// CHECK-NEXT: %[[q:.*]] = "tfl.quantize"(%arg0) <{qtype = tensor<1x224x224x3x!quant.uniform<i8:f32, 7.812500e-03>>}> : (tensor<1x224x224x3xf32>) -> tensor<1x224x224x3x!quant.uniform<i8:f32, 7.812500e-03>>
// CHECK-NEXT: %[[cst1:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<i8<-127:127>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>}> : () -> tensor<32x3x3x3x!quant.uniform<i8<-127:127>:f32, 0.021826678373682216>>

    // CHECK: %[[CST0:.*]] = stablehlo.constant dense<0xFF800000> : tensor<f32>
    // CHECK: %[[CST1:.*]] = stablehlo.constant dense<0xFF80000E> : tensor<2x3x1024x3xf32>
    // CHECK: %[[Q0:.*]] = "quantfork.qcast"(%[[CST0]])
    // CHECK: %[[Q1:.*]] = "quantfork.qcast"(%[[CST1]])
    // CHECK: %[[Q2:.*]] = "quantfork.qcast"(%[[ARG0]])
    // CHECK: %[[CALL:.*]] = call @quantized_dot_general_fn_1(%[[Q2]], %[[Q1]])

  %cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")

    attributes {tf.entry_function = {outputs = "result"}} {
  %cst = arith.constant dense<1> : tensor<i32> loc("dec")
  %cst0 = arith.constant dense<5> : tensor<i32> loc("N")
  %cst1 = arith.constant dense<3.0> : tensor<1xf32> loc("val")
  %0:2 = "tfl.while"(%cst0, %cst1) ({
    ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
      // CHECK: call @WhileOp_cond
      // CHECK-SAME: (tensor<*xi32>, tensor<*xf32>)

          [(ValueEquals<"0.0"> $cst),
           (ValueEquals<"0.0"> $cst1),
           (ValueEquals<"0.0"> $cst2),
           (SameValue $rem, $rem1),
           (SameValue $rem, $rem2),
           (SameValue $rem, $rem3),
           (SameTypeOrDefaultCompare $compare_type, $cst),
           (SameTypeOrDefaultCompare $compare_type1, $cst1)]>;

// Converts a dag of HLOs representing floor_mod with a constant to

  %cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")

  %cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")

// CHECK: %[[cst1:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 1.000000e-01>>, value = dense<1> : tensor<32x3x3x3xi8>}>
// CHECK: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[cst1]], %[[cst0]])
// CHECK: return %[[conv]] : tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>
}

			case out <- b:
			case <-done:
				return
			}
		}
	}()
	cnt1, cnt2 := 0, 0
	for i := 0; i < trials; i++ {
		switch b := <-out; b {
		case 1:
			cnt1++
		case 2:
			cnt2++
		default:
			t.Fatalf("unexpected value %d on channel", b)
		}
	}
	// If the select in the goroutine is fair,
	// cnt1 and cnt2 should be about the same value.

		o.Write(k)

		kk, err := Decapsulate(dk, ct)
		if err != nil {
			t.Fatal(err)
		}
		if !bytes.Equal(kk, k) {
			t.Errorf("k: got %x, expected %x", kk, k)
		}

		s.Read(ct1)
		k1, err := Decapsulate(dk, ct1)
		if err != nil {
			t.Fatal(err)
		}
		o.Write(k1)
	}

	got := hex.EncodeToString(o.Sum(nil))
	if got != expected {
		t.Errorf("got %s, expected %s", got, expected)
	}
}