%1 = "tf.BiasAdd"(%0, %bias) {T = "tfdtype$DT_FLOAT", data_format = "NHWC"}: (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
  %2 = "tf.Mul"(%1, %value) {T = "tfdtype$DT_FLOAT"} : (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
  func.return %2 : tensor<256x8x7x16xf32>

  %group_assignment = "tf.Const"() { value = dense<[[0],[1]]> : tensor<2x1xi32> } : () -> tensor<2x1xi32>
  // CHECK: "mhlo.all_reduce"
  // CHECK: mhlo.mul
  %0 = "tf.XlaAllReduce"(%input, %group_assignment) {reduce_op = "Mul", mode = "CrossReplica"} : (tensor<f32>, tensor<2x1xi32>) -> tensor<f32>
  func.return %0 : tensor<f32>
}

// -----

	WORD    $0xA71AF000     //ahi   %r1,-4096
	WFMADB  V2, V6, V0, V6
L17:
	RISBGN	$0, $15, $48, R1, R2
	LDGR    R2, F2
	FMADD   F2, F6, F2
	MOVD    $coshx4ff<>+0(SB), R1
	FMOVD   0(R1), F0
	FMUL    F2, F0
	FMOVD   F0, ret+8(FP)
	RET

L19:
	FNEG    F0, F4
	BR      L2
L20:
	MOVD    $coshxaddhy<>+0(SB), R1
	FMOVD   coshrodataL23<>+16(SB), F3
	FMOVD   0(R1), F2
	WFMSDB  V0, V3, V2, V3

// license that can be found in the LICENSE file.

package bug109

func f(a float64) float64 {
	e := 1.0
	e = e * a
	return e
}

/*
6g bugs/bug109.go
bugs/bug109.go:5: illegal types for operand: MUL
	(<float64>FLOAT64)
	(<float32>FLOAT32)
bugs/bug109.go:5: illegal types for operand: AS
	(<float64>FLOAT64)
bugs/bug109.go:6: illegal types for operand: RETURN
	(<float32>FLOAT32)
	(<float64>FLOAT64)

    %0 = tfl.add %arg0, %arg1 {fused_activation_function = "RELU6", tac.device = "GPU", tac.inference_type = "FLOAT"} : tensor<1xf32>
    %1 = tfl.mul %0, %arg2 {fused_activation_function = "RELU6", tac.device = "GPU", tac.inference_type = "FLOAT"} : tensor<1xf32>
    func.return %1 : tensor<1xf32>
  }

    StringRef reduce_op = all_reduce.getReduceOp();

    StringRef merge_op, final_op;
    if (reduce_op == "Add") {
      merge_op = "Add";
      final_op = "Id";
    } else if (reduce_op == "Mul") {
      merge_op = "Mul";
      final_op = "Id";
    } else if (reduce_op == "Min") {
      merge_op = "Min";
      final_op = "Id";
    } else if (reduce_op == "Max") {
      merge_op = "Max";
      final_op = "Id";

(MOVWnop (MOVWconst [c])) => (MOVWconst [c])

// mul by constant
(MUL x (MOVWconst [c])) && int32(c) == -1 => (RSBconst [0] x)
(MUL _ (MOVWconst [0])) => (MOVWconst [0])
(MUL x (MOVWconst [1])) => x
(MUL x (MOVWconst [c])) && isPowerOfTwo32(c) => (SLLconst [int32(log32(c))] x)
(MUL x (MOVWconst [c])) && isPowerOfTwo32(c-1) && c >= 3 => (ADDshiftLL x x [int32(log32(c-1))])

		println(s[0])
		panic("s[0] != 1")
	}
	if s[1] != 2+3i {
		println(s[1])
		panic("s[1] != 2+3i")
	}
	if s[2] != 4+5i {
		println(s[2])
		panic("s[2] != 4+5i")
	}

	x := 1 + 2i
	y := a.Mul(x)
	if y != (1+2i)*(3+4i) {
		println(y)
		panic("y != (1+2i)*(3+4i)")
	}

#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/util/work_sharder.h"

namespace tensorflow {
namespace {

using ops::Add;
using ops::BatchMatMul;
using ops::Const;
using ops::Mul;
using ops::Placeholder;
using ops::Sub;

tensorflow::SessionOptions GetSessionOptions() {
  tensorflow::SessionOptions options;
  // Disable optimizations for static graph to allow calls to Session::Extend.

           {{"value", test::AsScalar<int32>(2)}, {"dtype", DT_INT64}}},
          {{"scale"},
           "Cast",
           {"two"},
           {{"SrcT", DT_INT64}, {"DstT", DT_FLOAT}}},
          {{"y"}, "Mul", {"x", "scale"}, {{"T", DT_FLOAT}}},
      });

  tensorflow::set_tf2_execution(true);
  FunctionDefLibrary flib;
  *flib.add_function() = fd;
  FunctionLibraryDefinition flib_def(OpRegistry::Global(), flib);