}

// New returns a new Rand that uses random values from src
// to generate other random values.
func New(src Source) *Rand {
	return &Rand{src: src}
}

// Int64 returns a non-negative pseudo-random 63-bit integer as an int64.
func (r *Rand) Int64() int64 { return int64(r.src.Uint64() &^ (1 << 63)) }

// Uint32 returns a pseudo-random 32-bit value as a uint32.
func (r *Rand) Uint32() uint32 { return uint32(r.src.Uint64() >> 32) }

  // Collect operands for the new merged island.
  island_operands_and_results.operands.clear();
  for (IslandOp island : merged_island.islands)
    island_operands_and_results.operands.insert(island.operand_begin(),
                                                island.operand_end());
  for (IslandOp island : merged_island.islands)
    island_operands_and_results.operands.remove(island.getControl());

  %0:2 = tf_executor.graph {
    %control = tf_executor.island() wraps "tf.TPUReplicateMetadata"() {_tpu_replicate = "cluster", device = "/device:TPU:0", num_replicas = 2, topology = "topology"} : () -> ()
    %ri, %c0 = tf_executor.island wraps "tf.TPUReplicatedInput"(%arg0, %arg1) {index = 1 : i64, is_mirrored_variable = false, is_packed = false} : (tensor<i32>, tensor<i32>) -> tensor<i32>

// CHECK-NOT: func @_func
    tf_executor.graph {
      %outputs, %control = tf_executor.island wraps "arith.constant"() {value = dense<2.000000e+00> : tensor<f32>} : () -> tensor<f32>
      %outputs_0, %control_1 = tf_executor.island wraps "arith.constant"() {value = dense<3.000000e+00> : tensor<f32>} : () -> tensor<f32>

	readPos int8
}

// New returns a new [Rand] that uses random values from src
// to generate other random values.
func New(src Source) *Rand {
	s64, _ := src.(Source64)
	return &Rand{src: src, s64: s64}
}

// Seed uses the provided seed value to initialize the generator to a deterministic state.
// Seed should not be called concurrently with any other [Rand] method.
func (r *Rand) Seed(seed int64) {

    %outputs, %control = tf_executor.island wraps "tf.GuaranteeConst"(%arg1) {T = f32, device = ""} : (tensor<f32>) -> tensor<f32>
    %outputs_0, %control_1 = tf_executor.island wraps "tf.GuaranteeConst"(%arg2) {T = f32, device = ""} : (tensor<f32>) -> tensor<f32>
    %control_2 = tf_executor.island wraps "tf.NoOp"() {_pivot_for_cluster = "cluster", device = ""} : () -> ()

    }
  }

  IslandOp new_island = OpBuilder(island).create<IslandOp>(
      island.getLoc(), result_types,
      /*control=*/ControlType::get(island.getContext()),
      /*controlInputs=*/island.getOperands());
  new_island.getBody().push_back(new Block);

  // Move the operations in the new island, gather the results of the new yield.
  Block& island_body = new_island.GetBody();

// tf_executor.island {_parallel_execution_ids=r0:0,p0:0} wraps "tf.OpC"
// tf_executor.island {_parallel_execution_ids=r0:0,p0:1} wraps "tf.OpD"
// tf_executor.island {_parallel_execution_ids=r0:1} wraps "tf.OpB"
// tf_executor.island {_parallel_execution_ids=r0:1,p0:0} wraps "tf.OpC"
// tf_executor.island {_parallel_execution_ids=r0:1,p0:1} wraps "tf.OpD"
//
// "tf.OpA" will not have `_parallel_execution_ids` attr,

}

mlir::LogicalResult IslandOp::verify() {
  IslandOp island = *this;
  if (!island.GetBody().args_empty())
    return island.emitOpError() << "expects body without any arguments";

  Operation &yield = island.GetBody().back();
  if (!isa<YieldOp>(yield))
    return yield.emitOpError()
           << "invalid tf_executor.island terminator, yield expected";

// Copyright 2010 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// Package rand implements a cryptographically secure
// random number generator.
package rand

import "io"

// Reader is a global, shared instance of a cryptographically
// secure random number generator.
//
//   - On Linux, FreeBSD, Dragonfly, and Solaris, Reader uses getrandom(2)