1 files changed, 23 insertions, 5 deletions
diff --git a/tensorflow/python/keras/engine/sequential.py b/tensorflow/python/keras/engine/sequential.py
index 371504a503..41cdfda660 100644
--- a/tensorflow/python/keras/engine/sequential.py
+++ b/tensorflow/python/keras/engine/sequential.py
@@ -213,13 +213,31 @@ class Sequential(Model):
       self.outputs = [self.layers[-1].output]
       self.build()
 
-  @checkpointable.no_automatic_dependency_tracking
   def build(self, input_shape=None):
-    if input_shape and not self.inputs:
-      batch_shape = tuple(input_shape)
+    self._set_inputs_and_outputs(input_shape=input_shape)
+
+  def symbolic_set_inputs(self, inputs):
+    self._set_inputs_and_outputs(tensor=inputs)
+
+  @checkpointable.no_automatic_dependency_tracking
+  def _set_inputs_and_outputs(self, input_shape=None, tensor=None):
+    """Set model's input and output specs based on the input received.
+
+    If `tensor` is provided, `input_shape` is not required.
+
+    Args:
+      input_shape: Optional shape of input.
+      tensor: Optional existing tensor to wrap into the `Input` layer.
+    """
+    if not self.inputs:
       dtype = K.floatx()
-      x = Input(
-          batch_shape=batch_shape, dtype=dtype, name=self.name + '_input')
+      if tensor is not None:
+        batch_shape = (None,) + tuple(tensor.get_shape().as_list()[1:])
+        x = Input(dtype=dtype, name=self.name + '_input', tensor=tensor)
+      elif input_shape is not None:
+        batch_shape = tuple(input_shape)
+        x = Input(
+            batch_shape=batch_shape, dtype=dtype, name=self.name + '_input')
       self.inputs = [x]
       for layer in self._layers:
         x = layer(x)