// on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created
  // on remote tasks will be considered stale and garbage collected after
  // `keep_alive_secs` of inactivity.
  virtual Status SetOrUpdateServerDef(const ServerDef& server_def,
                                      bool reset_context, int keep_alive_secs,

# limitations under the License.
# ==============================================================================
setup_file() {
    cd /tf/tensorflow
    bazel version  # Start the bazel server
}

# Do a bazel query specifically for the licenses checker. It searches for
# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then

  echo "Use 'devtoolset-9' to build a manylinux2014 compatible toolchain"
  exit 1
  ;;
esac

mkdir -p "${TARGET}"

mkdir -p ${TARGET}/usr/include

# Put the current kernel headers from ubuntu in place.
ln -s "/usr/include/linux" "${TARGET}/usr/include/linux"
ln -s "/usr/include/asm-generic" "${TARGET}/usr/include/asm-generic"
ln -s "/usr/include/aarch64-linux-gnu/asm" "${TARGET}/usr/include/asm"

  # TODO(gunan): Add sanity checks to loaded modules here.

  # Load first party dynamic kernels.
  _tf_dir = _os.path.dirname(_current_file_location)
  _kernel_dir = _os.path.join(_tf_dir, "core", "kernels")
  if _os.path.exists(_kernel_dir):
    _ll.load_library(_kernel_dir)

  # Load third party dynamic kernels.
  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")

        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
    ],
)

tf_custom_op_library(
    name = "test_op1.so",
    srcs = ["test_op1.cc"],
)

tf_kernel_library(
    name = "test_op_kernel",
    srcs = ["test_op.cc"],
    deps = [
        "//tensorflow/core:framework",
        "//tensorflow/core:lib",
    ],
    alwayslink = 1,
)

tf_cuda_cc_test(

  TF_DeleteStatus(s);
  return NULL;
}

// A compute function. This will never actually get called in this test, it's
// just nice to know that it compiles.
void compute(void* kernel, TF_OpKernelContext* ctx) {
  TF_Tensor* input;
  TF_Status* s = TF_NewStatus();
  TF_GetInput(ctx, 0, &input, s);
  TF_DeleteTensor(input);
  TF_DeleteStatus(s);
}

// Exercises tensorflow's C API.

    ```bash
    bazel test ${flags} //tensorflow/python/...
    ```

    For a single component e.g. softmax op:

    ```bash
    bazel test ${flags} tensorflow/python/kernel_tests/nn_ops:softmax_op_test
    ```

    For a single/parameterized test e.g. `test_capture_variables` in
    `tensorflow/python/saved_model/load_test.py`:

    (Requires `python>=3.7`)

    ```bash

diff --git a/sysdeps/ieee754/dbl-64/k_rem_pio2.c b/sysdeps/ieee754/dbl-64/k_rem_pio2.c
index fcf956a..e2c5d29 100644
--- a/sysdeps/ieee754/dbl-64/k_rem_pio2.c
+++ b/sysdeps/ieee754/dbl-64/k_rem_pio2.c
@@ -172,7 +172,8 @@ int __kernel_rem_pio2(double *x, double *y, int e0, int nx, int prec, const int3
 
     /* compute q[0],q[1],...q[jk] */
 	for (i=0;i<=jk;i++) {
-	    for(j=0,fw=0.0;j<=jx;j++) fw += x[j]*f[jx+i-j]; q[i] = fw;

// and return "non-ready" handles in `retvals`. Note that any handles contained
// in 'op' should not be mutated till the kernel execution actually finishes.
//
// For sync execution, if any of the inputs to `op` are not ready, this call
// will block till they become ready and then return when the kernel execution
// is done.
// TODO(agarwal): change num_retvals to int from int*.

tblib==2.0.0 \
    --hash=sha256:9100bfa016b047d5b980d66e7efed952fbd20bd85b56110aaf473cb97d18709a \
    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \