#!/usr/bin/env bash

set -e
set -o pipefail

if [ -z "$PYTHON_BIN_PATH" ]; then
  PYTHON_BIN_PATH=$(which python3 || which python || true)
fi

# Set all env variables
CONFIGURE_DIR=$(dirname "$0")
"$PYTHON_BIN_PATH" "${CONFIGURE_DIR}/configure.py" "$@"

exports_files([
    "configure",
    "configure.py",
    "ACKNOWLEDGEMENTS",
    "LICENSE",

.DS_Store
.ipynb_checkpoints
node_modules
/.bazelrc.user
/.tf_configure.bazelrc
/xla_configure.bazelrc
/bazel-*
/bazel_pip
/tools/python_bin_path.sh
/tensorflow/tools/git/gen
/pip_test
/_python_build
*.pyc
__pycache__
*.swp
.vscode/
cmake_build/
tensorflow/contrib/cmake/_build/
.idea/**
/build/
[Bb]uild/
/build_output/
/tensorflow/core/util/version_info.cc
/tensorflow/python/framework/fast_tensor_util.cpp

  EXPECT_FALSE(executed);
  ASSERT_FALSE(TF_GetCode(status.get()) == TF_OK);

  // Custom devices can refuse to do type-based dispatch (as hcustom1 is
  // configured to do)
  matmul.reset(MatMulOp(context.get(), hcustom1.get(), hcpu.get()));
  num_retvals = 1;
  executed = false;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());
  EXPECT_FALSE(executed);

:: License for the specific language governing permissions and limitations under
:: the License.

@echo off

set configure_dir=%~dp0
set configure_dir=%configure_dir:~0,-1%
python "%configure_dir%\configure.py" %* || ( exit /b )

  """Helper function to print formatted help text for Bazel config options."""
  print('\t--config=%-12s\t# %s' % (name, help_text))


def configure_ios(environ_cp):
  """Configures TensorFlow for iOS builds."""
  if not is_macos():
    return
  if not get_var(environ_cp, 'TF_CONFIGURE_IOS', 'iOS', False):
    return
  for filepath in APPLE_BAZEL_FILES:

    TF_Status* status);

// Configure soft device placement policy for the eager executor. Note this
// policy is applied to any subsequent op executions.
TF_CAPI_EXPORT void TFE_ContextSetSoftDevicePlacement(TFE_Context* ctx,
                                                      unsigned char enable,
                                                      TF_Status* status);

/rpm-patch.sh "glibc.spec"
rm -f "glibc-2.17-317.el7.src.rpm" "glibc-2.17-c758a686.tar.gz" "glibc-2.17-c758a686-releng.tar.gz"
patch -p1 < /gcc9-fixups.patch
patch -p1 < /stringop_trunc.patch
cd ../glibc-build
../glibc-src/configure --prefix=/usr --disable-werror --enable-obsolete-rpc --disable-profile
make -j$(nproc)
make install DESTDIR=${TARGET}
cd ..

# Symlinks in the binary distribution are set up for installation in /usr, we

#      or tests passing incorrectly.
#    - Automatic LLVM updates are known to extend build time even with
#      the cache; this is unavoidable.
export TFCI=py311,linux_x86,public_cache,disk_cache

# Recommended: Configure Docker. (Linux only)
#
#   TF uses hub.docker.com/r/tensorflow/build containers for CI,
#   and scripts on Linux create a persistent container called "tf"
#   which mounts your TensorFlow directory into the container.
#

build:elinux_armhf --cpu=armhf
build:elinux_armhf --copt -mfp16-format=ieee

# Config-specific options should come above this line.

# Load rc file written by ./configure.
try-import %workspace%/.tf_configure.bazelrc
try-import %workspace%/xla_configure.bazelrc

# Load rc file with user-specific options.
try-import %workspace%/.bazelrc.user

# Here are bazelrc configs for release builds
# Build TensorFlow v2.