path: root/python37.patch

Support python 3.7, cherry-pick of:
https://github.com/tensorflow/tensorflow/commit/abb903df7a5998b33547c02e95f9fa47c00f31f4
https://github.com/tensorflow/tensorflow/commit/2b0805301e4531dd7c2ed677d932f6408675460e
https://github.com/tensorflow/tensorflow/pull/21202
https://github.com/tensorflow/tensorflow/pull/23453
---
diff --git a/tensorflow/c/eager/c_api.cc b/tensorflow/c/eager/c_api.cc
index 81221c4078..50873a07d8 100644
--- a/tensorflow/c/eager/c_api.cc
+++ b/tensorflow/c/eager/c_api.cc
@@ -46,6 +46,7 @@ limitations under the License.
 #include "tensorflow/core/framework/tensor_shape.pb.h"
 #include "tensorflow/core/framework/types.h"
 #include "tensorflow/core/lib/core/refcount.h"
+#include "tensorflow/core/lib/core/stringpiece.h"
 #include "tensorflow/core/lib/gtl/cleanup.h"
 #include "tensorflow/core/lib/gtl/flatmap.h"
 #include "tensorflow/core/lib/gtl/map_util.h"
@@ -200,8 +201,8 @@ void TFE_ContextOptionsSetConfig(TFE_ContextOptions* options, const void* proto,
 }
 
 void TFE_ContextOptionsSetAsync(TFE_ContextOptions* options,
-                                unsigned char async) {
-  options->async = async;
+                                unsigned char enable) {
+  options->async = enable;
 }
 void TFE_ContextOptionsSetDevicePlacementPolicy(
     TFE_ContextOptions* options, TFE_ContextDevicePlacementPolicy policy) {
@@ -218,9 +219,9 @@ TF_CAPI_EXPORT extern void TFE_ContextOptionsSetServerDef(
 }
 
 TF_CAPI_EXPORT extern void TFE_ContextSetAsyncForThread(TFE_Context* ctx,
-                                                        unsigned char async,
+                                                        unsigned char enable,
                                                         TF_Status* status) {
-  status->status = ctx->context.SetAsyncForThread(async);
+  status->status = ctx->context.SetAsyncForThread(enable);
 }
 
 void TFE_DeleteContextOptions(TFE_ContextOptions* options) { delete options; }
@@ -421,8 +422,11 @@ TF_AttrType TFE_OpNameGetAttrType(TFE_Context* ctx,
   return ret;
 }
 
-void TFE_OpSetAttrString(TFE_Op* op, const char* attr_name, const char* value) {
-  op->operation.MutableAttrs()->Set(attr_name, value);
+void TFE_OpSetAttrString(TFE_Op* op, const char* attr_name, const void* value,
+                         size_t length) {
+  op->operation.MutableAttrs()->Set(
+      attr_name,
+      tensorflow::StringPiece(static_cast<const char*>(value), length));
 }
 
 void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name, int64_t value) {
@@ -473,16 +477,22 @@ void TFE_OpSetAttrFunction(TFE_Op* op, const char* attr_name,
   op->operation.MutableAttrs()->Set(attr_name, attr_value);
 }
 
-#define TFE_OP_SET_ATTR_LIST(fn, type)                                \
-  void fn(TFE_Op* op, const char* attr_name, const type* values,      \
-          int num_values) {                                           \
-    op->operation.MutableAttrs()->Set(                                \
-        attr_name,                                                    \
-        tensorflow::gtl::ArraySlice<const type>(values, num_values)); \
+void TFE_OpSetAttrStringList(TFE_Op* op, const char* attr_name,
+                             const void* const* values, const size_t* lengths,
+                             int num_values) {
+  std::vector<tensorflow::StringPiece> v(num_values);
+  for (int i = 0; i < num_values; ++i) {
+    v[i] = tensorflow::StringPiece(static_cast<const char*>(values[i]),
+                                   lengths[i]);
   }
-TFE_OP_SET_ATTR_LIST(TFE_OpSetAttrStringList, char*)
-TFE_OP_SET_ATTR_LIST(TFE_OpSetAttrFloatList, float)
-#undef TFE_OP_SET_ATTR_LIST
+  op->operation.MutableAttrs()->Set(attr_name, v);
+}
+
+void TFE_OpSetAttrFloatList(TFE_Op* op, const char* attr_name,
+                            const float* values, int num_values) {
+  op->operation.MutableAttrs()->Set(
+      attr_name, tensorflow::gtl::ArraySlice<const float>(values, num_values));
+}
 
