set -euxo pipefail

# Run this from inside the tensorflow github directory.
# Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file"
# Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl"
# 
# This will create a venv with that wheel file installed in it, and a symlink
# in ./venv_and_symlink_name/tensorflow to ./tensorflow. We use this for the
# "pip" tests.

python -m venv /$1
mkdir -p $1
rm -f ./$1/tensorflow

          # Publish the results to enable scorecard badges. For more details, see
          # https://github.com/ossf/scorecard-action#publishing-results.
          # For private repositories, `publish_results` will automatically be set to `false`,
          # regardless of the value entered here.
          publish_results: true

      # Upload the results as artifacts (optional).
      - name: "Upload artifact"

// `src_inputs[i]` will have that input replaced with `dst_inputs[i]`.  `prefix`
// will be prepended to copied node names. `control_deps` are nodes in
// `dst_graph` that the copied `src_graph` nodes will have control dependencies
// on. `return_nodes` are nodes in `src_graph`, and the new corresponding nodes
// in `dst_graph` will be returned. `return_nodes` must be non-null.

#include <stdlib.h>
#include <string.h>

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/c/tf_status.h"

// Implementation of a filesystem for POSIX environments.
// This filesystem will support `file://` and empty (local) URI schemes.

static void* plugin_memory_allocate(size_t size) { return calloc(1, size); }
static void plugin_memory_free(void* ptr) { free(ptr); }

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After
the change has been submitted internally, your pull request will be merged
automatically on GitHub.

#include "tensorflow/core/platform/logging.h"

namespace tensorflow {

namespace {

// Managing context for the DLManagedTensor, will manage the lifetime of
// DLManagedTensor. When calling DLManagedTensor::deleter, it will notify the
// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;

    cat $BATS_TEST_TMPDIR/actual_missing_licenses
  fi

  # Fail if either of the two "extras" or "missing" lists are present. If so,
  # then the user will see the above error messages.
  [[ ! -s $BATS_TEST_TMPDIR/actual_extra_licenses ]] && [[ ! -s $BATS_TEST_TMPDIR/actual_missing_licenses ]]
}

@test "Pip package generated license includes all dependencies' licenses" {

# > TF's gen_api_init_files has a genrule to run the core TensorFlow code
# > on the host machine. If we don't have --distinct_host_configuration=false,
# > the core TensorFlow code will be built once for the host and once for the
# > target platform.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false

    --hash=sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519 \
    --hash=sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561
    # via requests
dill==0.3.7 \
    --hash=sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e \
    --hash=sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03
    # via -r requirements.in
dm-tree==0.1.8 \

#      Ex. no_upload      -- Disable all uploads, usually for temporary CI issues

# Recommended: use a local+remote cache.
#
#   Bazel will cache your builds in tensorflow/build_output/cache,
#   and will also try using public build cache results to speed up
#   your builds. This usually saves a lot of time, especially when
#   re-running tests. However, note that:
#