-@tf_export("losses.absolute_difference")
+@tf_export(v1=["losses.absolute_difference"])
 def absolute_difference(
     labels, predictions, weights=1.0, scope=None,
     loss_collection=ops.GraphKeys.LOSSES,
@@ -256,7 +256,7 @@ def absolute_difference(
         losses, weights, scope, loss_collection, reduction=reduction)
 
 
-@tf_export("losses.cosine_distance")
+@tf_export(v1=["losses.cosine_distance"])
 @deprecated_args(None, "dim is deprecated, use axis instead", "dim")
 def cosine_distance(
     labels, predictions, axis=None, weights=1.0, scope=None,
@@ -312,7 +312,7 @@ def cosine_distance(
         losses, weights, scope, loss_collection, reduction=reduction)
 
 
-@tf_export("losses.hinge_loss")
+@tf_export(v1=["losses.hinge_loss"])
 def hinge_loss(labels, logits, weights=1.0, scope=None,
                loss_collection=ops.GraphKeys.LOSSES,
                reduction=Reduction.SUM_BY_NONZERO_WEIGHTS):
@@ -362,7 +362,7 @@ def hinge_loss(labels, logits, weights=1.0, scope=None,
         losses, weights, scope, loss_collection, reduction=reduction)
 
 
-@tf_export("losses.huber_loss")
+@tf_export(v1=["losses.huber_loss"])
 def huber_loss(labels, predictions, weights=1.0, delta=1.0, scope=None,
                loss_collection=ops.GraphKeys.LOSSES,
                reduction=Reduction.SUM_BY_NONZERO_WEIGHTS):
@@ -440,7 +440,7 @@ def huber_loss(labels, predictions, weights=1.0, delta=1.0, scope=None,
         losses, weights, scope, loss_collection, reduction=reduction)
 
 
-@tf_export("losses.log_loss")
+@tf_export(v1=["losses.log_loss"])
 def log_loss(labels, predictions, weights=1.0, epsilon=1e-7, scope=None,
              loss_collection=ops.GraphKeys.LOSSES,
              reduction=Reduction.SUM_BY_NONZERO_WEIGHTS):
@@ -497,7 +497,7 @@ def log_loss(labels, predictions, weights=1.0, epsilon=1e-7, scope=None,
 
 
 # TODO(b/37208492): Add reduction arg.
-@tf_export("losses.mean_pairwise_squared_error")
+@tf_export(v1=["losses.mean_pairwise_squared_error"])
 def mean_pairwise_squared_error(
     labels, predictions, weights=1.0, scope=None,
     loss_collection=ops.GraphKeys.LOSSES):
@@ -593,7 +593,7 @@ def mean_pairwise_squared_error(
       return mean_loss
 
 
-@tf_export("losses.mean_squared_error")
+@tf_export(v1=["losses.mean_squared_error"])
 def mean_squared_error(
     labels, predictions, weights=1.0, scope=None,
     loss_collection=ops.GraphKeys.LOSSES,
@@ -646,7 +646,7 @@ def mean_squared_error(
         losses, weights, scope, loss_collection, reduction=reduction)
 
 
-@tf_export("losses.sigmoid_cross_entropy")
+@tf_export(v1=["losses.sigmoid_cross_entropy"])
 def sigmoid_cross_entropy(
     multi_class_labels, logits, weights=1.0, label_smoothing=0, scope=None,
     loss_collection=ops.GraphKeys.LOSSES,
@@ -710,7 +710,7 @@ def sigmoid_cross_entropy(
         losses, weights, scope, loss_collection, reduction=reduction)
 
 
-@tf_export("losses.softmax_cross_entropy")
+@tf_export(v1=["losses.softmax_cross_entropy"])
 def softmax_cross_entropy(
     onehot_labels, logits, weights=1.0, label_smoothing=0, scope=None,
     loss_collection=ops.GraphKeys.LOSSES,
@@ -832,7 +832,7 @@ def _remove_squeezable_dimensions(
   return labels, predictions, weights
 
 
-@tf_export("losses.sparse_softmax_cross_entropy")
+@tf_export(v1=["losses.sparse_softmax_cross_entropy"])
 def sparse_softmax_cross_entropy(
     labels, logits, weights=1.0, scope=None,
     loss_collection=ops.GraphKeys.LOSSES,
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.losses.-mean-squared-error.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.losses.-mean-squared-error.pbtxt
new file mode 100644
index 00000000000..a5718533500
--- /dev/null
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.losses.-mean-squared-error.pbtxt
@@ -0,0 +1,22 @@
+path: "tensorflow.keras.losses.MeanSquaredError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.losses.MeanSquaredError\'>"
+  is_instance: "<class \'tensorflow.python.keras.losses.Loss\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'reduction\', \'name\'], varargs=None, keywords=None, defaults=[\'sum_over_batch_size\', \'None\'], "
+  }
+  member_method {
+    name: "call"
+    argspec: "args=[\'self\', \'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.losses.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.losses.pbtxt
index eca6b915388..a0af6a29f0f 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.keras.losses.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.losses.pbtxt
@@ -1,5 +1,9 @@
 path: "tensorflow.keras.losses"
 tf_module {
+  member {
+    name: "MeanSquaredError"
+    mtype: "<type \'type\'>"
+  }
   member_method {
     name: "KLD"
     argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.losses.-mean-squared-error.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.losses.-mean-squared-error.pbtxt
new file mode 100644
index 00000000000..a626d9c7e6e
--- /dev/null
+++ b/tensorflow/tools/api/golden/v1/tensorflow.losses.-mean-squared-error.pbtxt
@@ -0,0 +1,22 @@
+path: "tensorflow.losses.MeanSquaredError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.losses.MeanSquaredError\'>"
+  is_instance: "<class \'tensorflow.python.keras.losses.Loss\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'reduction\', \'name\'], varargs=None, keywords=None, defaults=[\'sum_over_batch_size\', \'None\'], "
+  }
+  member_method {
+    name: "call"
+    argspec: "args=[\'self\', \'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.losses.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.losses.pbtxt
index c1d190ae116..a198db1b35c 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.losses.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.losses.pbtxt
@@ -1,5 +1,9 @@
 path: "tensorflow.losses"
 tf_module {
+  member {
+    name: "MeanSquaredError"
+    mtype: "<type \'type\'>"
+  }
   member {
     name: "Reduction"
     mtype: "<type \'type\'>"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.losses.-mean-squared-error.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.losses.-mean-squared-error.pbtxt
new file mode 100644
index 00000000000..a5718533500
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.losses.-mean-squared-error.pbtxt
@@ -0,0 +1,22 @@
+path: "tensorflow.keras.losses.MeanSquaredError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.losses.MeanSquaredError\'>"
+  is_instance: "<class \'tensorflow.python.keras.losses.Loss\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'reduction\', \'name\'], varargs=None, keywords=None, defaults=[\'sum_over_batch_size\', \'None\'], "
+  }
+  member_method {
+    name: "call"
+    argspec: "args=[\'self\', \'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.losses.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.losses.pbtxt
index 8618c6f1c7c..cb156e2248f 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.keras.losses.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.losses.pbtxt
@@ -1,5 +1,9 @@
 path: "tensorflow.keras.losses"
 tf_module {
+  member {
+    name: "MeanSquaredError"
+    mtype: "<type \'type\'>"
+  }
   member {
     name: "Reduction"
     mtype: "<type \'type\'>"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.losses.-mean-squared-error.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.losses.-mean-squared-error.pbtxt
new file mode 100644
index 00000000000..a626d9c7e6e
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.losses.-mean-squared-error.pbtxt
@@ -0,0 +1,22 @@
+path: "tensorflow.losses.MeanSquaredError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.losses.MeanSquaredError\'>"
+  is_instance: "<class \'tensorflow.python.keras.losses.Loss\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'reduction\', \'name\'], varargs=None, keywords=None, defaults=[\'sum_over_batch_size\', \'None\'], "
+  }
+  member_method {
+    name: "call"
+    argspec: "args=[\'self\', \'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.losses.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.losses.pbtxt
index c1d190ae116..87f5ef34911 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.losses.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.losses.pbtxt
@@ -1,25 +1,17 @@
 path: "tensorflow.losses"
 tf_module {
+  member {
+    name: "MeanSquaredError"
+    mtype: "<type \'type\'>"
+  }
   member {
     name: "Reduction"
     mtype: "<type \'type\'>"
   }
-  member_method {
-    name: "absolute_difference"
-    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
   member_method {
     name: "add_loss"
     argspec: "args=[\'loss\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'losses\'], "
   }
-  member_method {
-    name: "compute_weighted_loss"
-    argspec: "args=[\'losses\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
-  member_method {
-    name: "cosine_distance"
-    argspec: "args=[\'labels\', \'predictions\', \'axis\', \'weights\', \'scope\', \'loss_collection\', \'reduction\', \'dim\'], varargs=None, keywords=None, defaults=[\'None\', \'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\', \'None\'], "
-  }
   member_method {
     name: "get_losses"
     argspec: "args=[\'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'None\', \'losses\'], "
@@ -36,36 +28,4 @@ tf_module {
     name: "get_total_loss"
     argspec: "args=[\'add_regularization_losses\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'total_loss\'], "
   }
-  member_method {
-    name: "hinge_loss"
-    argspec: "args=[\'labels\', \'logits\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
-  member_method {
-    name: "huber_loss"
-    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'delta\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
-  member_method {
-    name: "log_loss"
-    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'epsilon\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'1e-07\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
-  member_method {
-    name: "mean_pairwise_squared_error"
-    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], "
-  }
-  member_method {
-    name: "mean_squared_error"
-    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
-  member_method {
-    name: "sigmoid_cross_entropy"
-    argspec: "args=[\'multi_class_labels\', \'logits\', \'weights\', \'label_smoothing\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
-  member_method {
-    name: "softmax_cross_entropy"
-    argspec: "args=[\'onehot_labels\', \'logits\', \'weights\', \'label_smoothing\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
-  member_method {
-    name: "sparse_softmax_cross_entropy"
-    argspec: "args=[\'labels\', \'logits\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], "
-  }
 }