tensorflow: internal compiler error: in assign_temp, at function.c:968

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System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 16.04

• Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:

• TensorFlow installed from (source or binary): source

• TensorFlow version: 2.0

• Python version: 3.6

• Installed using virtualenv? pip? conda?:

• Bazel version (if compiling from source): Build label: 0.26.1

• GCC/Compiler version (if compiling from source): gcc (Ubuntu 5.5.0-12ubuntu1~16.04) 5.5.0 20171010 and gcc (Ubuntu 7.4.0-1ubuntu1~16.04~ppa1) 7.4.0

• CUDA/cuDNN version: off

• GPU model and memory: off

Describe the problem

ERROR: /home/ubuntu/tensorflow/tensorflow/compiler/mlir/xla/BUILD:226:1: C++ compilation of rule '//tensorflow/compiler/mlir/xla:hlo' failed (Exit 1)
tensorflow/compiler/mlir/xla/ir/hlo_ops.cc: In function 'mlir::Type {anonymous}::GetBroadcastType(mlir::Builder*, mlir::Type, mlir::Type, mlir::Type, mlir::DenseIntElementsAttr)':
tensorflow/compiler/mlir/xla/ir/hlo_ops.cc:622:23: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for (int i = 0; i < shape_x.size(); i++) {
                     ~~^~~~~~~~~~~~~~~~
In file included from ./tensorflow/compiler/mlir/xla/ir/hlo_ops.h:22:0,
                 from tensorflow/compiler/mlir/xla/ir/hlo_ops.cc:18:
external/local_config_mlir/include/mlir/IR/Attributes.h: In member function 'T mlir::DenseElementsAttr::getValue(llvm::ArrayRef<long unsigned int>) const [with T = mlir::IntegerAttr]':
external/local_config_mlir/include/mlir/IR/Attributes.h:783:20: internal compiler error: in assign_temp, at function.c:968
     auto castFn = [](Attribute attr) { return attr.template cast<T>(); };
                    ^
Please submit a full bug report,

Provide the exact sequence of commands / steps that you executed before running into the problem

$ bazel build --config=opt  //tensorflow/tools/pip_package:build_pip_package

Any other info / logs Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.