func.return %0 : tensor<1xf32>
  }

// CHECK:   func @simpleTest(%[[VAL_0:.*]]: tensor<1xf32>, %[[VAL_1:.*]]: tensor<1xf32>, %[[VAL_2:.*]]: tensor<1xf32>, %[[VAL_3:.*]]: tensor<1xf32>) -> tensor<2x1xf32> {
// CHECK:           %[[VAL_4:.*]] = call @func_0_GPU_FLOAT(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]) {tac.interface_name = "func_0"} : (tensor<1xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

// CHECK:           [[VAL_6:%.*]] = "tfl.slice"([[VAL_1]], [[VAL_2]], [[VAL_5]]) : (tensor<1x8x8x1024xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<1x8x8x256xf32>
// CHECK:           [[VAL_7:%.*]] = "tfl.slice"([[VAL_1]], [[VAL_3]], [[VAL_5]]) : (tensor<1x8x8x1024xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<1x8x8x256xf32>

// PARTIAL:           %[[VAL_10:.*]] = "tfl.pseudo_const"() <{value = dense<0> : tensor<3xi32>}> : () -> tensor<3xi32>
// PARTIAL:           %[[VAL_11:.*]] = "tfl.slice"(%[[VAL_6]], %[[VAL_10]], %[[VAL_9]]) : (tensor<4x384x32xf32>, tensor<3xi32>, tensor<3xi32>) -> tensor<1x384x32xf32>
// PARTIAL:           return %[[VAL_11]] : tensor<1x384x32xf32>
// PARTIAL:         }

}

// -----

module {

            i1: va11
`,
		},
		{
			desc:     "partial create",
			baseYAML: testTreeYAML,
			path:     "a.b.d",
			value:    "val3",
			want: `
a:
  b:
    c: val1
    d: val3
    list1:
    - i1: val1
    - i2: val2
    - i3a: key1
      i3b:
        list2:
        - i1: val1
        - i2: val2
        - i3a: key1
          i3b:
            i1: va11
`,
		},

func provedUnsignedShiftLeft(val64 uint64, val32 uint32, val16 uint16, val8 uint8, shift int) (r1 uint64, r2 uint32, r3 uint16, r4 uint8) {
	if shift >= 0 && shift < 64 {
		// arm64:"LSL",-"CSEL"
		r1 = val64 << shift
	}
	if shift >= 0 && shift < 32 {
		// arm64:"LSL",-"CSEL"
		r2 = val32 << shift
	}
	if shift >= 0 && shift < 16 {
		// arm64:"LSL",-"CSEL"
		r3 = val16 << shift
	}
	if shift >= 0 && shift < 8 {

        when:
        ModuleComponentSelector result1 = serialize(selector1, serializer)
        ModuleComponentSelector result2 = serialize(selector2, serializer)
        ModuleComponentSelector result3 = serialize(selector3, serializer)

        then:
        result1.attributes == AttributeTestUtil.attributes("foo": "val1")

}

// CHECK-LABEL:   func.func @hardswish(
// CHECK-SAME:                         %[[VAL_0:.*]]: tensor<2xf32>) -> tensor<*xf32> {
// CHECK:           %[[VAL_1:.*]] = "tfl.hard_swish"(%[[VAL_0]]) : (tensor<2xf32>) -> tensor<2xf32>
// CHECK:           %[[VAL_2:.*]] = "tf.Identity"(%[[VAL_1]]) {device = ""} : (tensor<2xf32>) -> tensor<*xf32>
// CHECK:           %[[VAL_3:.*]] = "tf.Identity"(%[[VAL_2]]) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>

					LogFormat: &meshconfig.MeshConfig_ExtensionProvider_EnvoyFileAccessLogProvider_LogFormat_Text{
						Text: "%REQ_WITHOUT_QUERY(key1:val1)% REQ_WITHOUT_QUERY(key2:val1)% %METADATA(UPSTREAM_HOST:istio)% %METADATA(CLUSTER:istio)%\n",
					},
				},
			},
		},
	}

	jsonFormattersProvider = &meshconfig.MeshConfig_ExtensionProvider{
		Name: "envoy-json-formatters",

                     "Uses TF Uniform Quantized ops"))};
};

// Check if given indices in `val1` has same number of elements as given
// indices in `val2`.
bool HasEqualElementSize(Value val1, Value val2, ArrayRef<int> val1_indices,
                         ArrayRef<int> val2_indices) {
  ShapedType val1_shape = mlir::cast<ShapedType>(val1.getType());
  ShapedType val2_shape = mlir::cast<ShapedType>(val2.getType());

	// cond: vo.Val() != 0
	// result: (CMPWconst (MOVWload {sym} [vo.Off()] ptr mem) [vo.Val16()])
	for {
		vo := auxIntToValAndOff(v.AuxInt)
		sym := auxToSym(v.Aux)
		ptr := v_0
		mem := v_1
		if !(vo.Val() != 0) {
			break
		}
		v.reset(OpAMD64CMPWconst)
		v.AuxInt = int16ToAuxInt(vo.Val16())
		v0 := b.NewValue0(v.Pos, OpAMD64MOVWload, typ.UInt16)
		v0.AuxInt = int32ToAuxInt(vo.Off())