[llvm][NFC] expose LLVM_HAVE_TF_API through llvm-config.h

[mtrofin]

Summary

This allows users of the llvm library discover whether llvm was built
with the tensorflow c API dependency, which helps if using the TFUtils
wrapper, for example.

We don't do the same for the LLVM_HAVE_TF_AOT flag, because that does
not expose any API.

[mehdi_amini]

LGTM

llvm/CMakeLists.txt

configure_file(
   ${LLVM_MAIN_INCLUDE_DIR}/llvm/Config/Disassemblers.def.in
   ${LLVM_INCLUDE_DIR}/llvm/Config/Disassemblers.def
   )
 configure_file(
   ${LLVM_MAIN_INCLUDE_DIR}/llvm/Config/Targets.def.in
   ${LLVM_INCLUDE_DIR}/llvm/Config/Targets.def
   )
 
+# For up-to-date instructions for installing the Tensorflow dependency, refer to
+# the bot setup script: https://github.com/google/ml-compiler-opt/blob/master/buildbot/buildbot_init.sh
+# In this case, the latest C API library is available for download from
+# https://www.tensorflow.org/install/lang_c.
+# We will expose the conditional compilation variable,
+# LLVM_HAVE_TF_API, through llvm-config.h, so that a user of the LLVM library may
+# also leverage the dependency.
+set(TENSORFLOW_C_LIB_PATH "" CACHE PATH "Path to TensorFlow C library install")
+find_library(tensorflow_c_api tensorflow PATHS ${TENSORFLOW_C_LIB_PATH}/lib)
+
+if (tensorflow_c_api)
+  set(LLVM_HAVE_TF_API "ON" CACHE BOOL "Full Tensorflow API available")
+  include_directories(${TENSORFLOW_C_LIB_PATH}/include)
+endif()
+
 # Configure the three LLVM configuration header files.
 configure_file(
   ${LLVM_MAIN_INCLUDE_DIR}/llvm/Config/config.h.cmake
   ${LLVM_INCLUDE_DIR}/llvm/Config/config.h)
 configure_file(
   ${LLVM_MAIN_INCLUDE_DIR}/llvm/Config/llvm-config.h.cmake
   ${LLVM_INCLUDE_DIR}/llvm/Config/llvm-config.h)
 configure_file(

 # Specifically, assuming python3 is installed:
 # python3 -m pip install --upgrade pip && python3 -m pip install --user tf_nightly==2.3.0.dev20200528
 # Then set TENSORFLOW_AOT_PATH to the package install - usually it's ~/.local/lib/python3.7/site-packages/tensorflow
 #
 set(TENSORFLOW_AOT_PATH "" CACHE PATH "Path to TensorFlow pip install dir")
 
 if (NOT TENSORFLOW_AOT_PATH STREQUAL "")
   set(LLVM_HAVE_TF_AOT "ON" CACHE BOOL "Tensorflow AOT available")
-  set(TENSORFLOW_AOT_COMPILER 
-    "${TENSORFLOW_AOT_PATH}/../../../../bin/saved_model_cli" 
-      CACHE PATH "Path to the Tensorflow AOT compiler")
+  set(TENSORFLOW_AOT_COMPILER
+    "${TENSORFLOW_AOT_PATH}/../../../../bin/saved_model_cli"
+  # Unlike the LLVM_HAVE_TF_API case, we don't need to expose this through
+  # llvm-config.h, because it's an internal implementation detail. A user of the llvm library that wants to also
+  # use the TF AOT compiler may do so through their custom build step.
   add_definitions("-DLLVM_HAVE_TF_AOT")
   include_directories(${TENSORFLOW_AOT_PATH}/include)
   add_subdirectory(${TENSORFLOW_AOT_PATH}/xla_aot_runtime_src
     ${CMAKE_ARCHIVE_OUTPUT_DIRECTORY}/tf_runtime)
 endif()
 
-set(TENSORFLOW_C_LIB_PATH "" CACHE PATH "Path to TensorFlow C library install")
-find_library(tensorflow_c_api tensorflow PATHS ${TENSORFLOW_C_LIB_PATH}/lib)
-
-# Similar to the above Tensorflow dependency, please refer to the same script.
-# In this case, the latest C API library is available for download from
-# https://www.tensorflow.org/install/lang_c
-if (tensorflow_c_api)
-  set(LLVM_HAVE_TF_API "ON" CACHE BOOL "Full Tensorflow API available")
-  add_definitions("-DLLVM_HAVE_TF_API")
-  include_directories(${TENSORFLOW_C_LIB_PATH}/include)
-endif()
-
 # Put this before tblgen. Else we have a circular dependence.
 add_subdirectory(lib/Demangle)
 add_subdirectory(lib/Support)
 add_subdirectory(lib/TableGen)
 
 add_subdirectory(utils/TableGen)
 
 add_subdirectory(include/llvm)

llvm/include/llvm/Analysis/Utils/TFUtils.h

 //===- TFUtils.h - utilities for tensorflow C API ---------------*- C++ -*-===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 //
 //===----------------------------------------------------------------------===//
 //
 #ifndef LLVM_ANALYSIS_UTILS_TFUTILS_H
 #define LLVM_ANALYSIS_UTILS_TFUTILS_H
 
+#include "llvm/Config/config.h"
+
 #ifdef LLVM_HAVE_TF_API
 #include "tensorflow/c/c_api.h"
 #include "llvm/IR/LLVMContext.h"
 
 #include <memory>
 #include <vector>
 
 namespace llvm {

llvm/include/llvm/Config/llvm-config.h.cmake

 /* LLVM version string */
 #define LLVM_VERSION_STRING "${PACKAGE_VERSION}"
 
 /* Whether LLVM records statistics for use with GetStatistics(),
  * PrintStatistics() or PrintStatisticsJSON()
  */
 #cmakedefine01 LLVM_FORCE_ENABLE_STATS
 
+/* Define if LLVM was built with a dependency to the libtensorflow dynamic library */
+#cmakedefine LLVM_HAVE_TF_API
+
 #endif

llvm/unittests/Analysis/InlineSizeEstimatorAnalysisTest.cpp

 #include "llvm/Testing/Support/SupportHelpers.h"
 #include "gtest/gtest.h"
 
 using namespace llvm;
 
 extern const char *TestMainArgv0;
 extern cl::opt<std::string> TFIR2NativeModelPath;
 
-#if LLVM_HAVE_TF_API
+#ifdef LLVM_HAVE_TF_API
 static std::string getModelPath() {
   SmallString<128> InputsDir = unittest::getInputFileDirectory(TestMainArgv0);
   llvm::sys::path::append(InputsDir, "ir2native_x86_64_model");
   return std::string(InputsDir);
 }
 #endif
 
 static std::unique_ptr<Module> parseIR(LLVMContext &C, const char *IR) {

 define internal i32 @top() {
   %1 = call i32 @branches(i32 2)
   %2 = call i32 @f1(i32 %1)
   ret i32 %2
 }
 )IR");
 
   FunctionAnalysisManager FAM = buildFAM();
-#if LLVM_HAVE_TF_API
+#ifdef LLVM_HAVE_TF_API
   TFIR2NativeModelPath = getModelPath();
 #endif
 
   InlineSizeEstimatorAnalysis FA;
   auto SizeEstimate = FA.run(*M->getFunction("branches"), FAM);
-#if LLVM_HAVE_TF_API
+#ifdef LLVM_HAVE_TF_API
   EXPECT_GT(*SizeEstimate, 0);
 #else
   EXPECT_FALSE(SizeEstimate.hasValue());
 #endif
 }