::xla::cpu_function_runtime::BufferInfo(::xla::cpu_function_runtime::EncodedBufferInfo{386ULL, 1U, ~0U}),
::xla::cpu_function_runtime::BufferInfo(::xla::cpu_function_runtime::EncodedBufferInfo{5ULL, ~0U, ~0U}),
::xla::cpu_function_runtime::BufferInfo(::xla::cpu_function_runtime::EncodedBufferInfo{386ULL, 2U, ~0U}),
::xla::cpu_function_runtime::BufferInfo(::xla::cpu_function_runtime::EncodedBufferInfo{5ULL, ~0U, ~0U}),

#include "tensorflow/compiler/tf2xla/tf2xla_util.h"
#include "xla/cpu_function_runtime.h"
#include "xla/service/compiler.h"
#include "xla/service/cpu/buffer_info_util.h"
#include "xla/shape_util.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/lib/core/errors.h"

namespace tensorflow {
namespace tfcompile {

namespace {

using BufferInfo = xla::cpu_function_runtime::BufferInfo;

bool IsAlpha(char c) {

#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/local_client.h"
#include "xla/executable_run_options.h"
#include "xla/hlo/ir/hlo_input_output_alias_config.h"
#include "xla/pjrt/pjrt_client.h"
#include "xla/pjrt/tf_pjrt_client.h"
#include "xla/service/executable.h"
#include "xla/service/gpu/gpu_executable_run_options.h"
#include "tensorflow/core/framework/function.h"

           "Minimum number of operators in an XLA compilation. Ignored for "
           "operators placed on an XLA device or operators explicitly marked "
           "for compilation."),
      Flag("tf_xla_max_cluster_size",
           &mark_for_compilation_flags->tf_xla_max_cluster_size,
           "Maximum number of operators in an XLA compilation."),
      Flag(
          "tf_xla_ops_to_cluster",

        "@local_xla//xla:xla_data_proto_cc",
        "@local_xla//xla/client:client_library",
        "@local_xla//xla/client:compile_only_client",
        "@local_xla//xla/client:xla_computation",
        "@local_xla//xla/service:compiler",
        "@local_xla//xla/service/cpu:buffer_info_util",
        "@local_xla//xla/service/cpu:cpu_compiler",
        "@local_xla//xla/stream_executor:platform_manager",
    ],
)

tf_cc_test(

        "@local_tsl//tsl/platform:protobuf",
        "@local_xla//xla/client:client_library",
        "@local_xla//xla/client:compile_only_client",
        "@local_xla//xla/service/cpu:cpu_compiler",
        "@local_xla//xla/service/cpu:cpu_transfer_manager",
        "@local_xla//xla/stream_executor",
        "@local_xla//xla/stream_executor/host:host_platform",
        "@local_xla//xla/stream_executor/host:host_platform_id",
    ],

  EXPECT_EQ(exec_args.size(), 2);

  std::shared_ptr<xla::Literal> literal1 = *exec_args[0]->ToLiteralSync();
  EXPECT_TRUE(xla::LiteralTestUtil::Equal(
      *literal1, xla::LiteralUtil::CreateR2<int32_t>({{1, 2, 3}})));

  std::shared_ptr<xla::Literal> literal2 = *exec_args[1]->ToLiteralSync();
  EXPECT_TRUE(xla::LiteralTestUtil::Equal(
      *literal2, xla::LiteralUtil::CreateR2<int32_t>({{4, 5, 6}})));
}

#include "tensorflow/compiler/jit/variable_info.h"
#include "tensorflow/compiler/jit/xla_tensor.h"
#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "xla/client/local_client.h"
#include "xla/pjrt/pjrt_client.h"
#include "xla/service/shaped_buffer.h"
#include "xla/stream_executor/device_memory_allocator.h"
#include "tensorflow/core/framework/allocation_description.pb.h"
#include "tensorflow/core/framework/tensor.h"

#include "tensorflow/compiler/tf2xla/const_analysis.h"
#include "tensorflow/compiler/tf2xla/resource_operation_table.h"
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/service/graphcycles/graphcycles.h"
#include "xla/statusor.h"
#include "xla/union_find.h"
#include "xla/util.h"
#include "tensorflow/core/common_runtime/function.h"
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/framework/attr_value.pb.h"

      $resource,
      (TF_SubOp
        (CreateTFReadVariableOp $src_op, $value, $resource),
        $value
      ),
      (CreateConstBoolAttrFalse)
    )
  >;

// This decomposition is only correct inside XLA as it ignores use_locking
// attribute.
def DecomposeResourceApplyGradientDescentOp :
  Pat<
    (TF_ResourceApplyGradientDescentOp:$src_op $resource, $alpha, $delta, BoolAttr:$_),
    (TF_AssignVariableOp
      $resource,