tensorflow: Error trying to build for macOS with GPU support: "no toolchain corresponding to 'local_darwin' found for cpu 'darwin' "

System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): N/A
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): macOS ‘High Sierra’ Version 10.13.4 (17E202)
• TensorFlow installed from (source or binary): source
• TensorFlow version (use command below): N/A, attempting to compile at e365deab1333005c8aa186632f160c1bfd4485f8 with minimal local changes (see below)
• Python version: 2.7.15
• Bazel version (if compiling from source): 0.13.1-homebrew
• GCC/Compiler version (if compiling from source): Apple LLVM version 8.1.0 (clang-802.0.42)
• CUDA/cuDNN version: cuda_9.2.64_mac with cuda_9.2.64.1_mac, cudnn-9.2-osx-x64-v7.1
• GPU model and memory: NVIDIA GeForce GT 750M with 2 GB device memory, CUDA Compute Capability 3.0
• Exact command to reproduce:

./configure
bazel build --config=opt --config=cuda --save_temps --explain=explain.txt --verbose_explanations --verbose_failures --linkopt=-Wl,-rpath,/usr/local/cuda/lib //tensorflow/tools/pip_package:build_pip_package

Describe the problem

This is a re-occurrence of #9072, except that the solutions mentioned there (not using clang as the CUDA compiler, using CommandLineTools) do not resolve the problem.

To configure, I selected the following:

You have bazel 0.13.1-homebrew installed.
Please specify the location of python. [Default is /usr/local/opt/python@2/bin/python2.7]: 


Found possible Python library paths:
  /usr/local/Cellar/python@2/2.7.15/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages
Please input the desired Python library path to use.  Default is [/usr/local/Cellar/python@2/2.7.15/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages]

Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]:  
Google Cloud Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Hadoop File System support? [Y/n]: 
Hadoop File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Amazon S3 File System support? [Y/n]: 
Amazon S3 File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Apache Kafka Platform support? [Y/n]: 
Apache Kafka Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with XLA JIT support? [y/N]: 
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with GDR support? [y/N]: 
No GDR support will be enabled for TensorFlow.

Do you wish to build TensorFlow with VERBS support? [y/N]: 
No VERBS support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: 
No OpenCL SYCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: y
CUDA support will be enabled for TensorFlow.

Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 9.0]: 9.2


Please specify the location where CUDA 9.2 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: 


Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7.0]: 7.1.4


Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:


Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 3.5,5.2]3.0


Do you want to use clang as CUDA compiler? [y/N]: 
nvcc will be used as CUDA compiler.

Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]: 


Do you wish to build TensorFlow with MPI support? [y/N]: 
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]: 


Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: 
Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See tools/bazel.rc for more details.
	--config=mkl         	# Build with MKL support.
	--config=monolithic  	# Config for mostly static monolithic build.
Configuration finished

To build, I try:

bazel build --config=opt --config=cuda --save_temps --explain=explain.txt --verbose_explanations --verbose_failures --linkopt=-Wl,-rpath,/usr/local/cuda/lib //tensorflow/tools/pip_package:build_pip_package

However, this results in the error:

Starting local Bazel server and connecting to it...
............
WARNING: The following configs were expanded more than once: [cuda]. For repeatable flags, repeats are counted twice and may lead to unexpected behavior.
ERROR: Inconsistent crosstool configuration; no toolchain corresponding to 'local_darwin' found for cpu 'darwin'
INFO: Elapsed time: 0.903s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (2 packages loaded)

The output of xcode-select -p is:

/Library/Developer/CommandLineTools

The output of /usr/bin/gcc --version is:

Configured with: --prefix=/Library/Developer/CommandLineTools/usr --with-gxx-include-dir=/usr/include/c++/4.2.1
Apple LLVM version 8.1.0 (clang-802.0.42)
Target: x86_64-apple-darwin17.5.0
Thread model: posix
InstalledDir: /Library/Developer/CommandLineTools/usr/bin

I am able to build & run the ‘deviceQuery’ CUDA SDK sample without issue.

Source code / logs

The only local changes from e365deab1333005c8aa186632f160c1bfd4485f8 I have are:

diff --git a/tensorflow/core/kernels/concat_lib_gpu_impl.cu.cc b/tensorflow/core/kernels/concat_lib_gpu_impl.cu.cc
index a561d918bd..46c91b4511 100644
--- a/tensorflow/core/kernels/concat_lib_gpu_impl.cu.cc
+++ b/tensorflow/core/kernels/concat_lib_gpu_impl.cu.cc
@@ -69,7 +69,7 @@ __global__ void concat_variable_kernel(
   IntType num_inputs = input_ptr_data.size;
 
