package main

import "fmt"

type T int

func (t T) String() string { return fmt.Sprintf("T%d", int(t)) }

const (
	A T = 1 << (1 << iota)
	B
	C
	D
	E
)

func main() {
	s := fmt.Sprintf("%v %v %v %v %v", A, B, C, D, E)
	if s != "T2 T4 T16 T256 T65536" {
		println("type info didn't propagate in const: got", s)
		panic("fail")
	}
	x := uint(5)
	y := float64(uint64(1)<<x)	// used to fail to compile

// CHECK: name: "const2"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_HALF
// CHECK: half_val: 15360
// CHECK: half_val: 16384
// CHECK: name: "const3"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_BFLOAT16
// CHECK: half_val: 16964
// CHECK: half_val: 17485
// CHECK: name: "const4"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_BFLOAT16

	// First reduction step
	MUL	acc0, hlp1, hlp0

	MUL	const0, hlp1, t0
	ADDS	t0, acc0, acc0
	UMULH	const0, hlp0, t1

	MUL	const1, hlp0, t0
	ADCS	t0, acc1, acc1
	UMULH	const1, hlp0, y0

	MUL	const2, hlp0, t0
	ADCS	t0, acc2, acc2
	UMULH	const2, hlp0, acc0

	MUL	const3, hlp0, t0
	ADCS	t0, acc3, acc3

	UMULH	const3, hlp0, hlp0
	ADC	$0, hlp0

	ADDS	t1, acc1, acc1

// CHECK: name: "const2"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_HALF
// CHECK: half_val: 15360
// CHECK-NEXT: half_val: 16384
    %2:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = bf16, value = dense<[4.900000e+01, 8.200000e+02]> : tensor<2xbf16>} : () -> tensor<bf16> loc("const3")
// CHECK: name: "const3"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_BFLOAT16
// CHECK: half_val: 16964

					Valu("sb", OpSB, c.config.Types.Uintptr, 0, nil),
					Valu("const2", OpConst32, intType, 2, nil),
					Valu("const3", OpConst32, intType, 3, nil),
					Goto("b5")),
				Bloc("b2",
					Valu("addr", OpAddr, boolType.PtrTo(), 0, nil, "sb"),
					Valu("cond", OpLoad, boolType, 0, nil, "addr", "start"),
					Valu("phi", OpPhi, intType, 0, nil, "const2", "const3"),
					If("cond", "b3", "b4")),
				Bloc("b3",
					Goto("b2")),

// ChaCha8 is ChaCha with 8 rounds.
// See https://cr.yp.to/chacha/chacha-20080128.pdf.
//
// ChaCha8 operates on a 4x4 matrix of uint32 values, initially set to:
//
//	const1 const2 const3 const4
//	seed   seed   seed   seed
//	seed   seed   seed   seed
//	counter64     0      0
//
// We use the same constants as ChaCha20 does, a random seed,
// and a counter. Running ChaCha8 on this input produces

    // CHECK: %[[CONST2:.*]] = "tf.Const"() <{value = dense<
    // CHECK-SAME: [8, 8, 3, 64]
    // CHECK: %[[RESHAPE1:.*]] = "tf.Reshape"(%[[TRANSPOSE1:.*]], %[[CONST2:.*]]) : (tensor<4x2x4x2x3x64xf32>, tensor<4xi64>) -> tensor<8x8x3x64xf32>
    // CHECK: %[[CONST3:.*]] = "tf.Const"() <{value = dense<
    // CHECK-SAME: [7, 7, 3, 64]

    //        |         |
    //      Const_0    Const_1
    //
    const float const0_val[] = {1.0, 2.0, 3.0, 4.0};
    const float const1_val[] = {1.0, 0.0, 0.0, 1.0};
    TF_Operation* const0 = FloatConst2x2(graph_, s_, const0_val, "Const_0");
    TF_Operation* const1 = FloatConst2x2(graph_, s_, const1_val, "Const_1");
    TF_Operation* matmul = MatMul(graph_, s_, const0, const1, "MatMul");
    inputs[0] = TF_Output{const0, 0};

        shape {
          dim {
            size: 2
          }
        }
      }
    }
  }
}
node {
  name: "RaggedToTensor"
  op: "RaggedTensorToTensor"
  input: ["Const0", "_Arg", "Const1", "Const2"]
  attr {
    key: "T"
    value {
      type: DT_STRING
    }
  }
  attr {
    key: "row_partition_types"
    value {
      list {
        s: ["ROW_SPLITS"]
      }

(Lsh32x64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])
(Rsh32x64 x (Int64Make (Const32 [c]) _)) && c != 0 => (Signmask x)
(Rsh32Ux64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])
(Lsh16x64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])
(Rsh16x64 x (Int64Make (Const32 [c]) _)) && c != 0 => (Signmask (SignExt16to32 x))
(Rsh16Ux64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])