return client_->Load(serialized_executable, build_options);
}

void XlaDeviceCompilerClient::WaitForProgramsToFinish() {
  if (client_ == nullptr) return;

  for (auto* executor : client_->backend().stream_executors()) {
    bool ok = executor->SynchronizeAllActivity();
    if (!ok) {
      LOG(ERROR) << "Error synchronizing activity while waiting for all "
                    "programs to complete";
    }
  }
}

            "//tensorflow/core:portable_tensorflow_lib_lite",
        ],
        "//conditions:default": [
            ":tf_tensor",
            "//tensorflow/c/experimental/stream_executor",
            "//tensorflow/c/experimental/stream_executor:stream_executor_internal",
            "//tensorflow/core:framework",
            "//tensorflow/core:framework_lite",

        "@llvm-project//mlir:IR",
        "@llvm-project//mlir:Support",
        "@local_xla//xla:shape_util",
        "@local_xla//xla/mlir_hlo",
        "@local_xla//xla/stream_executor/tpu:c_api_conversions",
        "@local_xla//xla/stream_executor/tpu:tpu_api",
        "@local_xla//xla/translate/mhlo_to_hlo:type_to_shape",
    ],
)

cc_library(
    name = "tf_saved_model_asset_sinking_pass",

#include "tensorflow/compiler/jit/xla_device.h"
#include "tensorflow/compiler/jit/xla_device_ops.h"
#include "tensorflow/compiler/tf2xla/layout_util.h"
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/common_runtime/device_factory.h"
#include "tensorflow/core/lib/core/status.h"

namespace tensorflow {
using tensorflow::IdentityShapeRepresentationFn;

        [],
        otherwise = [
            "@local_xla//xla/stream_executor/cuda:all_runtime",
            "@local_xla//xla/stream_executor/cuda:cuda_driver",
            "@local_xla//xla/stream_executor/cuda:cuda_platform",
            "@local_xla//xla/stream_executor/cuda:cudnn_plugin",
            "@local_xla//xla/stream_executor/cuda:cufft_plugin",
            "@local_xla//xla/stream_executor:cuda_platform",

#include "tensorflow/compiler/jit/device_compiler.h"
#include "tensorflow/compiler/jit/xla_device.h"
#include "tensorflow/compiler/jit/xla_launch_util.h"
#include "tensorflow/compiler/jit/xla_platform_info.h"
#include "xla/stream_executor/integrations/tf_allocator_adapter.h"
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/tensor.h"

#include <optional>
#include <string>

#include "tensorflow/compiler/jit/device_compiler.h"
#include "tensorflow/compiler/jit/pjrt_base_device.h"
#include "tensorflow/compiler/jit/xla_device.h"
#include "xla/stream_executor/integrations/tf_allocator_adapter.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {

// Holds some information about the platform on which an

        "@llvm-project//mlir:Pass",
        "@local_tsl//tsl/platform:statusor",
        "@local_xla//xla:shape_util",
        "@local_xla//xla/client:client_library",
        "@local_xla//xla/stream_executor",
    ],
)

cc_library(
    name = "clustering_bridge_passes",
    srcs = ["clustering_bridge_passes.cc"],
    hdrs = ["clustering_bridge_passes.h"],
    deps = [

  if (it != state.allocators_.end()) {
    return it->second.get();
  }

  std::unique_ptr<XlaDeviceAllocator> alloc =
      std::make_unique<XlaDeviceAllocator>(
          backend->stream_executors()[device_ordinal]);
  XlaDeviceAllocator* alloc_ptr = alloc.get();
  state.allocators_[{backend, device_ordinal}] = std::move(alloc);
  return alloc_ptr;
}

namespace {

#include "tensorflow/compiler/tf2xla/layout_util.h"
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/client_library.h"
#include "xla/shape.h"
#include "xla/stream_executor/platform_manager.h"
#include "xla/translate/mhlo_to_hlo/type_to_shape.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"