bool enabled_for_all_;

    // If true, enable Device API (PjRt) for TF GPU device. This is a helper
    // flag so that individual tests can turn on PjRt for GPU specifically.
    // Once the rollout to GPU is complete, this flag can be deprecated.
    bool enabled_for_gpu_;

   private:
    // Devices for which using Device API (PjRt) is allowed in the XlaLaunch op.
    // This can only be modified programmatically.

#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "tensorflow/compiler/jit/pjrt_tensor_buffer_util.h"
#include "xla/pjrt/c/pjrt_c_api.h"
#include "xla/pjrt/pjrt_c_api_client.h"
#include "xla/pjrt/pjrt_client.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/types.h"

#ifndef TENSORFLOW_C_EXPERIMENTAL_NEXT_PLUGGABLE_DEVICE_TENSOR_PJRT_BUFFER_UTIL_H_
#define TENSORFLOW_C_EXPERIMENTAL_NEXT_PLUGGABLE_DEVICE_TENSOR_PJRT_BUFFER_UTIL_H_

#include "xla/pjrt/c/pjrt_c_api.h"
#include "xla/pjrt/pjrt_c_api_client.h"
#include "tensorflow/core/framework/tensor.h"

namespace tensorflow {

absl::StatusOr<PJRT_Buffer*> GetPjRtCBufferFromTensor(const Tensor* tensor);

#include "tensorflow/c/tf_tensor_internal.h"
#include "tensorflow/compiler/jit/variable_info.h"
#include "tensorflow/compiler/jit/variable_info_util.h"
#include "xla/pjrt/c/pjrt_c_api.h"
#include "xla/pjrt/c/pjrt_c_api_helpers.h"
#include "xla/pjrt/pjrt_c_api_client.h"
#include "xla/pjrt/pjrt_client.h"
#include "xla/tsl/distributed_runtime/coordination/coordination_service_agent.h"

            "If true, uses Device API (PjRt) for single device compilation and "
            "execution of functions marked for JIT compilation i.e. "
            "jit_compile=True. Defaults to false."),
       Flag("tf_xla_use_device_api_for_compile_on_demand",
            &ops_flags->tf_xla_use_device_api.enabled_for_compile_on_demand_,
            "If true, uses Device API (PjRt) for compiling and executing ops "

#include "tensorflow/compiler/tf2xla/shape_util.h"
#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "xla/client/local_client.h"
#include "xla/pjrt/pjrt_client.h"
#include "xla/pjrt/pjrt_future.h"
#include "xla/pjrt/pjrt_stream_executor_client.h"
#include "xla/pjrt/tracked_device_buffer.h"
#include "xla/shape_util.h"
#include "xla/status_macros.h"
#include "xla/stream_executor/platform_manager.h"

    VLOG(2) << "Compiling using PJRT";
    Status status = CompileToPjRtLoadedExecutable(
        *ctx, platform_info_, function_, xla_compiler_args,
        DeviceCompileMode::kStrict, has_ref_vars_,
        /*may_alias_resource_update=*/true, &compilation_result, &pjrt_client,
        &pjrt_executable);
    OP_REQUIRES_OK_ASYNC(ctx, status, done);

    VLOG(2) << "Compiled using PJRT: " << status;

#include "tensorflow/compiler/jit/xla_compile_util.h"
#include "tensorflow/compiler/jit/xla_device_compiler_client.h"
#include "xla/client/client_library.h"
#include "xla/client/local_client.h"
#include "xla/pjrt/pjrt_client.h"
#include "xla/service/compiler.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/op_kernel.h"

        "@llvm-project//mlir:IR",
    ],
)

cc_library(
    name = "tpu_passes",
    hdrs = ["transforms/tpu_passes.h"],
    visibility = [":friends"] + if_google([
        "//learning/brain/tfrt/ifrt/pjrt/__subpackages__",
        "//learning/serving/servables/tfrt:__subpackages__",
    ]),
    deps = [
        ":fallback_converter",
        ":tfrt_compile_options",
        "@llvm-project//llvm:Support",

        "@local_xla//xla:shape_util",
        "@local_xla//xla/mlir_hlo",
        "@local_xla//xla/pjrt:pjrt_client",
        "@local_xla//xla/pjrt:pjrt_executable",
        "@local_xla//xla/pjrt/cpu:cpu_client",
        "@local_xla//xla/tests:literal_test_util",
        "@stablehlo//:chlo_ops",
    ],
)

tf_cc_test(
    name = "legalize_tf_quant_test",