public static final KnownArchitecture X86_64 = new KnownArchitecture("x86-64", "x86_64", "amd64", "x64");
    public static final KnownArchitecture IA_64 = new KnownArchitecture("ia-64", "ia64");
    public static final KnownArchitecture ARM_V7 = new KnownArchitecture("arm-v7", "armv7", "arm", "arm32");
    public static final KnownArchitecture AARCH64 = new KnownArchitecture("aarch64", "arm-v8", "arm64");

}

// -----

// CHECK-LABEL: @add_f64(%arg0: tensor<3x3xbf16>, %arg1: tensor<3x3xbf16>) -> tensor<3x3xbf16>
func.func @add_f64(%arg0: tensor<3x3xf64>, %arg1: tensor<3x3xf64>) -> tensor<3x3xf64> {
  // CHECK-NOT: f64
  // CHECK: stablehlo.add
  %0 = stablehlo.add %arg0, %arg1: (tensor<3x3xf64>, tensor<3x3xf64>) -> tensor<3x3xf64>
  return %0 : tensor<3x3xf64>
}

// -----

// CHECK-LABEL: @constant_f32() -> tensor<2x2xbf16>

    %0 = stablehlo.composite "stablehlo.add_n" %arg0 { composite_attributes = { test_int = 2 : i64, test_bool = 0 : i1, test_string = "test"}, decomposition = @add_n.impl } : (tensor<i64>) -> tensor<i64>
    return %0 : tensor<i64>
  }
  func.func private @add_n.impl(%arg0: tensor<i64>) -> tensor<i64> {
    %0 = stablehlo.constant dense<2> : tensor<i64>

// Serialized string:
//   "\08\01\1A\01\01\22\01\00"

// CHECK-LABEL: func @host_compute
// CHECK-SAME:  ([[ARG0:%.*]]: tensor<i32>, [[ARG1:%.*]]: tensor<i64>)
func.func @host_compute(%arg0: tensor<i32>, %arg1: tensor<i64>) -> (tensor<f32>, tensor<f64>) {
  // CHECK:      [[INIT_TOKEN:%.*]] = mhlo.create_token

  // CHECK:      [[SEND_ARG0_TOKEN:%.*]] = "mhlo.send"([[ARG0]], [[INIT_TOKEN]])

      lhs_quantization_axis = -1 : i64,
      lhs_quantization_min_val = -2147483648 : i64,
      lhs_quantization_max_val = 2147483647 : i64,
      rhs_quantization_axis = -1 : i64,
      rhs_quantization_min_val = -2147483648 : i64,
      rhs_quantization_max_val = 2147483647 : i64,
      output_quantization_axis = -1 : i64,
      output_quantization_min_val = -2147483648 : i64,

  // CHECK-NEXT:  return [[SIZE]] : tensor<i64>
  func.return %1 : tensor<i64>
}

// -----

// Test for case with import and find ops.
func.func @hashtable_import_then_find(%arg0: tensor<5x!tf_type.string>) -> tensor<*xi64> {
  %cst = arith.constant dense<["emerson", "lake", "palmer"]> : tensor<3x!tf_type.string>
  %cst_0 = arith.constant dense<-1> : tensor<i64>

  // CHECK-SAME: allowed_batch_sizes = [6]
  // CHECK-SAME: batch_timeout_micros = 100000 : i64
  // CHECK-SAME: batching_queue = ""
  // CHECK-SAME: container = ""
  // CHECK-SAME: enable_large_batch_splitting = false
  // CHECK-SAME: max_batch_size = 6 : i64
  // CHECK-SAME: max_enqueued_batches = 10 : i64
  // CHECK-SAME: num_batch_threads = 2 : i64
  // CHECK-SAME: shared_name = "batch/"

      lhs_quantization_axis = -1 : i64,
      lhs_quantization_min_val = -2147483648 : i64,
      lhs_quantization_max_val = 2147483647 : i64,
      rhs_quantization_axis = -1 : i64,
      rhs_quantization_min_val = -2147483648 : i64,
      rhs_quantization_max_val = 2147483647 : i64,
      output_quantization_axis = -1 : i64,
      output_quantization_min_val = -2147483648 : i64,

    }, {
    ^bb0(%arg0: tensor<i64>, %arg1: tensor<i64>):
      %new_sum = "vhlo.add_v1"(%arg1, %arg1) : (tensor<i64>, tensor<i64>) -> tensor<i64>
      %new_i = "vhlo.add_v1" (%arg0, %arg1) : (tensor<i64>, tensor<i64>) -> tensor<i64>
      "vhlo.return_v1"(%new_i, %new_sum) : (tensor<i64>, tensor<i64>) ->()
  }) : (tensor<i64>, tensor<i64>) -> (tensor<i64>, tensor<i64>)
  return %0 : tensor<i64>
}

    "tf.InitializeTableFromTextFileV2"(%0, %arg0) {delimiter = "\09", device = "", key_index = -2 : i64, offset = 0 : i64, value_index = -1 : i64, vocab_size = 437 : i64} : (tensor<!tf_type.resource>, tensor<!tf_type.string>) -> ()