#include "tensorflow/core/runtime_fallback/util/fallback_test_util.h"
#include "tensorflow/core/tfrt/utils/fallback_tensor.h"
#include "tfrt/bef/bef_buffer.h"  // from @tf_runtime
#include "tfrt/bef_executor/bef_file.h"  // from @tf_runtime
#include "tfrt/core_runtime/core_runtime.h"  // from @tf_runtime
#include "tfrt/host_context/async_value.h"  // from @tf_runtime
#include "tfrt/host_context/async_value_ref.h"  // from @tf_runtime

#include "tensorflow/core/tfrt/utils/fallback_tensor.h"
#include "tfrt/bef/bef_buffer.h"  // from @tf_runtime
#include "tfrt/bef_converter/mlir_to_bef.h"  // from @tf_runtime
#include "tfrt/bef_executor/bef_file.h"  // from @tf_runtime
#include "tfrt/host_context/async_value.h"  // from @tf_runtime
#include "tfrt/host_context/chain.h"  // from @tf_runtime
#include "tfrt/host_context/execution_context.h"  // from @tf_runtime

        [
            "//third_party/tf_runtime_llvm:tfrt_translate_main",
        ],
        ["@tf_runtime//third_party/llvm_derived:tfrt_translate_main"],
    ),
)

tf_cc_binary(
    name = "bef_executor",
    testonly = True,
    visibility = [":friends"],
    deps = [
        "@tf_runtime//:dtype",
        "@tf_runtime//:simple_tracing_sink",
        "@tf_runtime//tools:bef_executor_expensive_kernels",

 public:
  using Base::Base;
  static constexpr ::mlir::StringLiteral name = "tf_executor.control";
};

class TokenType : public Type::TypeBase<TokenType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr ::mlir::StringLiteral name = "tf_executor.token";
};

}  // namespace tf_executor
}  // namespace mlir

// Declares the operations for this dialect using the generated header.

    return isa<tf_executor::IslandOp>(region->getParentOp());
  }
};

}  // namespace

TensorFlowExecutorDialect::TensorFlowExecutorDialect(MLIRContext *context)
    : Dialect(/*name=*/"tf_executor", context,
              TypeID::get<TensorFlowExecutorDialect>()) {
  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.cc.inc"
      >();

      tf_executor.yield %const : tensor<*xi1>
    }
    %loop_cond:2 = tf_executor.LoopCond %island#0 : tensor<*xi1>
    tf_executor.fetch %loop_cond#0 : tensor<*xi1>
  }
  func.return
}

// CHECK: %[[CONTROL:[^ ,]*]] = tf_executor.island wraps "tf.Print"
// CHECK: tf_executor.Enter {{.*}}, %[[CONTROL]]
func.func @enter_control_input() {
  tf_executor.graph {
    %island:2 = tf_executor.island {

func.func @simple_independent_chains(%arg0: !tf_res, %arg1: !tf_res, %arg2: tensor<f32>) {
  // CHECK: tf_executor.graph {
  tf_executor.graph {
    // CHECK: %[[A_CONTROL:.*]] = tf_executor.island wraps "tf.OpA"() : () -> ()
    %control_A = tf_executor.island wraps "tf.OpA"() : () -> ()
    // CHECK: %[[CHAIN_CONSTANT:.*]], %{{.*}} = tf_executor.island wraps "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>

    %control = tf_executor.island() wraps "tf.TPUReplicateMetadata"() {_tpu_replicate = "cluster", device = "/device:TPU:0", num_replicas = 2, topology = "topology"} : () -> ()
    %ri, %c0 = tf_executor.island wraps "tf.TPUReplicatedInput"(%arg0, %arg1) {index = 1 : i64, is_mirrored_variable = false, is_packed = false} : (tensor<i32>, tensor<i32>) -> tensor<i32>

// CHECK: TPUCompile
// CHECK: TPUExecute
// CHECK-NOT: func @_func
    tf_executor.graph {
      %outputs, %control = tf_executor.island wraps "arith.constant"() {value = dense<2.000000e+00> : tensor<f32>} : () -> tensor<f32>
      %outputs_0, %control_1 = tf_executor.island wraps "arith.constant"() {value = dense<3.000000e+00> : tensor<f32>} : () -> tensor<f32>

func.func @multiple_func_body_ops() {
  tf_executor.graph {
    tf_executor.island {
      "tf.NoOp"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  tf_executor.graph {
    tf_executor.island {
      "tf.NoOp"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  func.return
}

// -----