*   Conduct which could reasonably be considered inappropriate for the forum in
    which it occurs.

All TensorFlow forums and spaces are meant for professional interactions, and any behavior which could reasonably be considered inappropriate in a professional setting is unacceptable.


## Our Responsibilities

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#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.

setattr(_current_module, "keras", _KerasLazyLoader(globals()))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__
if _tf_uses_legacy_keras:
  _module_dir = _module_util.get_parent_dir_for_name("tf_keras.api._v2.keras")
else:
  _module_dir = _module_util.get_parent_dir_for_name("keras.api._v2.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__

# See the License for the specific language governing permissions and
# 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

    DCHECK(upstream_grad);

    // Recover data format from forward pass for gradient.
    std::string data_format;
    TF_RETURN_IF_ERROR(forward_attrs_.Get("data_format", &data_format));

    // Grad for A
    grad_inputs[0] = upstream_grad;
    grad_inputs[0]->Ref();

    // Grad for bias
    std::string name = "bias_add_grad";

  if (!TF_Run_Inputs(c_inputs, &input_pairs, status)) return;
  for (int i = 0; i < ninputs; ++i) {
    input_pairs[i].first = c_input_names[i];
  }
  std::vector<string> output_names(noutputs);
  for (int i = 0; i < noutputs; ++i) {
    output_names[i] = c_output_names[i];
  }
  std::vector<string> target_oper_names(ntargets);
  for (int i = 0; i < ntargets; ++i) {
    target_oper_names[i] = c_target_oper_names[i];

                                      bool clear_existing_contexts = false) = 0;

  // Initializes context for the local worker and no contexts will be created
  // for remote workers. Currently this only works for resetting context.
  // TODO(b/289445025): Consider removing this when we find a proper fix.
  virtual Status InitializeLocalOnlyContext(const ServerDef& server_def,

# > 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

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
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"
# 

      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
        with:
          ref: 'nightly'
      - name: Checkout repository for releases (skipped for nightly)
        if: ${{ github.event_name == 'push' }}