"//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/compiler/mlir/tensorflow:tensorflow_types",
        "//tensorflow/core:framework",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/framework:tensor_testutil",
        "//tensorflow/core/util/tensor_bundle",
        "@com_google_absl//absl/cleanup",

			},
		},
		5: {
			desc:       "Correct sha256, nested",
			src:        mustReader(t, bytes.NewReader([]byte("abcd")), 4, "", "", 4),
			size:       4,
			actualSize: 4,
			sha256hex:  "88d4266fd4e6338d13b845fcf289579d209c897823b9217da3e161936f031589",
		},
		{
			desc:       "Correct sha256, nested, truncated",

        "//tensorflow/c:tf_datatype",
        "//tensorflow/cc/experimental/base/public:status",
        "//tensorflow/cc/experimental/base/public:tensor",
        "//tensorflow/core:lib",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
    ],
)

tf_cc_test(
    name = "tensorhandle_test",
    srcs = [
        "tensorhandle_test.cc",
    ],
    deps = [
        ":tensor_types_test_util",

        ":xla_gpu_jit",
        "//tensorflow/cc:function_ops",
        "//tensorflow/cc:math_ops",
        "//tensorflow/cc:scope",
        "//tensorflow/core:framework",
        "//tensorflow/core:test",
        "//tensorflow/core/kernels:ops_testutil",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:status",
        "//tensorflow/core/platform:status_matchers",

func.func @test(%ch: !tfrt.chain, %arg0: !corert.tensorhandle, %arg1_th: !corert.tensorhandle) {
  %cpu = corert.get_op_handler %ch "cpu"
  %0 = corert.executeop(%cpu) "tf.Relu"(%arg0) { T = f32 } : 1
  %arg1 = tfrt_fallback_async.corert_tensorhandle_to_fallback_tensor %arg1_th {_tfrt_cost = 1 : i64, device = "/CPU:0"} : (!corert.tensorhandle) -> (!tfrt_fallback.tf_tensor)
  %1 = tfrt_fallback_async.executeop key(0) cost(100) device("/CPU:0") "tf.Relu"(%arg1) { T = f32 } : 1

func.func @test(%ch: !tfrt.chain, %arg0: !corert.tensorhandle, %arg1_th: !corert.tensorhandle) {
  %cpu = corert.get_op_handler %ch "cpu"
  %0 = corert.executeop(%cpu) "tf.Relu"(%arg0) { T = f32 } : 1
  %arg1 = tfrt_fallback_async.corert_tensorhandle_to_fallback_tensor %arg1_th {_tfrt_cost = 1 : i64, device = "/CPU:0"} : (!corert.tensorhandle) -> (!tfrt_fallback.tf_tensor)
  %1 = tfrt_fallback_async.executeop key(0) cost(100) device("/CPU:0") "tf.Relu"(%arg1) { T = f32 } : 1

			pools:          pools,
			name:           "Correct",
			expectedErr:    false,
			expectedUpdate: false,
		},
		{
			meta:           meta,
			pools:          newPools,
			name:           "Correct-Update",
			expectedErr:    false,
			expectedUpdate: true,
		},
		{
			meta:           meta,
			pools:          reducedPools,
			name:           "Correct-Update",
			expectedErr:    false,

func.func @resource() {
  // CHECK: tf.SomeOp
  // CHECK-SAME: dtype = !corert.resource
  "tf.SomeOp"() {device = "/device:CPU:0", dtype = !tf_type.resource} : () -> ()
  func.return
}

// CHECK-LABEL: func @variant
func.func @variant(%arg: tensor<!tf_type.variant>) {
  // CHECK: tf.ZerosLike
  // CHECK-SAME: T = !corert.variant

	listTypeResourceSchema = `
type: object
properties:
  correct-map:
    type: array
    x-kubernetes-list-type: map
    x-kubernetes-list-map-keys: ["a", "b"]
    items:
      type: object
      required: ["a", "b"]
      properties:
        a:
          type: integer
        b:
          type: integer
  correct-set:
    type: array
    x-kubernetes-list-type: set
    items:

        'paddings': paddings,
        'mode': mode,
    }
    # Make sure the composition python function is correct
    self._assertOpAndComposite([input_], tf.raw_ops.MirrorPad,
                               ops_defs._composite_mirror_pad, kwargs_, kwargs)
    # Make sure the translation and decomposition is correct
    self._assertOpAndComposite([input_],
                               tf.function(gen_pad_ops.new_mirror_pad),