// We cannot fuse this tfl.mul into the preceding conv op because %cst2 is not broadcast-compatible to %cst0.
  %1 = "tfl.mul"(%0, %cst2) {fused_activation_function = "RELU6"} : (tensor<1x4x4x2xf32>, tensor<4x2xf32>) -> tensor<1x4x4x2xf32>

  func.return %1 : tensor<1x4x4x2xf32>

// CHECK:  %0 = "tfl.depthwise_conv_2d"(%arg0, %cst, %cst_0)
// CHECK:  %1 = tfl.mul(%0, %cst_1)
// CHECK:  return %1
}

  %178 = "tf.Pack"(%7, %177) {axis = 0 : i64, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<2xi32>
  %179 = "tf.Tile"(%115, %178) {device = ""} : (tensor<?x1xi64>, tensor<2xi32>) -> tensor<?x?xi64>
  %180 = "tf.Mul"(%177, %118) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %181 = "tf.Pack"(%180) {axis = 0 : i64, device = ""} : (tensor<i32>) -> tensor<1xi32>

  // CHECK-NEXT: %[[sub:.*]] = mhlo.subtract %[[act]], %[[bcast_arg3]] : tensor<8x8x8x8xf32>
  // CHECK-NEXT: %[[mul:.*]] = mhlo.multiply %[[grad]], %[[sub]] : tensor<8x8x8x8xf32>
  // CHECK-NEXT: mhlo.constant dense<[0, 1, 2]> : tensor<3xi64>
  // CHECK-NEXT: %[[cmul:.*]] = mhlo.convert %[[mul]] : tensor<8x8x8x8xf32>
  // CHECK-NEXT: %[[init:.*]] = mhlo.constant dense<-0.000000e+00> : tensor<f32>

}

// CHECK-LABEL:   func @mul(
// CHECK-SAME:              %[[VAL_0:.*]]: tensor<2xi32>) -> tensor<2xi32> {
// CHECK:           %[[VAL_1:.*]] = "tf.Mul"(%[[VAL_0]], %[[VAL_0]]) : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
// CHECK:           return %[[VAL_1]] : tensor<2xi32>
// CHECK:         }
func.func @mul(%arg0: tensor<2xi32>) -> tensor<2xi32> {

			loopHead := s.f.NewBlock(ssa.BlockPlain)
			loopBody := s.f.NewBlock(ssa.BlockPlain)

			// Pick right size ops.
			var mul, and, add, zext ssa.Op
			if s.config.PtrSize == 4 {
				mul = ssa.OpMul32
				and = ssa.OpAnd32
				add = ssa.OpAdd32
				zext = ssa.OpCopy
			} else {
				mul = ssa.OpMul64
				and = ssa.OpAnd64
				add = ssa.OpAdd64
				zext = ssa.OpZeroExt32to64
			}

    StringRef reduce_op = op.getReduceOp();
    if (reduce_op == "Add") {
      BuildReduceBody<AddOp>(element_type, &reduce_scatter.getComputation(),
                             &rewriter);
    } else if (reduce_op == "Mul") {
      BuildReduceBody<MulOp>(element_type, &reduce_scatter.getComputation(),
                             &rewriter);
    } else if (reduce_op == "Min") {

n|max)-resolution(\s*:\s*)(\d*\.?\d+)(dppx|dpcm|dpi|x)/i,_m=class extends B2{prefixName(e,t){return e==="-moz-"?t+"--moz-device-pixel-ratio":e+t+"-device-pixel-ratio"}prefixQuery(e,t,r,n,a){return n=new M2(n),a==="dpi"?n=n.div(96):a==="dpcm"&&(n=n.mul(2.54).div(96)),n=n.simplify(),e==="-o-"&&(n=n.n+"/"+n.d),this.prefixName(e,t)+r+n}clean(e){if(!this.bad){this.bad=[];for(let t of this.prefixes)this.bad.push(this.prefixName(t,"min")),this.bad.push(this.prefixName(t,"max"))}e.params=Wo.editList(e.p...