//go:build arm || wasm

// Export some functions via linkname to assembly in sync/atomic.
//
//go:linkname And32
//go:linkname Or32
//go:linkname And64
//go:linkname Or64
//go:linkname Anduintptr
//go:linkname Oruintptr

package atomic

import _ "unsafe" // For linkname

//go:nosplit
func And32(ptr *uint32, val uint32) uint32 {
	for {
		old := *ptr
		if Cas(ptr, old, old&val) {
			return old
		}
	}

// CHECK-EMPTY:
// CHECK-NEXT:        },
// CHECK-NEXT:        has_rank: true
// CHECK-NEXT:      }, {
// CHECK-NEXT:        shape: [ 3, 2 ],
// CHECK-NEXT:        buffer: 2,
// CHECK-NEXT:        name: "tf.AddV2",
// CHECK-NEXT:        quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:        },
// CHECK-NEXT:        has_rank: true
// CHECK-NEXT:      } ],
// CHECK-NEXT:      inputs: [ 0 ],
// CHECK-NEXT:      outputs: [ 1 ],

  // CHECK: [[handle:%.*]] = "tf.VarHandleOp"()
  // CHECK: "tf.ReadVariableOp"([[handle]])
  %0 = "tf.ReadVariableOp"(%arg1) {device = "/device:CPU:0"} : (tensor<*x!tf_type.resource>) -> tensor<1x3xf32>
  %1 = "tf.AddV2"(%arg0, %0) {device = "/device:CPU:0"} : (tensor<1x3xf32>, tensor<1x3xf32>) -> tensor<1x3xf32>
  %2 = "tf.Identity"(%1) {device = "/device:CPU:0"} : (tensor<1x3xf32>) -> tensor<1x3xf32>
  func.return %2 : tensor<1x3xf32>
}

// CANON:             [[VAL_14:%.*]] = "tf.AddV2"([[VAL_12]], [[VAL_4]])
// CANON:             [[VAL_15:%.*]] = "tf.AddV2"([[VAL_13]], [[VAL_5]])
// CANON:             [[VAL_16:%.*]] = "tf.AddV2"([[VAL_11]], [[VAL_4]])
// CANON:             "tfl.yield"([[VAL_16]], [[VAL_14]], [[VAL_15]]) : (tensor<*xi32>, tensor<*xi32>, tensor<*xf32>) -> ()

// CHECK-DAG: %[[cst_0:.*]] = "tf.Const{{.*}} dense<1.200000e+01> : tensor<16xf32>
// CHECK-NEXT: %[[conv:.*]] = "tf.Conv2D"(%arg0, %[[cst]])
// CHECK-NEXT: %[[bias:.*]] = "tf.AddV2"(%[[conv]], %[[cst_0]])
// CHECK-NEXT: return %[[bias]] : tensor<256x8x7x16xf32>
}

// CHECK-LABEL: convaddv2mul
func.func @convaddv2mul(%arg: tensor<256x32x32x3xf32>) -> tensor<256x8x7x16xf32> {

  }

  func.func @while_body_add2(%arg0: tensor<i32>, %arg1: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
    %0 = "tf.Const"() {device = "/device:CPU:0", value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %1 = "tf.AddV2"(%arg0, %0) {device = "/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %2 = "tf.Div"(%arg1, %0) {device = "/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
    func.return %1, %2 : tensor<i32>, tensor<i32>

}

// CHECK-LABEL: add
func.func @add(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
  %0 = "tf.AddV2"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  func.return %0: tensor<1xf32>
// CHECK: %[[ADD_0:.*]] = "tf.AddV2"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
// CHECK: return %[[ADD_0]] : tensor<1xf32>
}

// CHECK-LABEL: softmax

	"testing"
)

func TestConvertMemProfile(t *testing.T) {
	addr1, addr2, map1, map2 := testPCs(t)

	// MemProfileRecord stacks are return PCs, so add one to the
	// addresses recorded in the "profile". The proto profile
	// locations are call PCs, so conversion will subtract one
	// from these and get back to addr1 and addr2.
	a1, a2 := uintptr(addr1)+1, uintptr(addr2)+1
	rate := int64(512 * 1024)
	rec := []profilerecord.MemProfileRecord{

//                  Mul                              AddV2
// This is to enable the FuseMulAndConv2D pattern.
// Here, root of the result is AddV2 instead of BiasAdd because the value may
// not have rank one and therefore the second operand may not have rank one
// that is required by the BiasAdd. BiasAdd with 'NHWC' data format equivalent
// to AddV2 op.
def PassthroughMulAndBiasAdd :
  Pat<(TF_MulOp

			default:
				return v.ptr
			}
		}
		addr1 := ptrval(v1)
		addr2 := ptrval(v2)
		if uintptr(addr1) > uintptr(addr2) {
			// Canonicalize order to reduce number of entries in visited.
			// Assumes non-moving garbage collector.
			addr1, addr2 = addr2, addr1
		}

		// Short circuit if references are already seen.
		typ := v1.Type()
		v := visit{addr1, addr2, typ}
		if visited[v] {
			return true
		}