io32[1] = io32[1] & 0xF0000FFF
	// ppc64x: -"RLWNM", MOVD, AND
	io32[2] = io32[2] & 0xFFFF0002

	var bigc uint32 = 0x12345678
	// ppc64x: "ANDCC\t[$]22136"
	io16[0] = io16[0] & uint16(bigc)

	// ppc64x: "ANDCC\t[$]120"
	io8[0] = io8[0] & uint8(bigc)

  func.return %2 : tensor<1x1xf32>

// CHECK: %[[q1:.*]] = "tfl.quantize"(%arg0) <{qtype = tensor<1x1x!quant.uniform<i16:f32, {{.*}}>>}> {volatile} : (tensor<1x1xf32>) -> tensor<1x1x!quant.uniform<i16:f32, {{.*}}>>
// CHECK-NEXT: %[[dq1:.*]] = "tfl.dequantize"(%[[q1]]) : (tensor<1x1x!quant.uniform<i16:f32, {{.*}}>>) -> tensor<1x1xf32>
// CHECK-NEXT: %[[sm:.*]] = "tfl.softmax"(%[[dq1]]) <{{{.*}}}> : (tensor<1x1xf32>) -> tensor<1x1xf32>

tensor<640x!quant.uniform<i32:f32, 1.601389680352559E-4>>, %arg15: tensor<2048x!quant.uniform<i16:f32, 4.3700000969693065E-4>>, %arg16: tensor<2048x!quant.uniform<i16:f32, 1.1000000085914508E-4>>, %arg17: tensor<2048x!quant.uniform<i16:f32, 1.6799999866634607E-4>>, %arg18: tensor<2048x!quant.uniform<i16:f32, 1.55999994603917E-4>>, %arg19: tensor<1x640x!quant.uniform<i8:f32, 0.09671100229024887:10>>, %arg20: tensor<1x2048x!quant.uniform<i16:f32, 4.8799999058246613E-4>>) -> tensor<1x640x!quant.uniform<i8:f32, 0.09671100229024887:10>>...

// CHECK-SAME: input_to_cell_intermediate = tensor<!quant.uniform<i16<-32767:32767>:f32, 1.2207403790398877E-4>>
// CHECK-SAME: input_to_forget_intermediate = tensor<!quant.uniform<i16<-32767:32767>:f32, 4.8829615161595508E-4>>
// CHECK-SAME: input_to_input_intermediate = tensor<!quant.uniform<i16<-32767:32767>:f32, 9.7659230323191015E-4>>
// CHECK-SAME: input_to_output_intermediate = tensor<!quant.uniform<i16<-32767:32767>:f32, 3.0518509475997192E-5>>

}

// CHECK-LABEL: testAddInt16
func.func @testAddInt16(tensor<? x i16>, tensor<? x i16>) -> tensor<? x i16> {
^bb0(%arg0: tensor<? x i16>, %arg1: tensor<? x i16>):
  // CHECK: tfl.add %arg0, %arg1 {fused_activation_function = "RELU6"}
  %0 = tfl.add %arg0, %arg1 {fused_activation_function = "RELU6"} : tensor<? x i16>
  func.return %0#0 : tensor<? x i16>
}

// CHECK-LABEL: testSub

    Results are always sorted in the descending order.
  }];

  let arguments = (ins
    TFL_TensorOf<[F32, I8, I16, I32, I64, UI8, QI8, QUI8]>:$input,
    TFL_TensorOf<[I16, I32]>:$k);

  let results = (outs
    TFL_TensorOf<[F32, I8, I16, I32, I64, UI8, QI8, QUI8]>:$values,
    TFL_TensorOf<[I16, I32]>:$indices);

  let builders = [
    OpBuilder<(ins "Value":$input, "Value":$k),

    %12 = "mhlo.compare"(%arg1, %arg3) {comparison_direction = #mhlo<comparison_direction LT>} : (tensor<i16>, tensor<i16>) -> tensor<i1>
    %13 = "mhlo.select"(%12, %arg1, %arg3) : (tensor<i1>, tensor<i16>, tensor<i16>) -> tensor<i16>
    %14 = "mhlo.compare"(%arg1, %arg3) {comparison_direction = #mhlo<comparison_direction EQ>} : (tensor<i16>, tensor<i16>) -> tensor<i1>

		isZeros(ip[0:10]) &&
		ip[10] == 0xff &&
		ip[11] == 0xff {
		return ip[12:16]
	}
	return nil
}

// To16 converts the IP address ip to a 16-byte representation.
// If ip is not an IP address (it is the wrong length), To16 returns nil.
func (ip IP) To16() IP {
	if len(ip) == IPv4len {
		return IPv4(ip[0], ip[1], ip[2], ip[3])
	}
	if len(ip) == IPv6len {
		return ip
	}
	return nil

  func.return %2 : tensor<1x32x32x16x!quant.uniform<i16:f32, 1.0>>
}

// -----

// CHECK-LABEL: @test_conv2d_replace_qi8

  %1 = "tfl.dequantize"(%0) : (tensor<2x1x!quant.uniform<i16:f32, 1.0>>) -> (tensor<2x1xf32>)
  %2 = "tfl.quantize"(%arg1) {qtype = tensor<2x3x!quant.uniform<i16:f32, 1.0>>} : (tensor<2x3xf32>) -> tensor<2x3x!quant.uniform<i16:f32, 1.0>>
  %3 = "tfl.dequantize"(%2) : (tensor<2x3x!quant.uniform<i16:f32, 1.0>>) -> (tensor<2x3xf32>)