@embedded_jdk//
^//$
@ruy//
EOF

  license_query "attr('licenses', 'notice', deps($BUILD_TARGET))" > $BATS_TEST_TMPDIR/expected_licenses
  license_query "deps($LICENSES_TARGET)" > $BATS_TEST_TMPDIR/actual_licenses

  # Column 1 is left only, Column 2 is right only, Column 3 is shared lines
  # Select lines unique to actual_licenses, i.e. extra licenses.

# downloaded TF as a zip archive).
export TFCI_GIT_DIR=$(cd $(dirname "$0"); realpath ../../)
cd "$TFCI_GIT_DIR"

# "TFCI" may optionally be set to the name of an env-type file with TFCI
# variables in it, OR may be left empty if the user has already exported the
# relevant variables in their environment. Because of 'set -o allexport' above
# (which is equivalent to "set -a"), every variable in the file is exported
# for other files to use.
#

  int64_t* p = storage;
  int storage_left = storage_size;
  for (int i = 0; i < len; ++i) {
    // shapes[i].dims() == -1 for shapes with an unknown rank.
    int64_t n = shapes[i].dims();
    num_dims[i] = n;
    dims[i] = p;
    if (n < 0) {
      continue;
    }
    if (storage_left < n) {
      status->status = InvalidArgument(

// "vspace" because a subset of these are related to a vector space, such as
// adding gradients, getting zeroes, etc. Currently cannot be implemented
// without using tensorflow python code, hence left unspecified here.
//
// Gradient is the type returned by gradient functions. In Python TF it's either
// Tensor or IndexedSlices or None, which here we map to nullptr. Gradients need

    *   Various random number generation improvements:
    *   Add a fast path for default `random_uniform`
    *   `random_seed` documentation improvement.
    *   `RandomBinomial` broadcasts and appends the sample shape to the left
        rather than the right.
    *   Added `tf.random.stateless_binomial`, `tf.random.stateless_gamma`,
        `tf.random.stateless_poisson`
    *   `tf.random.stateless_uniform` now supports unbounded sampling of `int`