 void TFE_OpSetAttrIntList(TFE_Op* op, const char* attr_name,
                           const int64_t* values, int num_values) {
@@ -655,9 +665,11 @@ void SetOpAttrValueScalar(TFE_Context* ctx, TFE_Op* op,
                           const tensorflow::AttrValue& default_value,
                           const char* attr_name, TF_Status* status) {
   switch (default_value.value_case()) {
-    case tensorflow::AttrValue::kS:
-      TFE_OpSetAttrString(op, attr_name, default_value.s().data());
+    case tensorflow::AttrValue::kS: {
+      const string& v = default_value.s();
+      TFE_OpSetAttrString(op, attr_name, v.data(), v.size());
       break;
+    }
     case tensorflow::AttrValue::kI:
       TFE_OpSetAttrInt(op, attr_name, static_cast<int64_t>(default_value.i()));
       break;
diff --git a/tensorflow/c/eager/c_api.h b/tensorflow/c/eager/c_api.h
index 1862af3ce2..8c6bc63c9b 100644
--- a/tensorflow/c/eager/c_api.h
+++ b/tensorflow/c/eager/c_api.h
@@ -76,7 +76,7 @@ typedef enum TFE_ContextDevicePlacementPolicy {
 // Sets the default execution mode (sync/async). Note that this can be
 // overridden per thread using TFE_ContextSetAsyncForThread.
 TF_CAPI_EXPORT extern void TFE_ContextOptionsSetAsync(TFE_ContextOptions*,
-                                                      unsigned char async);
+                                                      unsigned char enable);
 
 TF_CAPI_EXPORT extern void TFE_ContextOptionsSetDevicePlacementPolicy(
     TFE_ContextOptions*, TFE_ContextDevicePlacementPolicy);
@@ -125,7 +125,7 @@ TFE_ContextGetDevicePlacementPolicy(TFE_Context*);
 
 // Overrides the execution mode (sync/async) for the current thread.
 TF_CAPI_EXPORT extern void TFE_ContextSetAsyncForThread(TFE_Context*,
-                                                        unsigned char async,
+                                                        unsigned char enable,
                                                         TF_Status* status);
 
 // Causes the calling thread to block till all ops dispatched in async mode
@@ -278,7 +278,8 @@ TF_CAPI_EXPORT extern TF_AttrType TFE_OpNameGetAttrType(
 
 TF_CAPI_EXPORT extern void TFE_OpSetAttrString(TFE_Op* op,
                                                const char* attr_name,
-                                               const char* value);
+                                               const void* value,
+                                               size_t length);
 TF_CAPI_EXPORT extern void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name,
                                             int64_t value);
 TF_CAPI_EXPORT extern void TFE_OpSetAttrFloat(TFE_Op* op, const char* attr_name,
@@ -305,7 +306,8 @@ TF_CAPI_EXPORT extern void TFE_OpSetAttrFunction(TFE_Op* op,
 
 TF_CAPI_EXPORT extern void TFE_OpSetAttrStringList(TFE_Op* op,
                                                    const char* attr_name,
-                                                   const char** value,
+                                                   const void* const* values,
+                                                   const size_t* lengths,
                                                    int num_values);
 TF_CAPI_EXPORT extern void TFE_OpSetAttrIntList(TFE_Op* op,
                                                 const char* attr_name,
diff --git a/tensorflow/c/eager/c_api_test.cc b/tensorflow/c/eager/c_api_test.cc
index 27ff5f7211..b796246747 100644
--- a/tensorflow/c/eager/c_api_test.cc
+++ b/tensorflow/c/eager/c_api_test.cc
@@ -1083,8 +1083,8 @@ TFE_TensorHandle* CreateVariable(TFE_Context* ctx, float value,
   if (TF_GetCode(status) != TF_OK) return nullptr;
   TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
   TFE_OpSetAttrShape(op, "shape", {}, 0, status);
-  TFE_OpSetAttrString(op, "container", "");
-  TFE_OpSetAttrString(op, "shared_name", "");
+  TFE_OpSetAttrString(op, "container", "", 0);
+  TFE_OpSetAttrString(op, "shared_name", "", 0);
   if (TF_GetCode(status) != TF_OK) return nullptr;
   TFE_TensorHandle* var_handle = nullptr;
   int num_retvals = 1;
diff --git a/tensorflow/python/eager/pywrap_tfe.h b/tensorflow/python/eager/pywrap_tfe.h
index a916a75f00..823c4078b8 100644
--- a/tensorflow/python/eager/pywrap_tfe.h
+++ b/tensorflow/python/eager/pywrap_tfe.h
@@ -89,7 +89,7 @@ int MaybeRaiseExceptionFromStatus(const tensorflow::Status& status,
                                   PyObject* exception);
 
 // Returns the string associated with the passed-in python object.
-char* TFE_GetPythonString(PyObject* o);
+const char* TFE_GetPythonString(PyObject* o);
 
 // Returns a unique id on each call.
 int64_t get_uid();
diff --git a/tensorflow/python/eager/pywrap_tfe_src.cc b/tensorflow/python/eager/pywrap_tfe_src.cc
index 6c9481c3af..9cf428da99 100644
--- a/tensorflow/python/eager/pywrap_tfe_src.cc
+++ b/tensorflow/python/eager/pywrap_tfe_src.cc
@@ -205,14 +205,20 @@ bool ParseDimensionValue(const string& key, PyObject* py_value,
 }
 
 bool ParseStringValue(const string& key, PyObject* py_value, TF_Status* status,
-                      const char** value) {
+                      tensorflow::StringPiece* value) {
   if (PyBytes_Check(py_value)) {
-    *value = PyBytes_AsString(py_value);
+    Py_ssize_t size = 0;
+    char* buf = nullptr;
+    if (PyBytes_AsStringAndSize(py_value, &buf, &size) < 0) return false;
+    *value = tensorflow::StringPiece(buf, size);
     return true;
   }
 #if PY_MAJOR_VERSION >= 3
   if (PyUnicode_Check(py_value)) {
-    *value = PyUnicode_AsUTF8(py_value);
+    Py_ssize_t size = 0;
+    const char* buf = PyUnicode_AsUTF8AndSize(py_value, &size);
+    if (buf == nullptr) return false;
+    *value = tensorflow::StringPiece(buf, size);
     return true;
   }
 #endif
@@ -275,8 +281,16 @@ bool SetOpAttrList(
   }
 
