%0 = mhlo.constant dense<1.000000e+00> : tensor<f64>
      %1 = mhlo.convert %0 : (tensor<f64>) -> tensor<i64>
      %2 = mhlo.reshape %1 : (tensor<i64>) -> tensor<1xi64>
      %3 = "mhlo.dynamic_iota"(%2) {iota_dimension = 0 : i64} : (tensor<1xi64>) -> tensor<?xi32>
      %4 = mhlo.multiply %3, %3 : tensor<?xi32>
      return %4 : tensor<?xi32>
    }
  })";
  CellReader<int64_t> legal_error(kFailedLegalizationStreamz);

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

  %cst = "tf.Const"() <{value = dense<0.000000e+00> : tensor<f32>}> : () -> tensor<f32>
  %cst_0 = "tf.Const"() <{value = dense<1> : tensor<1xi64>}> : () -> tensor<1xi64>
  %fill = "tf.Fill"(%cst_0, %cst) : (tensor<1xi64>, tensor<f32>) -> tensor<1xf32>
  tf_device.replicate([%0, %fill] as %arg_r0: tensor<1xf32>) {n = 2 : i32} {
    %1 = "tf_device.launch"() <{device = "TPU_REPLICATED_HOST_0"}> ({

    %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...

  // CHECK-DAG: %cst = arith.constant dense<0.000000e+00> : tensor<10x10xf32>
  // CHECK-DAG: %cst_0 = arith.constant dense<1000> : tensor<2xi64>
  // CHECK-DAG: %cst_1 = arith.constant dense<1.000000e+00> : tensor<f32>
  // CHECK: %0 = "tfl.fill"(%cst_0, %cst_1) : (tensor<2xi64>, tensor<f32>) -> tensor<1000x1000xf32>
  // CHECK: return %cst, %0 : tensor<10x10xf32>, tensor<1000x1000xf32>

  %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