chore: import upstream snapshot with attribution

tensorflow/python/framework/proto_test.py

@@ -0,0 +1,43 @@
+# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Protobuf related tests."""
+
+import numpy as np
+
+from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import ops
+from tensorflow.python.platform import test
+
+
+class ProtoTest(test.TestCase):
+
+  # TODO(vrv): re-enable this test once we figure out how this can
+  # pass the pip install test (where the user is expected to have
+  # protobuf installed).
+  def _testLargeProto(self):
+    # create a constant of size > 64MB.
+    a = constant_op.constant(np.zeros([1024, 1024, 17]))
+    # Serialize the resulting graph def.
+    gdef = a.op.graph.as_graph_def()
+    serialized = gdef.SerializeToString()
+    unserialized = ops.Graph().as_graph_def()
+    # Deserialize back. Protobuf python library should support
+    # protos larger than 64MB.
+    unserialized.ParseFromString(serialized)
+    self.assertProtoEquals(unserialized, gdef)
+
+
+if __name__ == "__main__":
+  test.main()