   if (type == TF_ATTR_STRING) {
-    PARSE_LIST(const char*, ParseStringValue);
-    TFE_OpSetAttrStringList(op, key, values.get(), num_values);
+    std::unique_ptr<const void*[]> values(new const void*[num_values]);
+    std::unique_ptr<size_t[]> lengths(new size_t[num_values]);
+    for (int i = 0; i < num_values; ++i) {
+      tensorflow::StringPiece value;
+      tensorflow::Safe_PyObjectPtr py_value(PySequence_ITEM(py_list, i));
+      if (!ParseStringValue(key, py_value.get(), status, &value)) return false;
+      values[i] = value.data();
+      lengths[i] = value.size();
+    }
+    TFE_OpSetAttrStringList(op, key, values.get(), lengths.get(), num_values);
   } else if (type == TF_ATTR_INT) {
     PARSE_LIST(int64_t, ParseInt64Value);
     TFE_OpSetAttrIntList(op, key, values.get(), num_values);
@@ -379,12 +393,15 @@ void SetOpAttrListDefault(
     TF_Status* status) {
   if (type == TF_ATTR_STRING) {
     int num_values = attr.default_value().list().s_size();
-    std::unique_ptr<const char*[]> values(new const char*[num_values]);
+    std::unique_ptr<const void*[]> values(new const void*[num_values]);
+    std::unique_ptr<size_t[]> lengths(new size_t[num_values]);
     (*attr_list_sizes)[key] = num_values;
     for (int i = 0; i < num_values; i++) {
-      values[i] = attr.default_value().list().s(i).data();
+      const string& v = attr.default_value().list().s(i);
+      values[i] = v.data();
+      lengths[i] = v.size();
     }
-    TFE_OpSetAttrStringList(op, key, values.get(), num_values);
+    TFE_OpSetAttrStringList(op, key, values.get(), lengths.get(), num_values);
   } else if (type == TF_ATTR_INT) {
     int num_values = attr.default_value().list().i_size();
     std::unique_ptr<int64_t[]> values(new int64_t[num_values]);
@@ -470,9 +487,9 @@ bool SetOpAttrScalar(
     tensorflow::gtl::FlatMap<string, tensorflow::int64>* attr_list_sizes,
     TF_Status* status) {
   if (type == TF_ATTR_STRING) {
-    const char* value;
+    tensorflow::StringPiece value;
     if (!ParseStringValue(key, py_value, status, &value)) return false;
-    TFE_OpSetAttrString(op, key, value);
+    TFE_OpSetAttrString(op, key, value.data(), value.size());
   } else if (type == TF_ATTR_INT) {
     int64_t value;
     if (!ParseInt64Value(key, py_value, status, &value)) return false;
@@ -533,7 +550,7 @@ bool SetOpAttrScalar(
     //     (which is what the various "defun" or "Defun" decorators do).
     // And in the future also allow an object that can encapsulate
     // the function name and its attribute values.
-    const char* func_name = nullptr;
+    tensorflow::StringPiece func_name;
     if (!ParseStringValue(key, py_value, status, &func_name)) {
       PyObject* name_attr = PyObject_GetAttrString(py_value, "name");
       if (name_attr == nullptr ||
@@ -549,7 +566,8 @@ bool SetOpAttrScalar(
         return false;
       }
     }
-    TFE_Op* func = TFE_NewOp(ctx, func_name, status);
+    TFE_Op* func = TFE_NewOp(
+        ctx, string(func_name.data(), func_name.size()).c_str(), status);
     if (TF_GetCode(status) != TF_OK) return false;
     TFE_OpSetAttrFunction(op, key, func);
     TFE_DeleteOp(func);
@@ -807,7 +825,7 @@ int MaybeRaiseExceptionFromStatus(const tensorflow::Status& status,
   return -1;
 }
 
-char* TFE_GetPythonString(PyObject* o) {
+const char* TFE_GetPythonString(PyObject* o) {
   if (PyBytes_Check(o)) {
     return PyBytes_AsString(o);
   }
diff --git a/tensorflow/python/lib/core/ndarray_tensor.cc b/tensorflow/python/lib/core/ndarray_tensor.cc
index 9df38d464c..f87674a524 100644
--- a/tensorflow/python/lib/core/ndarray_tensor.cc
+++ b/tensorflow/python/lib/core/ndarray_tensor.cc
@@ -136,6 +136,31 @@ Status PyArray_TYPE_to_TF_DataType(PyArrayObject* array,
   return Status::OK();
 }
 