   // verbose declaration needed due to template
-  extern __shared__ __align__(sizeof(T)) unsigned char smem[];
+  extern __shared__ __align__(sizeof(T) > 16 ? sizeof(T) : 16) unsigned char smem[];
   IntType* smem_col_scan = reinterpret_cast<IntType*>(smem);
 
   if (useSmem) {
diff --git a/tensorflow/core/kernels/depthwise_conv_op_gpu.cu.cc b/tensorflow/core/kernels/depthwise_conv_op_gpu.cu.cc
index 5390222b3a..fcbd733614 100644
--- a/tensorflow/core/kernels/depthwise_conv_op_gpu.cu.cc
+++ b/tensorflow/core/kernels/depthwise_conv_op_gpu.cu.cc
@@ -172,7 +172,7 @@ __global__ __launch_bounds__(1024, 2) void DepthwiseConv2dGPUKernelNHWCSmall(
     const DepthwiseArgs args, const T* input, const T* filter, T* output) {
   assert(CanLaunchDepthwiseConv2dGPUSmall(args));
   // Holds block plus halo and filter data for blockDim.x depths.
-  extern __shared__ __align__(sizeof(T)) unsigned char shared_memory[];
+  extern __shared__ __align__(sizeof(T) > 16 ? sizeof(T) : 16) unsigned char shared_memory[];
   T* const shared_data = reinterpret_cast<T*>(shared_memory);
 
   const int num_batches = args.batch;
@@ -452,7 +452,7 @@ __global__ __launch_bounds__(1024, 2) void DepthwiseConv2dGPUKernelNCHWSmall(
     const DepthwiseArgs args, const T* input, const T* filter, T* output) {
   assert(CanLaunchDepthwiseConv2dGPUSmall(args));
   // Holds block plus halo and filter data for blockDim.z depths.
-  extern __shared__ __align__(sizeof(T)) unsigned char shared_memory[];
+  extern __shared__ __align__(sizeof(T) > 16 ? sizeof(T) : 16) unsigned char shared_memory[];
   T* const shared_data = reinterpret_cast<T*>(shared_memory);
 
   const int num_batches = args.batch;
@@ -1118,7 +1118,7 @@ __launch_bounds__(1024, 2) void DepthwiseConv2dBackpropFilterGPUKernelNHWCSmall(
     const DepthwiseArgs args, const T* output, const T* input, T* filter) {
   assert(CanLaunchDepthwiseConv2dBackpropFilterGPUSmall(args, blockDim.z));
   // Holds block plus halo and filter data for blockDim.x depths.
-  extern __shared__ __align__(sizeof(T)) unsigned char shared_memory[];
+  extern __shared__ __align__(sizeof(T) > 16 ? sizeof(T) : 16) unsigned char shared_memory[];
   T* const shared_data = reinterpret_cast<T*>(shared_memory);
 
   const int num_batches = args.batch;
@@ -1388,7 +1388,7 @@ __launch_bounds__(1024, 2) void DepthwiseConv2dBackpropFilterGPUKernelNCHWSmall(
     const DepthwiseArgs args, const T* output, const T* input, T* filter) {
   assert(CanLaunchDepthwiseConv2dBackpropFilterGPUSmall(args, blockDim.x));
   // Holds block plus halo and filter data for blockDim.z depths.
-  extern __shared__ __align__(sizeof(T)) unsigned char shared_memory[];
+  extern __shared__ __align__(sizeof(T) > 16 ? sizeof(T) : 16) unsigned char shared_memory[];
   T* const shared_data = reinterpret_cast<T*>(shared_memory);
 
   const int num_batches = args.batch;
diff --git a/tensorflow/core/kernels/split_lib_gpu.cu.cc b/tensorflow/core/kernels/split_lib_gpu.cu.cc
index 393818730b..58a1294005 100644
--- a/tensorflow/core/kernels/split_lib_gpu.cu.cc
+++ b/tensorflow/core/kernels/split_lib_gpu.cu.cc
@@ -121,7 +121,7 @@ __global__ void split_v_kernel(const T* input_ptr,
   int num_outputs = output_ptr_data.size;
 
   // verbose declaration needed due to template
-  extern __shared__ __align__(sizeof(T)) unsigned char smem[];
+  extern __shared__ __align__(sizeof(T) > 16 ? sizeof(T) : 16) unsigned char smem[];
   IntType* smem_col_scan = reinterpret_cast<IntType*>(smem);
 
   if (useSmem) {
diff --git a/third_party/gpus/cuda/BUILD.tpl b/third_party/gpus/cuda/BUILD.tpl
index 2a37c65bc7..43446dd99b 100644
--- a/third_party/gpus/cuda/BUILD.tpl
+++ b/third_party/gpus/cuda/BUILD.tpl
@@ -110,7 +110,7 @@ cc_library(
         ".",
         "cuda/include",
     ],
-    linkopts = ["-lgomp"],
+    #linkopts = ["-lgomp"],
     linkstatic = 1,
     visibility = ["//visibility:public"],
 )
diff --git a/third_party/toolchains/gpus/cuda/BUILD b/third_party/toolchains/gpus/cuda/BUILD
index 4cb8380938..d025c4f3aa 100644
--- a/third_party/toolchains/gpus/cuda/BUILD
+++ b/third_party/toolchains/gpus/cuda/BUILD
@@ -115,7 +115,7 @@ cc_library(
         ".",
         "cuda/include",
     ],
-    linkopts = ["-lgomp"],
+    #linkopts = ["-lgomp"],
     linkstatic = 1,
     visibility = ["//visibility:public"],
 )