}

// CHECK-LABEL:   func.func @avg_pool2d_1(
// CHECK-SAME:                            %[[VAL_0:.*]]: tensor<1x3x6x6xf32>) -> tensor<*xf32> {
// CHECK:           %[[VAL_1:.*]] = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32>
// CHECK:           %[[VAL_2:.*]] = "tfl.transpose"(%[[VAL_0]], %[[VAL_1]]) : (tensor<1x3x6x6xf32>, tensor<4xi32>) -> tensor<1x6x6x3xf32>
// CHECK:           %[[VAL_3:.*]] = arith.constant dense<0> : tensor<4x2xi32>

// CHECK-LABEL: func @transposeConv2D
func.func @transposeConv2D(%arg0: tensor<1x3x32x32xf32>, %arg1: tensor<1x1x3x8xf32>) -> tensor<1x8x32x32xf32> {

  // Convert input: NCHW -> NHWC
  %0 = "tf.Const"() {value = dense<[0, 2, 3, 1]> : tensor<4xi32>} : () -> tensor<4xi32>
  %1 = "tf.Transpose"(%arg0, %0) : (tensor<1x3x32x32xf32>, tensor<4xi32>) -> tensor<1x32x32x3xf32>

  // Compute in NHWC
  %2 = "tf.Conv2D"(%1, %arg1)
    {

}

SmallVector<int64_t, 4> GetDataFormatPermutation(StringRef from, StringRef to) {
  if (from == "NHWC" && to == "NCHW") {
    return {0, 3, 1, 2};
  } else if (from == "NCHW" && to == "NHWC") {
    return {0, 2, 3, 1};
  } else {
    return {};
  }
}

// Shuffle elements in the `attr` according to the permutation. Optional
// `inner_size` allows to shuffle array attributes created from rank 2 tensors

}


func f9(a int) (in int, fl float64) {
	i := 9
	f := float64(9)
	return i, f
}


func main() {
	f1()
	f2(1)
	r3 := f3(1, 2)
	assertequal(r3, 3, "3")
	r4 := f4(0, 2, 3.0)
	assertequal(r4, 4, "4")
	r5 := f5(1)
	assertequal(r5, 5, "5")
	r6 := f6(1)
	assertequal(r6, 6, "6")
	var r7 int
	var s7 float64
	r7, s7 = f7(1)
	assertequal(r7, 7, "r7")
	assertequal(int(s7), 7, "s7")

	return (t.x + a) * (t.y + int(b))
}


func f9(a int) (i int, f float32) {
	i = 9
	f = 9.0
	return
}


func main() {
	f1()
	f2(1)
	r3 := f3(1, 2)
	assertequal(r3, 3, "3")
	r4 := f4(0, 2, 3.0)
	assertequal(r4, 4, "4")
	r5 := f5(1)
	assertequal(r5, 5, "5")
	r6 := f6(1)
	assertequal(r6, 6, "6")
	r7, s7 := f7(1)
	assertequal(r7, 7, "r7")
	assertequal(int(s7), 7, "s7")
	r8, s8 := f8(1)

        request.setParameter("geo.location.2.distance", "1km");

        final GeoInfo geoInfo = new GeoInfo(request);
        String result =

  %cst_0 = "tf.Const"() {device = "", value = dense<[0, 3, 1, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
  %cst_1 = "tf.Const"() {_tpu_replicate = "cluster", device = "", value = dense<[0, 2, 3, 1]> : tensor<4xi32>} : () -> tensor<4xi32>
  %0 = "tf.Cast"(%arg0) {Truncate = false, device = ""} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xbf16>

  %input_scale = "tf.Const"() { value = dense<0.588> : tensor<f32> } : () -> tensor<f32>
  %input_zp = "tf.Const"() { value = dense<42> : tensor<i32> } : () -> tensor<i32>
  %filter_scale = "tf.Const"() { value = dense<0.0235> : tensor<f32> } : () -> tensor<f32>
  %filter_zp = "tf.Const"() { value = dense<0> : tensor<i32> } : () -> tensor<i32>
  %accum_scale = "tf.Const"() { value = dense<0.013818> : tensor<f32> } : () -> tensor<f32>

			}
		})
	}
}

// BenchmarkMarshalCorpusFile measures the time it takes to serialize byte
// slices of various sizes to a corpus file. The slice contains a repeating
// sequence of bytes 0-255 to mix escaped and non-escaped characters.
func BenchmarkMarshalCorpusFile(b *testing.B) {
	buf := make([]byte, 1024*1024)
	for i := 0; i < len(buf); i++ {
		buf[i] = byte(i)
	}

}
// CHECK-SAME: (%[[ARG_0:.+]]: tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32>
// CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant
// CHECK-DAG: %[[TRANSPOSE_0:.+]] = stablehlo.transpose %[[CONST_0]], dims = [0, 2, 3, 1] : (tensor<1x4x3x3xf32>) -> tensor<1x3x3x4xf32>

// Check that the shape of the add is changed to reflect the deferred transpose.
// CHECK: %[[ADD_0:.+]] = stablehlo.add %[[ARG_0]], %[[TRANSPOSE_0]] : tensor<1x3x3x4xf32>