#include <unordered_set>
#include <utility>
#include <vector>

#include "absl/algorithm/container.h"
#include "absl/container/flat_hash_map.h"
#include "absl/container/flat_hash_set.h"
#include "absl/log/log.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "absl/types/span.h"
#include "llvm/ADT/SmallVector.h"

    for (auto output : forward_outputs_) {
      if (output) {
        output->Ref();
      }
    }
  }

  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    AbstractTensorHandle* upstream_grad = grad_outputs[0];
    AbstractTensorHandle* activations = forward_outputs_[0];

#include "tensorflow/compiler/mlir/tensorflow_to_stablehlo/python/pywrap_tensorflow_to_stablehlo_lib.h"

#include <string>
#include <vector>

#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "llvm/Support/ToolOutputFile.h"
#include "llvm/Support/raw_ostream.h"
#include "mlir/Bytecode/BytecodeWriter.h"  // from @llvm-project

      return absl::OkStatus();

    case DLDataTypeCode::kDLUInt:
      switch (dtype.bits) {
        case 8:
          *tf_dtype = TF_DataType::TF_UINT8;
          return absl::OkStatus();
        case 16:
          *tf_dtype = TF_DataType::TF_UINT16;
          return absl::OkStatus();
        case 32:
          *tf_dtype = TF_DataType::TF_UINT32;
          return absl::OkStatus();
        case 64:

    VLOG(2) << "CopyCPUTensorToDevice empty tensor";
    done(absl::OkStatus());
    return;
  }

  absl::StatusOr<xla::PjRtClient*> pjrt_client =
      GetOrCreatePjRtClient(DeviceType(device->device_type()));
  if (!pjrt_client.ok()) {
    done(pjrt_client.status());
    return;
  }
  absl::StatusOr<std::unique_ptr<xla::PjRtBuffer>> buffer_or =

#include <string>
#include <unordered_set>
#include <vector>

#include "absl/base/nullability.h"
#include "absl/container/flat_hash_map.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/string_view.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project

// output_arrays is specified.
absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> LoadFromGraphdefOrMlirSource(
    const std::string& input_filename, bool input_mlir,
    bool use_splatted_constant, const std::vector<std::string>& extra_tf_opdefs,
    const GraphImportConfig& specs, absl::string_view debug_info_file,
    absl::string_view input_arrays, absl::string_view input_dtypes,

// for debugging.
inline constexpr absl::string_view kTfQuantPtqPreCalibrationStepName =
    "tf_quant_ptq_pre_calibration";
inline constexpr absl::string_view kTfQuantPtqPostCalibrationStepName =
    "tf_quant_ptq_post_calibration";
inline constexpr absl::string_view kTfQuantQatStepName = "tf_quant_qat";
inline constexpr absl::string_view kTfQuantPtqDynamicRangeStepName =
    "tf_quant_ptq_dynamic_range";

        "@com_google_absl//absl/algorithm:container",
        "@com_google_absl//absl/base:core_headers",
        "@com_google_absl//absl/container:flat_hash_map",
        "@com_google_absl//absl/container:flat_hash_set",
        "@com_google_absl//absl/container:inlined_vector",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/synchronization",
        "@llvm-project//llvm:Support",

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

#include "absl/algorithm/container.h"
#include "absl/status/status.h"
#include "absl/strings/str_split.h"
#include "absl/strings/string_view.h"
#include "tensorflow/compiler/jit/device_executable_persistor.h"
#include "tensorflow/compiler/jit/flags.h"