}
    TF_DeleteShapeAndTypeList(input_shapes);
    TF_DeleteShapeAndTypeList(output_shapes);
  }

  absl::optional<std::vector<int64_t>> make_shape(
      std::vector<int64_t>&& dims) const {
    return absl::make_optional(dims);
  }

  absl::optional<std::vector<int64_t>> unknown_shape() const {
    return absl::nullopt;
  }

  static constexpr int64_t kUnknownDim =

#endif
  } else {
    status->status = tensorflow::errors::InvalidArgument(
        "Unsupported Device Type for dlpack");
  }

  return ctx;
}

// Converts DLDevice to TF device name.
absl::optional<std::string> DeviceNameFromDlContext(const DLDevice& ctx,
                                                    TF_Status* status) {
  switch (ctx.device_type) {
    case DLDeviceType::kDLCPU:
      return "CPU:0";

#ifndef TENSORFLOW_C_EAGER_PARALLEL_DEVICE_PARALLEL_DEVICE_LIB_H_
#define TENSORFLOW_C_EAGER_PARALLEL_DEVICE_PARALLEL_DEVICE_LIB_H_

#include <memory>
#include <optional>
#include <string>
#include <utility>
#include <vector>

#include "absl/types/optional.h"
#include "absl/types/span.h"
#include "absl/types/variant.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"

                 TF_Message(first_bad_status.get()));
  }
}

absl::optional<std::vector<std::unique_ptr<ParallelTensor>>>
ParallelDevice::Join(
    const std::vector<PartialTensorShape>& expected_output_shapes,
    TF_Status* status) const {
  absl::optional<std::vector<std::unique_ptr<ParallelTensor>>> result;
  // Compute per-device per-output tensors

#ifndef TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_CONTEXT_H_
#define TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_CONTEXT_H_

#include <functional>
#include <map>
#include <memory>
#include <vector>

#include "absl/types/optional.h"
#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/immediate_execution_distributed_manager.h"
#include "tensorflow/c/eager/immediate_execution_operation.h"

};

absl::optional<std::vector<MaybeParallelTensorOwned>> ExecuteWithSpecialOps(
    const ParallelDevice& parallel_device,
    const std::string& parallel_device_name, TFE_Context* context,
    std::vector<MaybeParallelTensorUnowned> inputs, const char* operation_name,
    const TFE_OpAttrs* attributes, int expected_max_outputs,
    TF_Status* status) {
  absl::optional<std::vector<MaybeParallelTensorOwned>> result;

    ] + if_not_mobile([
        "//tensorflow/core/kernels:tensor_list",
        "//tensorflow/core/kernels:tensor_list_util",
        "//tensorflow/core/kernels:variant_ops_util",
        "//tensorflow/core/kernels/data:optional_ops_util",
        "//tensorflow/core/platform:abi",
    ]),
    alwayslink = 1,
)

tf_cuda_library(
    name = "ops",
    srcs = [
        "ops.cc",
    ],
    hdrs = [

}

// Validates the read only memory region operations given by the plugin.
static Status ValidateHelper(const TF_ReadOnlyMemoryRegionOps* ops) {
  if (ops == nullptr) {
    // read only memory region support is always optional
    return OkStatus();
  }

  if (ops->cleanup == nullptr)
    return errors::FailedPrecondition(
        "Trying to register filesystem without `cleanup` operation on read "
        "only memory regions");

        "//tensorflow/core:framework",
        "//tensorflow/core:lib",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core/util:managed_stack_trace",
        "@com_google_absl//absl/types:optional",
        "@com_google_absl//absl/types:span",
    ],
)

cc_library(
    name = "abstract_context",
    hdrs = ["abstract_context.h"],
    visibility = [
        "//tensorflow:internal",
    ],

  //
  // Does not include the shape and dtype of the tensor (which is generally
  // appended later), but should include any information specific to this custom
  // device which would be useful for debugging.
  //
  // Optional. If null, defaults to resolving the TFE_TensorHandle into a
  // TF_Tensor and summarizing that.
  TF_Buffer* (*summarize)(void* data, TF_Status* status) = nullptr;
} TFE_CustomDeviceTensorHandle;