class OperandsSameElementTypeConstraintBase<string op> :
  PredOpTrait<op # " operands have same element type",
    OperandsSameElementTypeConstraintBasePred>;

// This is a constraint for most of the binary ops, e.g., add, mul, div, etc.
// Binary ops lhs & rhs should have the same value type, and is capable to
// compare quantization types as well.
def BinaryOpSameElementTypeConstraint :

  // CHECK: "tfl.unidirectional_sequence_lstm"(%arg0,
  // CHECK-SAME: %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg15,
  // CHECK-SAME: %arg16, %arg17, %arg18, %arg19, %arg20, %arg21, %arg22, %arg23) <{cell_clip = 1.000000e+00 : f32, fused_activation_function = "NONE", time_major = false}> :
  // CHECK-SAME: (tensor<?x?x?xf32>,

  let summary = "Form clusters from instructions assigned to same device";
  let constructor = "TFDevice::CreateClusterFormationPass()";
  let dependentDialects = ["tf_device::TensorFlowDeviceDialect"];
  let description = [{
    Clusters operations with the same device assignment id. For each
    cluster, creates a "tf_device.device_launch" op with a Region containing the

// all), or relative or absolute file paths.
//
// - All arguments must have the same version suffix. Different queries are not
// allowed, even if they refer to the same version.
//
// - All arguments must refer to packages in the same module at the same version.
//
// - Package path arguments must refer to main packages. Pattern arguments
// will only match main packages.
//

	// used for storing the uploadID's parsed on concurrent HTTP requests for NewMultipart upload on the same object.
	testUploads := struct {
		sync.Mutex
		uploads []string
	}{}

	objectName := "test-object-new-multipart-parallel"
	var wg sync.WaitGroup
	for i := 0; i < 10; i++ {
		wg.Add(1)
		// Initiate NewMultipart upload on the same object 10 times concurrrently.
		go func() {
			defer wg.Done()

  %0 = "tf.Conv3D"(%arg0, %arg1) {padding = "SAME", strides = [2, 1, 1, 1, 1]} : (tensor<?x?x?x?x?xf32>, tensor<?x?x?x?x?xf32>) -> tensor<?x?x?x?x?xf32>
  func.return %0: tensor<?x?x?x?x?xf32>
  // CHECK-LABEL: conv3d_invalid_strides
  // CHECK:  [[BCT:%.*]] = "tf.Conv3D"(%arg0, %arg1) <{padding = "SAME", strides = [2, 1, 1, 1, 1]}> : (tensor<?x?x?x?x?xf32>, tensor<?x?x?x?x?xf32>) -> tensor<?x?x?x?x?xf32>

			} else {
				ro = append(ro, s)
			}
		}

		// Check that we haven't made two symbols with the same .Outer into
		// different types (because references two symbols with non-nil Outer
		// become references to the outer symbol + offset it's vital that the
		// symbol and the outer end up in the same section).
		for _, s := range relro {
			if outer := ldr.OuterSym(s); outer != 0 {
				st := state.symType(s)

}

// Follow the use chain of TensorList and return true iff all elements written
// to TensorList have same static shape. If all elements have same shape, assign
// it to `potential_element_type`.
//
// This can handle multiple mutations of a TensorList object and would return
// true if across all mutations the elements written have the same shape.
bool CanInferTensorListElementType(Value tensorlist,

	// Get request range.
	var rs *HTTPRangeSpec
	var rangeErr error
	rangeHeader := r.Header.Get(xhttp.Range)
	if rangeHeader != "" {
		// Both 'Range' and 'partNumber' cannot be specified at the same time
		if opts.PartNumber > 0 {
			writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrInvalidRangePartNumber), r.URL)
			return
		}

		rs, rangeErr = parseRequestRangeSpec(rangeHeader)

					t.Fatalf("unexpected requested pod termination: %#v", s)
				}
				// expect we get a pod sync record for kill that should have the same grace period as before (2), but no
				// running pod because the SyncKnownPods method killed it
				if actual, expected := records[uid], []syncPodRecord{
					{name: "pod1", updateType: kubetypes.SyncPodCreate},