diff --git a/tensorflow/lite/testing/model_coverage/model_coverage_lib.py b/tensorflow/lite/testing/model_coverage/model_coverage_lib.py
index ba1534c6152..eaf8918308e 100644
--- a/tensorflow/lite/testing/model_coverage/model_coverage_lib.py
+++ b/tensorflow/lite/testing/model_coverage/model_coverage_lib.py
@@ -242,8 +242,9 @@ def compare_models_v2(tflite_model, concrete_func, input_data=None,
 
   # Gets the TensorFlow results as a map from the output names to outputs.
   # Converts the map into a list that is equivalent to the TFLite list.
-  tf_results_map = concrete_func(input_data_func)
-  tf_results = [tf_results_map[tf_results_map.keys()[0]]]
+  tf_results = concrete_func(input_data_func)
+  if isinstance(tf_results, dict):
+    tf_results = [tf_results[tf_results.keys()[0]]]
   tflite_results = _evaluate_tflite_model(tflite_model, input_data)
   for tf_result, tflite_result in zip(tf_results, tflite_results):
     np.testing.assert_almost_equal(tf_result, tflite_result, tolerance)
diff --git a/tensorflow/python/framework/convert_to_constants.py b/tensorflow/python/framework/convert_to_constants.py
index 6352ef16c4e..43b713d8ca9 100644
--- a/tensorflow/python/framework/convert_to_constants.py
+++ b/tensorflow/python/framework/convert_to_constants.py
@@ -109,14 +109,31 @@ def convert_variables_to_constants_v2(func):
   input_tensors = func.inputs[-len(func.captured_inputs):]
   for var in func.graph.variables:
     index = func.captured_inputs.index(var.handle)
-    tensor = input_tensors[index]
-    node_name = get_name(tensor.name)
-    tensor_data[node_name] = var.numpy()
-    map_name_to_handle[node_name] = var.handle
+    tensor_name = get_name(input_tensors[index].name)
+    tensor_data[tensor_name] = var.numpy()
+    map_name_to_handle[tensor_name] = var.handle
+
+  # Get mapping from input name to value for non-variable placeholders.
+  map_name_to_value = {}
+  for name_tensor, value_tensor in zip(input_tensors, func.captured_inputs):
+    tensor_name = get_name(name_tensor.name)
+    if tensor_name not in map_name_to_handle:
+      map_name_to_value[tensor_name] = value_tensor
 
   resource_identities = {}
-  resource_placeholders = {}
+  placeholders = {}
+  converted_input_indices = set()
   for node in graph_def.node:
+    if node.name in map_name_to_value:
+      # Get the dtype and data for the Placeholders whose values are stored as
+      # Tensors. This is the case for values that were originally Const ops.
+      tensor = map_name_to_value[node.name]
+      placeholders[node.name] = {
+          "dtype": node.attr["dtype"],
+          "data": tensor.numpy(),
+      }
+      converted_input_indices.add(
+          func.captured_inputs.index(map_name_to_value[node.name]))
     if node.op == "ReadVariableOp":
       # Get name of Placeholder op associated with ReadVariableOp. There can be
       # an Identity in between the ReadVariableOp and Placeholder. Store the
@@ -130,22 +147,23 @@ def convert_variables_to_constants_v2(func):
                          "to the ReadVariableOp.")
       # Build a map of Placeholder ops that are inputs to ReadVariableOps to the
       # variable's dtype and data.
-      resource_placeholders[input_name] = {
+      placeholders[input_name] = {
           "dtype": node.attr["dtype"],
           "data": tensor_data[input_name],
       }
+      converted_input_indices.add(
+          func.captured_inputs.index(map_name_to_handle[input_name]))
 
   # Reconstruct the graph with constants in place of variables.
   output_graph_def = graph_pb2.GraphDef()
   how_many_converted = 0
 
-  converted_input_indices = set([])
   for input_node in graph_def.node:
     output_node = output_graph_def.node.add()
-    # Convert Placeholder ops that are inputs to ReadVariableOps into Const ops.
-    if input_node.name in resource_placeholders:
-      dtype = resource_placeholders[input_node.name]["dtype"]
-      data = resource_placeholders[input_node.name]["data"]
+    # Convert Placeholder ops to Const ops.
+    if input_node.name in placeholders:
+      dtype = placeholders[input_node.name]["dtype"]
+      data = placeholders[input_node.name]["data"]
 
       output_node.op = "Const"
       output_node.name = input_node.name
@@ -154,8 +172,6 @@ def convert_variables_to_constants_v2(func):
           tensor_util.make_tensor_proto(
               data, dtype=dtype.type, shape=data.shape))
       how_many_converted += 1
-      converted_input_indices.add(
-          func.captured_inputs.index(map_name_to_handle[input_node.name]))
     # Change the dtype for Identity ops that are inputs to ReadVariableOps.
     elif input_node.name in resource_identities:
       output_node.CopyFrom(input_node)