if (!IsBroadcastableElementsAttrAndType(new_type, filter.getType())) {
      return failure();
    }

    auto new_op =
        rewriter.create<arith::ConstantOp>(mul_op.getLoc(), new_type, new_cst);
    Value new_const_val = new_op.getResult();

    // Rewrite. Since the folder of TFL::MulOp couldn't broadcast the operands,
    // TF::MulOp is used to fold the constant.

//   - github.com/cloudwego/frugal
//
// Do not remove or change the type signature.
// See go.dev/issue/67401.
//
//go:linkname step
func step(p []byte, pc *uintptr, val *int32, first bool) (newp []byte, ok bool) {
	// For both uvdelta and pcdelta, the common case (~70%)
	// is that they are a single byte. If so, avoid calling readvarint.
	uvdelta := uint32(p[0])
	if uvdelta == 0 && !first {

		} else {
			for i := range expected[x] {
				newEp := newMap[x][i]
				if newEp.String() != expected[x][i].endpoint ||
					newEp.IsLocal() != expected[x][i].isLocal {
					t.Errorf("[%d] expected new[%v][%d] to be %v, got %v", tci, x, i, expected[x][i], newEp)
				}
			}
		}
	}
}

func TestUpdateEndpointsMap(t *testing.T) {

		n := n.(*ir.UnaryExpr)
		a := s.expr(n.X)
		if n.Type().IsComplex() {
			tp := types.FloatForComplex(n.Type())
			negop := s.ssaOp(n.Op(), tp)
			return s.newValue2(ssa.OpComplexMake, n.Type(),
				s.newValue1(negop, tp, s.newValue1(ssa.OpComplexReal, tp, a)),
				s.newValue1(negop, tp, s.newValue1(ssa.OpComplexImag, tp, a)))
		}
		return s.newValue1(s.ssaOp(n.Op(), n.Type()), a.Type, a)
	case ir.ONOT, ir.OBITNOT:

};

#include "tensorflow/compiler/mlir/tensorflow/transforms/generated_canonicalize.inc"
}  // namespace

INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(NcclAllReduceOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(NegOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(OnesLikeOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(PreventGradientOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(QuantizeAndDequantizeOp);

    //  move downwards towards the subdiagonals. So the start indices will
    //  be decreasing.)
    Value d = rewriter.create<SubtractOp>(loc, b_k1, iotaM);
    Value neg_d = rewriter.create<NegOp>(loc, d);

    // diag_len_d = min(rows + min(d, 0), cols - max(d, 0))
    // (Length of a diagonal for a given d. Same as max_diag_len for m = 0.)
    Value diag_len_d = rewriter.create<MinOp>(
        loc,

onRotateEnd_(e){this.rotating_=false;},getMousePosition_(e){const rect=tr.ui.b.windowRectForElement(this.canvas_);return[(e.clientX-rect.x)*this.pixelRatio_,(e.clientY-rect.y)*this.pixelRatio_];},getMouseDelta_(e,p){const newP=this.getMousePosition_(e);return[newP[0]-p[0],newP[1]-p[1]];},dispatchRenderEvent_(){tr.b.dispatchSimpleEvent(this,'renderrequired',false,false);}};return{Camera,};});'use strict';tr.exportTo('tr.ui.b',function(){const THIS_DOC=document.currentScript.ownerDocument;const co...