func.func private @while_body(%arg0 : tensor<4xf32>, %arg1 : tensor<i32>) -> (tensor<4xi64>, tensor<i32>)
func.func @testWhileRegionIncompatibleCast(%arg0 : tensor<*xi64>, %arg1 : tensor<i32>) -> tensor<*xi64> {
  // CHECK: [[Result:%.*]]:2 = "tf.While"(%arg0, %arg1) <{body = @tf.WhileRegion_body, cond = @tf.WhileRegion_cond
  %0:2 = "tf.WhileRegion"(%arg0, %arg1) (
    {
      ^bb0(%carg0: tensor<*xi64>, %carg1: tensor<i32>):

  %1:4 = "tf.CustomAggregator"(%arg0) {id = "1", calibration_method = 1 : i32, num_bins = 0 : i32, max_percentile = 0.000000e+00 : f32, min_percentile = 0.000000e+00 : f32} : (tensor<8x8x8x8xf32>) -> (tensor<8x8x8x8xf32>, tensor<f32>, tensor<f32>, tensor<*xi64>)
  func.return %0#0, %1#0 : tensor<8x8x8x8xf32>, tensor<8x8x8x8xf32>
}
// CHECK: func @customAggregator

    %1 = "tf.RngReadAndSkip"(%resource, %alg, %delta) : (tensor<!tf_type.resource<tensor<3xi64>>>, tensor<i32>, tensor<ui64>) -> tensor<3xi64>
    tf_device.return %1 : tensor<3xi64>
  }) : () -> tensor<3xi64>
  func.return %0 : tensor<3xi64>
}

// Test that ordering token resource of tf.CollectiveReduceV2 op is removed.
// CHECK-LABEL: func @decompose_collective_reduce_v2_op

    %3 = "tf.XlaCallModule"(%2#0, %0, %1) {Sout = [#tf_type.shape<1x3>], _entry_function = @composite_dot_general_fn_1, _original_entry_function = "composite_dot_general_fn_1", _tfl_quant_trait = "fully_quantizable", dim_args_spec = [], disabled_checks...

  %2 = "tf.LookupTableFindV2"(%0, %arg, %default) {device = "/CPU:0"} : (tensor<!tf_type.resource>, tensor<?x!tf_type.string>, tensor<i64>) -> tensor<*xi64>
  func.return %1, %2 : tensor<i64>, tensor<*xi64>
}

}

  %2 = "tf.XlaCallModule"(%1#0, %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, _o...

  // CHECK-SAME: <{calibration_methods = [1 : i32, 1 : i32], ids = ["0", "1"], output_file_path = "main_0.pb"}> : (tensor<f32>, tensor<f32>, tensor<0xi64>, tensor<f32>, tensor<f32>, tensor<0xi64>) -> ()
  // CHECK: return

  func.func @init_all_tables()
  attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer"]} {
    %cst = arith.constant dense<[1, 2, 3, 4]> : tensor<4xi64>
    %cst_0 = arith.constant dense<["a", "b", "c", "d"]> : tensor<4x!tf_type.string>

  func.return %0 : tensor<4xi32>
}

func.func @i64() -> tensor<4xi64> {
  // CHECK-LABEL: @i64
  // CHECK: value = dense<[1, 2, 3, 72623859790382856]> : tensor<4xi64>
  %0 = "tfl.pseudo_const" () { value = dense<[1, 2, 3, 72623859790382856]> : tensor<4xi64> } : () -> tensor<4xi64>
  func.return %0 : tensor<4xi64>
}

func.func @string() -> tensor<2x2x!tf_type.string> {
  // CHECK-LABEL: @string

  func.func @main(%arg0: tensor<10x19xf32>, %arg1: tensor<19x10xf32> {mhlo.is_same_data_across_replicas = true}) -> tensor<10x19xf32> {
    %0 = "tf.Shape"(%arg0) : (tensor<10x19xf32>) -> tensor<2xi64>
    %1 = "tf.Reshape"(%arg1, %0) : (tensor<19x10xf32>, tensor<2xi64>) -> tensor<10x19xf32>
    func.return %1 : tensor<10x19xf32>
  }
}

// Tests that foldable ops are constant-folded to enable legalization of ops