chore: import upstream snapshot with attribution

tensorflow/python/grappler/model_analyzer_wrapper.cc

@@ -0,0 +1,55 @@
+/* Copyright 2019 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.
+==============================================================================*/
+
+#include <memory>
+#include <sstream>
+#include <string>
+
+#include "pybind11/pybind11.h"  // from @pybind11
+#include "tensorflow/core/grappler/grappler_item_builder.h"
+#include "tensorflow/core/protobuf/meta_graph.pb.h"
+#include "tensorflow/python/grappler/model_analyzer.h"
+#include "tensorflow/python/lib/core/pybind11_status.h"
+
+namespace py = pybind11;
+
+PYBIND11_MODULE(_pywrap_model_analyzer, m) {
+  m.def("GenerateModelReport",
+        [](const py::bytes& serialized_metagraph, bool assume_valid_feeds,
+           bool debug) -> py::bytes {
+          tensorflow::MetaGraphDef metagraph;
+          if (!metagraph.ParseFromString(std::string(serialized_metagraph))) {
+            return "The MetaGraphDef could not be parsed as a valid protocol "
+                   "buffer";
+          }
+
+          tensorflow::grappler::ItemConfig cfg;
+          cfg.apply_optimizations = false;
+          std::unique_ptr<tensorflow::grappler::GrapplerItem> item =
+              tensorflow::grappler::GrapplerItemFromMetaGraphDef(
+                  "metagraph", metagraph, cfg);
+          if (item == nullptr) {
+            return "Error: failed to preprocess metagraph: check your log file "
+                   "for errors";
+          }
+
+          tensorflow::grappler::ModelAnalyzer analyzer(*item);
+
+          std::ostringstream os;
+          tensorflow::MaybeRaiseFromStatus(
+              analyzer.GenerateReport(debug, assume_valid_feeds, os));
+          return py::bytes(os.str());
+        });
+}