+Status PyObjectToString(PyObject* obj, const char** ptr, Py_ssize_t* len) {
+  if (!PyUnicode_Check(obj)) {
+    char* buf;
+    if (PyBytes_AsStringAndSize(obj, &buf, len) != 0) {
+      return errors::Internal("Unable to get element as bytes.");
+    }
+    *ptr = buf;
+    return Status::OK();
+  }
+#if (PY_MAJOR_VERSION > 3 || (PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION >= 3))
+  *ptr = PyUnicode_AsUTF8AndSize(obj, len);
+  if (*ptr != nullptr) return Status::OK();
+#else
+  PyObject* utemp = PyUnicode_AsUTF8String(obj);
+  char* buf;
+  if (utemp != nullptr && PyBytes_AsStringAndSize(utemp, &buf, len) != -1) {
+    *ptr = buf;
+    Py_DECREF(utemp);
+    return Status::OK();
+  }
+  Py_XDECREF(utemp);
+#endif
+  return errors::Internal("Unable to convert element to UTF-8.");
+}
+
 // Iterate over the string array 'array', extract the ptr and len of each string
 // element and call f(ptr, len).
 template <typename F>
@@ -148,33 +173,10 @@ Status PyBytesArrayMap(PyArrayObject* array, F f) {
     if (!item) {
       return errors::Internal("Unable to get element from the feed - no item.");
     }
-    char* ptr;
     Py_ssize_t len;
-
-    if (PyUnicode_Check(item.get())) {
-#if PY_VERSION_HEX >= 0x03030000
-      // Accept unicode by converting to UTF-8 bytes.
-      ptr = PyUnicode_AsUTF8AndSize(item.get(), &len);
-      if (!ptr) {
-        return errors::Internal("Unable to get element as UTF-8.");
-      }
-      f(ptr, len);
-#else
-      PyObject* utemp = PyUnicode_AsUTF8String(item.get());
-      if (!utemp || PyBytes_AsStringAndSize(utemp, &ptr, &len) == -1) {
-        Py_XDECREF(utemp);
-        return errors::Internal("Unable to convert element to UTF-8.");
-      }
-      f(ptr, len);
-      Py_DECREF(utemp);
-#endif
-    } else {
-      int success = PyBytes_AsStringAndSize(item.get(), &ptr, &len);
-      if (success != 0) {
-        return errors::Internal("Unable to get element as bytes.");
-      }
-      f(ptr, len);
-    }
+    const char* ptr;
+    TF_RETURN_IF_ERROR(PyObjectToString(item.get(), &ptr, &len));
+    f(ptr, len);
     PyArray_ITER_NEXT(iter.get());
   }
   return Status::OK();
@@ -186,10 +188,11 @@ Status EncodePyBytesArray(PyArrayObject* array, tensorflow::int64 nelems,
                           size_t* size, void** buffer) {
   // Compute bytes needed for encoding.
   *size = 0;
-  TF_RETURN_IF_ERROR(PyBytesArrayMap(array, [&size](char* ptr, Py_ssize_t len) {
-    *size +=
-        sizeof(tensorflow::uint64) + tensorflow::core::VarintLength(len) + len;
-  }));
+  TF_RETURN_IF_ERROR(
+      PyBytesArrayMap(array, [&size](const char* ptr, Py_ssize_t len) {
+        *size += sizeof(tensorflow::uint64) +
+                 tensorflow::core::VarintLength(len) + len;
+      }));
   // Encode all strings.
   std::unique_ptr<char[]> base_ptr(new char[*size]);
   char* base = base_ptr.get();
@@ -198,7 +201,7 @@ Status EncodePyBytesArray(PyArrayObject* array, tensorflow::int64 nelems,
   tensorflow::uint64* offsets = reinterpret_cast<tensorflow::uint64*>(base);
 
