// CHECK-NEXT: z.b
// CHECK-NEXT: z.c

// -----

// CHECK-LABEL: @terminator
func.func @terminator(%arg0: f32) -> (f32) attributes {ignore_side_effects_for_testing} {
  func.call @terminator(%arg0) : (f32) -> (f32)
  "x.a"(%arg0) : (f32) -> ()
  "y.a"(%arg0) : (f32) -> ()
  "z.a"(%arg0) : (f32) -> ()
  func.return %arg0 : f32
}
// CHECK: x.a
// CHECK: y.a
// CHECK: z.a
// CHECK: return
// CHECK-NOT: call
// CHECK: }

		// Atomic compare and swap.
		// arg0 = pointer, arg1 = old value, arg2 = new value, arg3 = memory.
		// if *arg0 == arg1 {
		//   *arg0 = arg2
		//   return (true, memory)
		// } else {
		//   return (false, memory)
		// }
		// MOV  $0, Rout
		// LR	(Rarg0), Rtmp
		// BNE	Rtmp, Rarg1, 3(PC)
		// SC	Rarg2, (Rarg0), Rtmp
		// BNE	Rtmp, ZERO, -3(PC)
		// MOV  $1, Rout

// CHECK: %[[dw:.*]] = "tfl.depthwise_conv_2d"(%arg0, %arg1, %arg2)
// CHECK: %[[q:.*]] = "tfl.quantize"(%[[dw]])
// CHECK: %[[dq:.*]] = "tfl.dequantize"(%[[q]])
// CHECK: return %[[dq]], %[[dq]]
}

// Series of values needing requantization -- first the args then the results
// of concatenation operations. concat(concat(arg2, arg0), concat(arg1, arg0)),
// concat(concat(arg2, arg0), arg3)). arg0 should be requantized twice --

		{name: "MOVBloadidx", argLength: 3, reg: gploadidx, commutative: true, asm: "MOVB", aux: "SymOff", typ: "Int8", symEffect: "Read"},      // load a byte from arg0+arg1+auxint+aux. arg2=mem. Sign extend.
		{name: "MOVHZloadidx", argLength: 3, reg: gploadidx, commutative: true, asm: "MOVHZ", aux: "SymOff", typ: "UInt16", symEffect: "Read"},  // load 2 bytes from arg0+arg1+auxint+aux. arg2=mem. Zero extend.

^bb0(%arg0: tensor<8xf32>, %arg3: tensor<f32>, %arg4: tensor<f32>):
  %1 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg3, %arg4) {num_bits = 3, narrow_range = false} : (tensor<8xf32>, tensor<f32>, tensor<f32>) -> tensor<8xf32>
  func.return %1 : tensor<8xf32>

// CHECK: %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
// CHECK: return %0 : tensor<8xf32>
}

	// Memory operations
	{name: "Load", argLength: 2},                          // Load from arg0.  arg1=memory
	{name: "Dereference", argLength: 2},                   // Load from arg0.  arg1=memory.  Helper op for arg/result passing, result is an otherwise not-SSA-able "value".

// CHECK-LABEL: bias_add
func.func @bias_add(%arg0: tensor<1x10x10x32xf32>, %arg1: tensor<32xf32>) -> tensor<1x10x10x32xf32> {
  %0 = "tf.BiasAdd"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NHWC"} : (tensor<1x10x10x32xf32>, tensor<32xf32>) -> tensor<1x10x10x32xf32>
  func.return %0 : tensor<1x10x10x32xf32>

// CHECK-NEXT:  [[ADD_2:%.*]] = "tf.AddV2"(%arg0, [[CST]])
// CHECK-NEXT:  return [[ADD_2]], %arg1, [[ADD]], [[TENSOR_MAP_INSERT_RESULT]]

func.func @otherVariantWhileCond(%arg0: tensor<i32>, %arg1: tensor<i32>, %arg2: tensor<i32>, %arg3: tensor<!tf_type.variant>) -> tensor<i1> {
  %0 = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>

  }
  func.func private @quantized_conv2d_with_bias_and_relu_fn_0(%arg0: tensor<1x3x4x3xi8>, %arg1: tensor<2x3x3x2xi8>, %arg2: tensor<2xi32>, %arg3: tensor<f32>, %arg4: tensor<i32>, %arg5: tensor<f32>, %arg6: tensor<i32>, %arg7: tensor<f32>, %arg8: tensor<i32>, %arg9: tensor<f32>, %arg10: tensor<i32>) -> tensor<1x3x2x2xi8> {
    %cst = "tf.Const"() {value = dense<127> : tensor<i32>} : () -> tensor<i32>

// CHECK-LABEL:func @replicated
// CHECK-SAME: ([[ARG0:%.*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, [[ARG1:%.*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, [[ARG2:%.*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, [[ARG3:%.*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>)