]),
)

# Check that c_api_no_xla does not depend on xla.
check_deps(
    name = "c_api_no_xla_check_deps",
    disallowed_deps = ["//tensorflow/compiler/jit:xla_kernel_creator"],
    deps = [":c_api_no_xla"],
)

tf_cuda_library(
    name = "c_api_no_xla",
    srcs = [
        "c_api.cc",
        "c_api_function.cc",
    ],
    hdrs = [
        "c_api.h",

                                     " but actual rank is ", rank);
    return;
  }

  if (num_dims == 0) {
    // Output shape is a scalar.
    return;
  }

  // Rank is greater than 0, so fill in the values, if known, and
  // -1 for unknown values.
  for (int i = 0; i < num_dims; ++i) {
    auto dim = ic->Dim(shape, i);
    int64_t value = -1;
    if (ic->ValueKnown(dim)) {

  ls -t *.whl | tail -n +2 | xargs rm
fi

# Check if size is too big. TFCI_WHL_SIZE_LIMIT is in find's format, which can be
# 'k' for kilobytes, 'M' for megabytes, or 'G' for gigabytes, and the + to indicate
# "anything greater than" is added by the script.
if [[ "$TFCI_WHL_SIZE_LIMIT_ENABLE" == "1" ]] && [[ -n "$(find . -iname "*.whl" -size "+$TFCI_WHL_SIZE_LIMIT")" ]]; then
  echo "Error: Generated wheel is too big! Limit is $TFCI_WHL_SIZE_LIMIT"

        `tf.acosh`, `tf.add`, `tf.as_string`, `tf.asin`, `tf.asinh`, `tf.atan`,
        `tf.atan2`, `tf.atanh`, `tf.cos`, `tf.cosh`, `tf.equal`, `tf.exp`,
        `tf.floor`, `tf.greater`, `tf.greater_equal`, `tf.less`,
        `tf.less_equal`, `tf.log`, `tf.logp1`, `tf.logical_and`,
        `tf.logical_not`, `tf.logical_or`, `tf.maximum`, `tf.minimum`,
        `tf.not_equal`, `tf.sin`, `tf.sinh`, `tf.tan`