   TF_RETURN_IF_ERROR(PyBytesArrayMap(
-      array, [&base, &data_start, &dst, &offsets](char* ptr, Py_ssize_t len) {
+      array, [&data_start, &dst, &offsets](const char* ptr, Py_ssize_t len) {
         *offsets = (dst - data_start);
         offsets++;
         dst = tensorflow::core::EncodeVarint64(dst, len);
diff --git a/tensorflow/python/lib/core/py_func.cc b/tensorflow/python/lib/core/py_func.cc
index a13fdbb57c..a7f8065fb3 100644
--- a/tensorflow/python/lib/core/py_func.cc
+++ b/tensorflow/python/lib/core/py_func.cc
@@ -303,6 +303,35 @@ class NumpyTensorBuffer : public TensorBuffer {
   void* data_;
 };
 
+Status PyObjectToString(PyObject* obj, string* str) {
+  char* py_bytes;
+  Py_ssize_t size;
+  if (PyBytes_AsStringAndSize(obj, &py_bytes, &size) != -1) {
+    str->assign(py_bytes, size);
+    return Status::OK();
+  }
+#if PY_MAJOR_VERSION >= 3
+  const char* ptr = PyUnicode_AsUTF8AndSize(obj, &size);
+  if (ptr != nullptr) {
+    str->assign(ptr, size);
+    return Status::OK();
+  }
+#else
+  if (PyUnicode_Check(obj)) {
+    PyObject* unicode = PyUnicode_AsUTF8String(obj);
+    char* ptr;
+    if (unicode && PyString_AsStringAndSize(unicode, &ptr, &size) != -1) {
+      str->assign(ptr, size);
+      Py_DECREF(unicode);
+      return Status::OK();
+    }
+    Py_XDECREF(unicode);
+  }
+#endif
+  return errors::Unimplemented("Unsupported object type ",
+                               obj->ob_type->tp_name);
+}
+
 Status ConvertNdarrayToTensor(PyObject* obj, Tensor* ret) {
   PyArrayObject* input = reinterpret_cast<PyArrayObject*>(obj);
   DataType dtype = DT_INVALID;
@@ -318,29 +347,7 @@ Status ConvertNdarrayToTensor(PyObject* obj, Tensor* ret) {
       auto tflat = t.flat<string>();
       PyObject** input_data = reinterpret_cast<PyObject**>(PyArray_DATA(input));
       for (int i = 0; i < tflat.dimension(0); ++i) {
-        char* el;
-        Py_ssize_t el_size;
-        if (PyBytes_AsStringAndSize(input_data[i], &el, &el_size) == -1) {
-#if PY_MAJOR_VERSION >= 3
-          el = PyUnicode_AsUTF8AndSize(input_data[i], &el_size);
-#else
-          el = nullptr;
-          if (PyUnicode_Check(input_data[i])) {
-            PyObject* unicode = PyUnicode_AsUTF8String(input_data[i]);
-            if (unicode) {
-              if (PyString_AsStringAndSize(unicode, &el, &el_size) == -1) {
-                Py_DECREF(unicode);
-                el = nullptr;
-              }
-            }
-          }
-#endif
-          if (!el) {
-            return errors::Unimplemented("Unsupported object type ",
-                                         input_data[i]->ob_type->tp_name);
-          }
-        }
-        tflat(i) = string(el, el_size);
+        TF_RETURN_IF_ERROR(PyObjectToString(input_data[i], &tflat(i)));
       }
       *ret = t;
       break;
diff --git a/tensorflow/python/pywrap_tfe.i b/tensorflow/python/pywrap_tfe.i
index 500dc30cc3..eb627d3ecc 100644
--- a/tensorflow/python/pywrap_tfe.i
+++ b/tensorflow/python/pywrap_tfe.i
@@ -102,20 +102,29 @@ limitations under the License.
   }
 }
 
+// For const parameters in a function, SWIG pretty much ignores the const.
+// See: http://www.swig.org/Doc2.0/SWIG.html#SWIG_nn13
+// Hence the 'const_cast'.
 %typemap(in) const char* serialized_function_def {
-  $1 = TFE_GetPythonString($input);
+  $1 = const_cast<char*>(TFE_GetPythonString($input));
 }
 
+// For const parameters in a function, SWIG pretty much ignores the const.
+// See: http://www.swig.org/Doc2.0/SWIG.html#SWIG_nn13
+// Hence the 'const_cast'.
 %typemap(in) const char* device_name {
   if ($input == Py_None) {
     $1 = nullptr;
   } else {
-    $1 = TFE_GetPythonString($input);
+    $1 = const_cast<char*>(TFE_GetPythonString($input));
   }
 }
 
+// For const parameters in a function, SWIG pretty much ignores the const.
+// See: http://www.swig.org/Doc2.0/SWIG.html#SWIG_nn13
+// Hence the 'const_cast'.
 %typemap(in) const char* op_name {
-  $1 = TFE_GetPythonString($input);
+  $1 = const_cast<char*>(TFE_GetPythonString($input));
 }
 
 %typemap(in) (TFE_Context*) {
diff --git a/tensorflow/workspace.bzl b/tensorflow/workspace.bzl
index ea8c727e4d..44a95d6bad 100644
--- a/tensorflow/workspace.bzl
+++ b/tensorflow/workspace.bzl
@@ -358,14 +358,18 @@ def tf_workspace(path_prefix="", tf_repo_name=""):
       },
   )
 
+  PROTOBUF_urls =[
+      "https://mirror.bazel.build/github.com/protocolbuffers/protobuf/archive/v3.6.1.2.tar.gz",
+      "https://github.com/protocolbuffers/protobuf/archive/v3.6.1.2.tar.gz",
+  ]
+  PROTOBUF_sha256 = "2244b0308846bb22b4ff0bcc675e99290ff9f1115553ae9671eba1030af31bc0"
+  PROTOBUF_strip_prefix = "protobuf-3.6.1.2"
+
   tf_http_archive(
       name = "protobuf_archive",
-      urls = [
-          "https://mirror.bazel.build/github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
-          "https://github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
-      ],
-      sha256 = "846d907acf472ae233ec0882ef3a2d24edbbe834b80c305e867ac65a1f2c59e3",
-      strip_prefix = "protobuf-396336eb961b75f03b25824fe86cf6490fb75e3a",
+      urls = PROTOBUF_urls,
+      sha256 = PROTOBUF_sha256,
+      strip_prefix = PROTOBUF_strip_prefix,
   )
 
   # We need to import the protobuf library under the names com_google_protobuf
@@ -373,22 +377,16 @@ def tf_workspace(path_prefix="", tf_repo_name=""):
   # Unfortunately there is no way to alias http_archives at the moment.
   tf_http_archive(
       name = "com_google_protobuf",
-      urls = [
-          "https://mirror.bazel.build/github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
-          "https://github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
-      ],
-      sha256 = "846d907acf472ae233ec0882ef3a2d24edbbe834b80c305e867ac65a1f2c59e3",
-      strip_prefix = "protobuf-396336eb961b75f03b25824fe86cf6490fb75e3a",
+       urls = PROTOBUF_urls,
+      sha256 = PROTOBUF_sha256,
+      strip_prefix = PROTOBUF_strip_prefix,
   )
 
   tf_http_archive(
       name = "com_google_protobuf_cc",
-      urls = [
-          "https://mirror.bazel.build/github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
-          "https://github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
-      ],
-      sha256 = "846d907acf472ae233ec0882ef3a2d24edbbe834b80c305e867ac65a1f2c59e3",
-      strip_prefix = "protobuf-396336eb961b75f03b25824fe86cf6490fb75e3a",
+      urls = PROTOBUF_urls,
+      sha256 = PROTOBUF_sha256,
+      strip_prefix = PROTOBUF_strip_prefix,
   )
 
   tf_http_archive(