"tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",
            "lineWidth": 1,
            "pointSize": 5,
            "scaleDistribution": {
              "type": "linear"
            },
            "showPoints": "never",
            "spanNulls": false,
            "stacking": {
              "group": "A",

              "tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",
            "lineWidth": 1,
            "pointSize": 5,
            "scaleDistribution": {
              "type": "linear"
            },
            "showPoints": "never",
            "spanNulls": false,
            "stacking": {
              "group": "A",

   //   (multiply_linear_by_lr ? clamp(-l1 * lr, linear, l1 * lr)
   //                            clamp(-l1, linear, l1)) - linear
   (TF_SubOp:$linear_clipped_minus_linear
     (ConstAttrIfThenElse
       $multiply_linear_by_lr,
       (Clamp $src_op,
         (TF_NegOp (TF_MulOp $l1, $lr)),
         (CreateTFReadVariableOp $src_op, $l1, $linear),
         (TF_MulOp $l1, $lr)
       ),
       (Clamp $src_op,

///     Scope linear = root.NewSubScope("linear");
///     // W will be named "linear/W"
///     auto W = Variable(linear.WithOpName("W"),
///                       {2, 2}, DT_FLOAT);
///     // b will be named "linear/b_3"
///     int idx = 3;
///     auto b = Variable(linear.WithOpName("b_", idx),
///                       {2}, DT_FLOAT);
///     auto x = Const(linear, {...});  // name: "linear/Const"

              "tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",
            "lineWidth": 1,
            "pointSize": 5,
            "scaleDistribution": {
              "type": "linear"
            },
            "showPoints": "never",
            "spanNulls": true,
            "stacking": {
              "group": "A",

              "tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",
            "lineWidth": 1,
            "pointSize": 5,
            "scaleDistribution": {
              "type": "linear"
            },
            "showPoints": "never",
            "spanNulls": false,
            "stacking": {
              "group": "A",

xt","axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"insertNulls":false,"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"type":"linear"},"showPoints":"never","spanNulls":false,"stacking":{"group":"A","mode":"none"},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[{"color":"green","value":null},{"color":"red"...

	// Insert regardless of whether we have a match in m.pcs.
	// Even if we have a match, we want to keep the newest version
	// of that stack, since we're much more likely tos see it again
	// as we iterate through the trace linearly. Simultaneously, we
	// are likely to never see the old stack again.
	m.pcs[pcs] = stack
	m.stacks[stack] = rec
	return rec
}

func (m *stackMap) profile() []traceviewer.ProfileRecord {

	// In both cases the algorithm is a linear scan over the two
	// lists - T's methods and V's methods - simultaneously.
	// Since method tables are stored in a unique sorted order
	// (alphabetical, with no duplicate method names), the scan
	// through V's methods must hit a match for each of T's
	// methods along the way, or else V does not implement T.
	// This lets us run the scan in overall linear time instead of

// CHECK-LABEL: testResourceApplyFtrl
func.func @testResourceApplyFtrl(%var: tensor<*x!tf_type.resource>, %accum: tensor<*x!tf_type.resource>, %linear: tensor<*x!tf_type.resource>, %grad: tensor<*xf32>, %lr: tensor<*xf32>, %l1: tensor<*xf32>, %l2: tensor<*xf32>, %lr_power: tensor<*xf32>) -> () {