return nil
}

func iterSimple(yield func(int) bool) {
	for range 3 {
		if !yield(5) {
			return
		}
	}
}

func iterNested(yield func(int) bool) {
	next, stop := iter.Pull(iterSimple)
	for {
		v, ok := next()
		if ok {
			if !yield(v) {
				stop()
			}
		} else {
			return
		}
	}
}

func iterLock(yield func(int) bool) {
	for range 3 {

        %2 = "tf.Abs"(%asin) : (tensor<*xf32>) -> tensor<*xf32>
        "tf.Yield"(%2) : (tensor<*xf32>) -> ()
      }, {
        %2 = "tf.Neg"(%arg1) : (tensor<*xf32>) -> tensor<*xf32>
        "tf.Yield"(%2) : (tensor<*xf32>) -> ()
      }) { is_stateless = true } :  (tensor<i1>) -> tensor<*xf32>

    "tf.Yield"(%1) : (tensor<*xf32>) -> ()
    }, {
    // Outer Else

      tf_executor.yield %add1, %add2 : tensor<*xi32>, tensor<*xi32>
    }
    %island2:3 = tf_executor.island(%island1#2) {
      %sub = "tf.Sub"(%arg0, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
      %mul = "tf.Mul"(%sub, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
      tf_executor.yield %sub, %mul : tensor<*xi32>, tensor<*xi32>
    }

import (
	"fmt"
	. "iter"
	"runtime"
	"testing"
)

func count(n int) Seq[int] {
	return func(yield func(int) bool) {
		for i := range n {
			if !yield(i) {
				break
			}
		}
	}
}

func squares(n int) Seq2[int, int64] {
	return func(yield func(int, int64) bool) {
		for i := range n {
			if !yield(i, int64(i)*int64(i)) {
				break
			}
		}
	}
}

func TestPull(t *testing.T) {

// When called as seq(yield), seq calls yield(v) for each value v in the sequence,
// stopping early if yield returns false.
type Seq[V any] func(yield func(V) bool)

// Seq2 is an iterator over sequences of pairs of values, most commonly key-value pairs.
// When called as seq(yield), seq calls yield(k, v) for each pair (k, v) in the sequence,
// stopping early if yield returns false.

  // CHECK-SAME: _then_func_name = "testIf1Then"
  // CHECK-SAME: is_stateless = false
  // CHECK: [[Result0:%.*]] = func.call @testIf1Then
  // CHECK: "tf.Yield"([[Result0]])
  // CHECK: [[Result1:%.*]] = func.call @testIf1Else
  // CHECK: "tf.Yield"([[Result1]])
  // CHECK: _attr0 = 10
  // CHECK-SAME: _attr1 = true
  // CHECK-NOT: attr2 =
  // CHECK-NOT: else_branch
  // CHECK-NOT: then_branch
  // CHECK-SAME: }

      "tf.Yield"(%0) : (tensor<512x256xf32>) -> ()
    }, {
      "tf.Yield"(%arg2) : (tensor<512x256xf32>) -> ()
    }) { is_stateless = true}: (tensor<i1>) -> tensor<512x256xf32>
    "tf.Yield"(%1) : (tensor<512x256xf32>) -> ()
  }, {
    "tf.Yield"(%arg2) : (tensor<512x256xf32>) -> ()
  }) { is_stateless = true}: (tensor<i1>) -> tensor<512x256xf32>

	})
	return err
}

func iterSimple(yield func(int) bool) {
	for range 3 {
		if !yield(5) {
			return
		}
	}
}

func iterNested(yield func(int) bool) {
	next, stop := iter.Pull(iterSimple)
	for {
		v, ok := next()
		if ok {
			if !yield(v) {
				stop()
			}
		} else {
			return
		}
	}
}

func iterCallback(yield func(int) bool) {
	for range 3 {

func.func @multiple_func_body_ops() {
  tf_executor.graph {
    tf_executor.island {
      "tf.NoOp"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  tf_executor.graph {
    tf_executor.island {
      "tf.NoOp"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  func.return
}

// -----

        tf_device.return %2 : tensor<i64>
      }
      tf_executor.yield %1#0, %1#1 : tensor<i64>, tensor<i64>
    }
    tf_executor.fetch
  }
  func.return
}

// CHECK:      tf_executor.island
// CHECK:      [[CONST_0:%.+]] = "tf.Const"
// CHECK-SAME: value = dense<1> : tensor<i64>
// CHECK:      tf_executor.yield [[CONST_0]]
// CHECK:      tf_executor.island
// CHECK:      [[CONST_1:%.+]] = "tf.Const"