limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/dlpack.h"

#include <string>

#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"

            "names (",
            n->name(),
            "). This is a bug. Please file an issue at "
            "https://github.com/tensorflow/tensorflow/issues.");
      }
    }
  }

  // Unpack the results from grad_outputs_arg.
  TFOutputsFromOutputs(dy_arg, dy);
#endif  // defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
}

// TF_Session functions ----------------------------------------------

  // custom device.
  //
  // Many devices will want to simply return an "unimplemented" status
  // here. This is the default behavior if `pack` is null when passed to
  // TFE_RegisterCustomDevice.
  TFE_TensorHandle* (*pack)(TFE_Context* context, TFE_TensorHandle** handles,
                            int num_handles, TF_Status* s,
                            void* device_info) = nullptr;

        "//tensorflow/core/common_runtime/eager:tensor_handle",
        "@dlpack",
    ],
    alwayslink = 1,
)

tf_cuda_cc_test(
    name = "dlpack_test",
    size = "small",
    srcs = [
        "dlpack_test.cc",
    ],
    args = [],
    tags = [],
    deps = [
        ":c_api",
        ":dlpack",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",

tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS test $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_test
tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_build

tfrun ./ci/official/utilities/repack_libtensorflow.sh "$TFCI_OUTPUT_DIR" "$TFCI_LIB_SUFFIX"

if [[ "$TFCI_ARTIFACT_STAGING_GCS_ENABLE" == 1 ]]; then
  # Note: -n disables overwriting previously created files.

  if (use_function) {
    const char* fn_name = "test_fn";
    core::RefCountPtr<AbstractFunction> scoped_func;
    // Returning null tensors from a tf.function is not supported, so we keep
    // track of indices in the model's outputs are nullptr in this set.
    // The FunctionDef only outputs the non-null tensors. We later pad the
    // function op outputs to have nullptrs at the `null_indices`.

        TFE_DeleteTensorHandle(outputs[i]);
      }
    }
    return status.status;
  }

  tensorflow::Status Pack(absl::Span<ImmediateExecutionTensorHandle*> handles,
                          ImmediateExecutionTensorHandle** result) override {
    TF_Status status;
    *result = tensorflow::unwrap(device_.pack(context_,
                                              tensorflow::wrap(handles.data()),

      // One of the inputs we're trying to pack is on a custom device. We'll let
      // the first custom device we see handle all of the packing.
      auto* custom_device_handle =
          tensorflow::down_cast<tensorflow::CustomDeviceTensorHandle*>(
              unwrapped_handle);
      tensorflow::ImmediateExecutionTensorHandle* result;
      status->status = custom_device_handle->device()->Pack(

    "@onednn//:__subpackages__",
    "@org_sqlite//:__subpackages__",
    "@platforms//:__subpackages__",
    "@snappy//:__subpackages__",
    "@upb//:__subpackages__",
    "@zlib//:__subpackages__",
    "@dlpack//:__subpackages__",
    "@arm_neon_2_x86_sse//:__subpackages__",
    "@cpuinfo//:__subpackages__",
    "@ruy//:__subpackages__",
    "@XNNPACK//:__subpackages__",
    "@pthreadpool//:__subpackages__",

`tf.reverse_v2()` will remain until 1.0 final. * `tf.mul`, `tf.sub` and `tf.neg`
are deprecated in favor of `tf.multiply`, `tf.subtract` and `tf.negative`. *
`tf.pack` and `tf.unpack` are deprecated in favor of `tf.stack` and
`tf.unstack`. * `TensorArray.pack` and `TensorArray.unpack` are getting
deprecated in favor of `TensorArray.stack` and `TensorArray.unstack`. * The
following Python functions have had their arguments changed to use `axis` when