}
					atomic.AddInt64(&ops, int64(n))
					atomic.AddInt64(&lat, latency)
				})
				spent := time.Since(t)
				if spent > 0 && n > 0 {
					// Since we are benchmarking n parallel servers we need to multiply by n.
					// This will give an estimate of the total ops/s.
					latency := float64(atomic.LoadInt64(&lat)) / float64(time.Millisecond)
					b.ReportMetric(float64(n)*float64(ops)/spent.Seconds(), "vops/s")

//   ⎡x / c⎤ = ⎣x * m / 2^(n+s)⎦ + 1
// (TODO: derivation?)
//
// The multiply is a bit odd, as it is a signed n-bit value
// times an unsigned n-bit value.  For n smaller than the
// word size, we can extend x and m appropriately and use the
// signed multiply instruction.  For n == word size,
// we must use the signed multiply high and correct
// the result by adding x*2^n.
//

    %16 = stablehlo.subtract %10, %15 : tensor<1x3x3x4xf32>
    %17 = stablehlo.broadcast_in_dim %4, dims = [0, 1, 2, 3] : (tensor<1x1x1x4xf32>) -> tensor<1x3x3x4xf32>
    %18 = stablehlo.multiply %16, %17 : tensor<1x3x3x4xf32>
    %19 = call @uniform_quantize_1(%18, %5, %6) : (tensor<1x3x3x4xf32>, tensor<1x1x1x1xf32>, tensor<1x1x1x1xi8>) -> tensor<1x3x3x4xi8>

	HasAVX512IFMA       bool // Advanced vector extension 512 Integer Fused Multiply Add
	HasAVX512VBMI       bool // Advanced vector extension 512 Vector Byte Manipulation Instructions
	HasAVX5124VNNIW     bool // Advanced vector extension 512 Vector Neural Network Instructions Word variable precision
	HasAVX5124FMAPS     bool // Advanced vector extension 512 Fused Multiply Accumulation Packed Single precision

                        Multiplier multiplier = new Multiplier();
                        Assert.assertEquals(1, multiplier.multiply(1, 1));
                        Assert.assertEquals(4, multiplier.multiply(2, 2));
                        Assert.assertEquals(2, multiplier.multiply(1, 2));
                    }
                }
            """
            file("transitive/build.gradle") << """

  %10 = mhlo.add %arg0, %5 : tensor<2xf32>
  %11 = mhlo.clamp %7, %10, %3 : tensor<2xf32>
  %12 = mhlo.clamp %9, %11, %1 : tensor<2xf32>
  %13 = mhlo.multiply %arg0, %12 : tensor<2xf32>
  %14 = mhlo.divide %13, %1 : tensor<2xf32>
  return %14 : tensor<2xf32>
}

// CHECK-LABEL:   func.func @hardswish(

  static final double LARGE_INTEGER_VALUES_MEAN =
      BigInteger.valueOf(Integer.MAX_VALUE)
          .multiply(BigInteger.valueOf(3L))
          .divide(BigInteger.valueOf(4L))
          .doubleValue();
  static final double LARGE_INTEGER_VALUES_POPULATION_VARIANCE =
      BigInteger.valueOf(Integer.MAX_VALUE)
          .multiply(BigInteger.valueOf(Integer.MAX_VALUE))
          .divide(BigInteger.valueOf(16L))
          .doubleValue();

    def "adds source dependencies Swift module of test component to Xcode indexer search path"() {
        def library = new SwiftLib()
        def test = new SwiftLibTest(library, library.greeter, library.sum, library.multiply)

        given:
        buildTestFixture.withBuildInSubDir()
        singleProjectBuild("greeter") {
            buildFile << """
                apply plugin: 'swift-library'
            """

  // CHECK: %[[CONSTANT2:.*]] = stablehlo.constant dense<1.000000e+03> : tensor<1024x3xf32>
  // CHECK: %[[ADD:.*]] = stablehlo.add %[[INPUT1]], %[[CONSTANT2]] : tensor<1024x3xf32>
  // CHECK: %[[MUL:.*]] = stablehlo.multiply %[[INPUT1]], %[[INPUT2]] : tensor<1024x3xf32>
  // CHECK: return %[[ADD]], %[[MUL]]
  // CHECK: }

  // CHECK: @serving_default

    18: 0000000000403dc0     0 OBJECT  LOCAL  DEFAULT   20 __frame_dummy_in[...]
    19: 0000000000000000     0 FILE    LOCAL  DEFAULT  ABS sum.cpp
    20: 0000000000000000     0 FILE    LOCAL  DEFAULT  ABS multiply.cpp
    21: 0000000000000000     0 FILE    LOCAL  DEFAULT  ABS crtstuff.c
    22: 00000000004021e0     0 OBJECT  LOCAL  DEFAULT   19 __FRAME_END__
    23: 0000000000000000     0 FILE    LOCAL  DEFAULT  ABS