// CHECK:           [[VAL_9:%.*]] = "tf.Add"([[VAL_8]], [[VAL_1]]) : (tensor<?x8x10xf32>, tensor<?x10xf32>) -> tensor<?x8x10xf32>
// CHECK:           [[VAL_10:%.*]] = "tf.Add"([[VAL_8]], [[VAL_2]]) : (tensor<?x8x10xf32>, tensor<?x10xf32>) -> tensor<?x8x10xf32>
// CHECK:           [[VAL_11:%.*]] = "tf.Add"([[VAL_1]], [[VAL_2]]) : (tensor<?x10xf32>, tensor<?x10xf32>) -> tensor<?x10xf32>

// CHECK:           %[[VAL_0:.*]] = stablehlo.constant dense<[3, 4]> : tensor<2xi32>
// CHECK:           %[[VAL_1:.*]] = "tfl.custom"(%[[VAL_0]]) <{custom_code = "RandomStandardNormal", custom_option = #tfl<const_bytes : "0x">}> : (tensor<2xi32>) -> tensor<3x4xf32>
// CHECK:           %[[VAL_2:.*]] = stablehlo.tuple %[[VAL_1]] : tuple<tensor<3x4xf32>>
// CHECK:           return %[[VAL_2]] : tuple<tensor<3x4xf32>>
// CHECK:         }

    // CHECK: %[[VAL_1:.*]] = "tfl.reshape"(%[[CONCAT]], %[[VAL_0]]) : (tensor<2xf32>, tensor<2xi32>) -> tensor<2x1xf32>
    // CHECK: return %[[VAL_1]]
  }

	// ppc64x:-"MOVHZ\tR\\d+,\\sR\\d+"
	val16[1] = uint16(sval16[*u16>>2])

}

func setnox(x8 int8, u8 *uint8, y8 *int8, z8 *uint8, x16 *int16, u16 *uint16, x32 *int32, u32 *uint32) {

	// ppc64x:-"MOVBZ\tR\\d+,\\sR\\d+"
	val16[0] = uint16(*u8)

	// AND not needed due to size
	// ppc64x:-"ANDCC"
	sval16[1] = 255 & int16(x8+*y8)

	// ppc64x:-"ANDCC"
	val16[1] = 255 & uint16(*u8+*z8)

		result string
	}{
		{JSONSchemaPropsOrBoolHolder{}, `{"val1":false}`},

		{JSONSchemaPropsOrBoolHolder{JSPoB: JSONSchemaPropsOrBool{Schema: &JSONSchemaProps{}}}, `{"val1":{}}`},
		{JSONSchemaPropsOrBoolHolder{JSPoB: JSONSchemaPropsOrBool{Schema: &JSONSchemaProps{Type: "string"}}}, `{"val1":{"type":"string"}}`},
		{JSONSchemaPropsOrBoolHolder{JSPoB: JSONSchemaPropsOrBool{}}, `{"val1":false}`},

(CMPLconstload {sym} [vo] ptr mem) && vo.Val() != 0 => (CMPLconst (MOVLload {sym} [vo.Off()] ptr mem) [vo.Val()])
(CMPWconstload {sym} [vo] ptr mem) && vo.Val() != 0 => (CMPWconst (MOVWload {sym} [vo.Off()] ptr mem) [vo.Val16()])
(CMPBconstload {sym} [vo] ptr mem) && vo.Val() != 0 => (CMPBconst (MOVBload {sym} [vo.Off()] ptr mem) [vo.Val8()])

// CHECK-SAME:    [[VAL_0:%.*]]: tensor<2xi32>
func.func @inline_with_arg(%arg0 : tensor<2xi32>) -> tensor<2xi32> {
// CHECK-NEXT:  [[VAL_1:%.*]] = tfl.sub [[VAL_0]], [[VAL_0]] {fused_activation_function = "RELU6"} : tensor<2xi32>
// CHECK-NEXT:  [[VAL_2:%.*]] = tfl.add [[VAL_1]], [[VAL_0]] {fused_activation_function = "RELU6"} : tensor<2xi32>
// CHECK-NEXT:  return [[VAL_2]] : tensor<2xi32>

    }
  }
}
versions {
  producer: 175
}

# CHECK: func @main(%[[VAL_0:.*]]: tensor<2x5x3xf32>, %[[VAL_1:.*]]: tensor<3x7xf32>) -> tensor<2x5x7xf32> attributes {tf.entry_function = {control_outputs = "", inputs = "Placeholder,Placeholder_1", outputs = "MatMul"}} {
# CHECK:     %[[VAL_2:.*]] = "tfl.batch_matmul"(%[[VAL_0]], %[[VAL_1]]) <{adj_x = false, adj_y = false}> : (tensor<2x5x3xf32>, tensor<3x7xf32>) -> tensor<2x5x7xf32>

func.func @f() {
  // CHECK: "tf.VarHandleOp"
  // CHECK: "tf.ReadVariableOp"
  %val0 = "tf.VariableV2"() {_class = ["loc:@v"], container = "", device = "", shape = #tf_type.shape<96>, shared_name = ""} : () -> tensor<96x!tf_type.f32ref>
  %val1 = "tf.Identity"(%val0) : (tensor<96x!tf_type.f32ref>) -> tensor<96xf32>
  func.return
}

// -----

// Test case: Basic converting. '_class' attribute is at IdentityOp.

func.func @f() {

				Topology: map[string]string{
					"key1": "val1",
				},
			},
			internal: discovery.Endpoint{
				DeprecatedTopology: map[string]string{
					"key1": "val1",
				},
			},
		},
		{
			desc: "non empty topology map, with zone",
			external: v1beta1.Endpoint{
				Topology: map[string]string{
					"key1":                   "val1",
					corev1.LabelTopologyZone: "zone1",
				},
			},