Int32 ~int32,
	Int64 ~int64,
	Int8_16 ~int8 | ~int16,
](
	i8 Int8,
	i16 Int16,
	i32 Int32,
	i64 Int64,
	i8_16 Int8_16,
) {
	b = 42
	b = 42.0
	// etc.

	i8 = -1 << 7
	i8 = 1<<7 - 1
	i16 = -1 << 15
	i16 = 1<<15 - 1
	i32 = -1 << 31
	i32 = 1<<31 - 1
	i64 = -1 << 63
	i64 = 1<<63 - 1

	i8_16 = -1 << 7
	i8_16 = 1<<7 - 1
	i8_16 = - /* ERRORx `cannot use .* as Int8_16` */ 1 << 15

_xla_compile_device_type = "TPU", allow_soft_placement = false, computation_shape = [], device = "", device_assignment = [0, 0, 0, 0, 0, 0, 0, 1], host_compute_core = [], input_sharding_configuration = ["{devices=[2,1]0,1}"], num_cores_per_replica = 2 : i64, output_sharding_configuration = [""], padding_map = [], step_marker_location = "STEP_MARK_AT_ENTRY", topology = "\0A\04\02\02\01\02\10\01\18\08\22 \00\00\00\00\00\00\00\01\01\00\00\00\01\00\00\01\00\01\00\00\00\01\00\01\01\01\00\00\01\01\00\01", t...

  %2 = stablehlo.convolution(%arg0, %0) dim_numbers = [b, f, 0, 1]x[o, i, 0, 1]->[b, f, 0, 1], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x8x4x4xf32>, tensor<8x8x3x3xf32>) -> tensor<1x8x4x4xf32>
  return %2 : tensor<1x8x4x4xf32>
}
// CHECK: @main(%[[ARG:.+]]: tensor<1x8x4x4xf32>) -> tensor<1x8x4x4xf32>

    %2 = "tf.XlaCallModule"(%arg0, %0) <{Sout = [#tf_type.shape<1x3>], dim_args_spec = [], disabled_checks = [], has_token_input_output = false, module = "", platforms = [], version = 5 : i64}> {_entry_function = @composite_dot_general_fn_1, _original_entry_function = "composite_dot_general_fn_1", _stablehlo_module_attrs = {}, _tfl_quant_trait = "fully_quantizable", device = ""} : (tensor<1x1024xf32>, tensor<1024x3xf32>) -> tensor<1x3xf32>...

func.func @gather(%indices: tensor<?xi32>,
             %resource: tensor<*x!tf_type.resource>) -> tensor<*xi32> {
  %0 = "tf.ResourceGather"(%resource, %indices) {batch_dims = 0 : i64, device = "/device:CPU:0", validate_indices = true}: (tensor<*x!tf_type.resource>, tensor<?xi32>) -> (tensor<*xi32>)
  func.return %0 : tensor<*xi32>
}

 // expected-error@below {{op is in dialect chlo not in tf functional dialect}}
  %0 = "chlo.broadcast_add"(%arg0, %arg1) {broadcast_dimensions = array<i64: 3>} : (tensor<1x32x10x32xi32>, tensor<32xi32>) -> tensor<1x32x10x32xi32>
  func.return %0 : tensor<1x32x10x32xi32>
}

// -----

// CHECK-LABEL: func @testTFDialect

}

func.func @callee(%ch: !tfrt.chain, %arg: !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor) {
  %const = tfrt_fallback_async.const_dense_tensor dense<9> : tensor<i32> {_tfrt_cost = 1 : i64}
  %result = tfrt_fallback_async.executeop key(0) cost(3) device("/device:CPU:0") "tf.Less"(%arg, %const) {T = i32} : 1
  tfrt.return %ch, %result : !tfrt.chain, !tfrt_fallback.tf_tensor
}

      %arg1 : tensor<*x!tf_type.variant>) {
    %cst_0 = arith.constant dense<2> : tensor<i64>
    %cst_1 = arith.constant dense<0> : tensor<i32>
    %0 = "tf.RepeatDataset"(%arg1, %cst_0) {device = "",
      output_shapes = [#tf_type.shape<?>],
      output_types = [!tf_type.string]} : (tensor<*x!tf_type.variant>, tensor<i64>) -> tensor<!tf_type.variant>

    %1 = "tf.ReduceDataset"(%0, %cst_1, %arg0) {

    %0 = "tf.XlaCallModule"(%arg0, %arg1) {Sout = [#tf_type.shape<?>], dim_args_spec = [], _entry_function = @_stablehlo_main_0, _stablehlo_module_attrs = { mhlo.num_partitions = 1 }, module = "", platforms = [], version = 5 : i64} : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi32>
    // CHECK: return %[[RESULT]]
    func.return %0 : tensor<10xi32>
  }

    %2 = stablehlo.add %1, %arg2 : tensor<5xf32>
    %3 = "tfl.abs"(%2) {fused_activation_function = "NONE"} : (tensor<5xf32>) -> tensor<5xf32>
    "stablehlo.return"(%3) : (tensor<5xf32>) -> ()
  }) {dimensions = array<i64: 0>} : (tensor<7x5xf32>, tensor<5xf32>) -> tensor<5xf32>
  func.return %0: tensor<5xf32>
}

// -----

// CHECK-LABEL: op_with_region_mixed_shlo_tfl_shlo