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diff --git a/tensorflow/python/client/tf_session_helper.h b/tensorflow/python/client/tf_session_helper.h
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+++ b/tensorflow/python/client/tf_session_helper.h
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+#ifndef TENSORFLOW_PYTHON_CLIENT_TF_SESSION_HELPER_H_
+#define TENSORFLOW_PYTHON_CLIENT_TF_SESSION_HELPER_H_
+
+#include <Python.h>
+
+#include "numpy/arrayobject.h"
+
+#include "tensorflow/core/lib/core/errors.h"
+#include "tensorflow/core/lib/gtl/inlined_vector.h"
+#include "tensorflow/core/public/status.h"
+#include "tensorflow/core/public/tensor_c_api.h"
+
+namespace tensorflow {
+
+// Container types for the various arguments and temporary values used
+// in the wrapper.
+
+// A FeedVector is a vector of tensor name and numpy array pairs. The
+// name is a borrowed C string.
+typedef tensorflow::gtl::InlinedVector<std::pair<const char*, PyArrayObject*>,
+                                       8> FeedVector;
+
+// A NameVector is a vector of tensor or operation names, as borrowed
+// C strings.
+typedef tensorflow::gtl::InlinedVector<const char*, 8> NameVector;
+
+// A PyObjectVector is a vector of borrowed pointers to PyObjects.
+typedef tensorflow::gtl::InlinedVector<PyObject*, 8> PyObjectVector;
+
+// Safe containers for (an) owned PyObject(s). On destruction, the
+// reference count of the contained object will be decremented.
+inline void Py_DECREF_wrapper(PyObject* o) { Py_DECREF(o); }
+typedef void (*Py_DECREF_wrapper_type)(PyObject*);
+typedef std::unique_ptr<PyObject, Py_DECREF_wrapper_type> Safe_PyObjectPtr;
+typedef std::vector<Safe_PyObjectPtr> Safe_PyObjectVector;
+Safe_PyObjectPtr make_safe(PyObject* o);
+
+// Run the graph associated with the session starting with the
+// supplied inputs[].  Regardless of success of failure, inputs[] are
+// stolen by the implementation (i.e. the implementation will
+// eventually call Py_DECREF on each array input).
+//
+// On success, the tensors corresponding to output_names[0,noutputs-1]
+// are placed in out_values[], and these outputs[] become the property
+// of the caller (the caller must eventually call Py_DECREF on them).
+//
+// On failure, out_status contains a tensorflow::Status with an error
+// message.
+void TF_Run_wrapper(TF_Session* session, const FeedVector& inputs,
+                    const NameVector& output_names,
+                    const NameVector& target_nodes, Status* out_status,
+                    PyObjectVector* out_values);
+
+}  // namespace tensorflow
+
+#endif  // TENSORFLOW_PYTHON_CLIENT_TF_SESSION_HELPER_H_