(Neq32  x y) => (NotEqual (CMPW  x y))
(Neq64  x y) => (NotEqual (CMP   x y))
(NeqPtr x y) => (NotEqual (CMP   x y))
(Neq(32|64)F x y) => (NotEqual (FCMP(S|D) x y))

(Less(8|16) x y) => (LessThan (CMPW (SignExt(8|16)to32 x) (SignExt(8|16)to32 y)))
(Less32 x y) => (LessThan (CMPW x y))
(Less64 x y) => (LessThan (CMP  x y))

// Set condition flags for floating-point comparisons "x < y"

// (t + x) - (t + y) == x - y
// (t + x) - (y + t) == x - y
// (x + t) - (y + t) == x - y
// (x + t) - (t + y) == x - y
// (x - t) + (t + y) == x + y
// (x - t) + (y + t) == x + y
(Sub(64|32|16|8) (Add(64|32|16|8) t x) (Add(64|32|16|8) t y)) => (Sub(64|32|16|8) x y)
(Add(64|32|16|8) (Sub(64|32|16|8) x t) (Add(64|32|16|8) t y)) => (Add(64|32|16|8) x y)

// ^(x-1) == ^x+1 == -x

oltip":0,"links":[],"liveNow":false,"panels":[{"collapsed":false,"datasource":{"type":"prometheus","uid":"${datasource}"},"gridPos":{"h":1,"w":24,"x":0,"y":0},"id":21,"panels":[],"targets":[{"datasource":{"type":"prometheus","uid":"${datasource}"},"refId":"A"}],"title":"Performance Dashboard Notes","type":"row"},{"gridPos":{"h":6,"w":24,"x":0,"y":1},"id":19,"links":[],"options":{"code":{"language":"plaintext","showLineNumbers":false,"showMiniMap":false},"content":"The charts on this dashboard are...

                "value": 80
              }
            ]
          }
        },
        "overrides": []
      },
      "gridPos": {
        "h": 6,
        "w": 12,
        "x": 0,
        "y": 0
      },
      "id": 52,
      "options": {
        "displayMode": "basic",
        "maxVizHeight": 300,
        "minVizHeight": 10,
        "minVizWidth": 0,
        "namePlacement": "auto",

          "$_op.getOperand(" # y #
          ").getType().cast<ShapedType>().getShape()[" # j # "]">]>;

class TFL_OperandsHaveSameDimsTrait<int x, int y, int i, int j> :
  PredOpTrait<"dim " # i # " of operand " # x # " equals to dim " # j #
    " of operand " # y,
    TFL_OperandsHaveSameDims<x, y, i, j>>;

// Return true if number of elements of x-th operand is the same as j-th dim of

var deepEqualPerfTests = []struct {
	x, y any
}{
	{x: int8(99), y: int8(99)},
	{x: []int8{99}, y: []int8{99}},
	{x: int16(99), y: int16(99)},
	{x: []int16{99}, y: []int16{99}},
	{x: int32(99), y: int32(99)},
	{x: []int32{99}, y: []int32{99}},
	{x: int64(99), y: int64(99)},
	{x: []int64{99}, y: []int64{99}},
	{x: int(999999), y: int(999999)},
	{x: []int{999999}, y: []int{999999}},

        };

    // Note that `y` is the divisor if the op is tf.DivNoNan and it is the
    // multiplier if the op is tf.MulNoNan.
    Value y = op.getY();
    // The below if condition is true iff `y.getDefiningOp()` is of the type
    // TF::ConstOp, i.e., if `y` is defined by an op and it is the tf.Const op.
    // In that case, `yDefOp` stores this tf.Const op.

		},
		{
			podWithOrphanFinalizer("pod10"),
			nilOrphanOptions,
			orphanDeleteStrategy,
			false,
			[]string{"foo.com/x", metav1.FinalizerOrphanDependents, "bar.com/y"},
		},
		{
			podWithOtherFinalizers("pod11"),
			nilOrphanOptions,
			defaultDeleteStrategy,
			false,
			[]string{"foo.com/x", "bar.com/y"},
		},
		{

              ),
              tensor_spec.TensorSpec(
                  name='y', shape=shapes[1], dtype=dtypes.float32
              ),
          ]
      )
      def matmul_without_kernel(
          self, x: core.Tensor, y: core.Tensor
      ) -> Mapping[str, core.Tensor]:
        return self._matmul(x, y)

      def _matmul(self, x, y):
        x = array_ops.fake_quant_with_min_max_vars(
            x,

//
// Define “new” code as code with a go.mod file in the same directory
// or a parent directory. If an import in new code says x/y/v2/z but
// x/y/v2/z does not exist and x/y/go.mod says “module x/y/v2”,
// then go build will read the import as x/y/z instead.
// See golang.org/issue/25069.
func moduleImportPath(path, parentPath, parentDir, parentRoot string) (found string) {
	if parentRoot == "" {