Sonraki bölümler [Tutorial - User Guide: Security](../../tutorial/security/index.md){.internal-link target=_blank} sayfasını okuduğunuzu varsayarak hazırlanmıştır.

    if (mlir::isa<ComplexType>(element_type) ||
        mlir::isa<quant::QuantizedType>(element_type)) {
      return;
    }
    op_builder->setInsertionPoint(const_op);
    Value scalar = op_builder->create<mhlo::ConstantOp>(
        const_op->getLoc(),
        DenseElementsAttr::get(
            RankedTensorType::get(/*shape=*/{}, element_type),
            splat_elements_attr.getSplatValue<Attribute>()));

//
//go:noescape
func p256OrdSqr(res, in *p256OrdElement, n int)

func P256OrdInverse(k []byte) ([]byte, error) {
	if len(k) != 32 {
		return nil, errors.New("invalid scalar length")
	}

	x := new(p256OrdElement)
	p256OrdBigToLittle(x, (*[32]byte)(k))
	p256OrdReduce(x)

	// Inversion is implemented as exponentiation by n - 2, per Fermat's little theorem.
	//

	if isZero(out) {
		return nil, errors.New("crypto/ecdh: bad X25519 remote ECDH input: low order point")
	}
	return out, nil
}

func x25519ScalarMult(dst, scalar, point []byte) {
	var e [32]byte

	copy(e[:], scalar[:])
	e[0] &= 248
	e[31] &= 127
	e[31] |= 64

	var x1, x2, z2, x3, z3, tmp0, tmp1 field.Element
	x1.SetBytes(point[:])
	x2.One()
	x3.Set(&x1)
	z3.One()

	swap := 0

  - nihpo
  - armand-sauzay
  - databento-bot
  - databento
  - nanram22
  - Flint-company
  - porter-dev
  - fern-api
  - ndimares
  - svixhq
  - Alek99
  - codacy
  - zanfaruqui
  - scalar
  - bump-sh
  - andrew-propelauth

  TF_DeleteTensor(result_t);
}

// TODO(srbs): Add tests for captures.
// TODO(srbs): Add tests for polymorphism (different shapes and dtypes).
TEST_P(FunctionTest, Square) {
  // Construct a scalar.
  impl::TaggedValueTensor x = CreateScalarTensor<float, TF_FLOAT>(2.0f);
  FunctionDef fdef = SquareFunc();
  AbstractFunctionPtr trace(new GraphFunction(fdef), /*add_ref=*/false);
  Function tf_function;

	// be a scalar typed field of the child structure (no nesting is supported).
	XListMapKeys []string

	// x-kubernetes-list-type annotates an array to further describe its topology.
	// This extension must only be used on lists and may have 3 possible values:
	//
	// 1) `atomic`: the list is treated as a single entity, like a scalar.

	})
	return {{.p}}GeneratorTable
}

// ScalarBaseMult sets p = scalar * B, where B is the canonical generator, and
// returns p.
func (p *{{.P}}Point) ScalarBaseMult(scalar []byte) (*{{.P}}Point, error) {
	if len(scalar) != {{.p}}ElementLength {
		return nil, errors.New("invalid scalar length")
	}
	tables := p.generatorTable()

	// This is also a scalar multiplication with a four-bit window like in

  }

  auto* ctx = reinterpret_cast<TF_OpKernelContext*>(cc_ctx);
  if (cc_a.dtype() == ::tensorflow::DT_VARIANT) {
    return VariantBinaryAddFunc(
        cc_ctx, cc_a.scalar<Variant>()(), cc_b.scalar<Variant>()(),
        cc_out->scalar<Variant>().data(), binary_add_func);
  } else {
    binary_add_func(ctx, a, b, out);
    return cc_ctx->status();
  }
}

static Status VariantBinaryAddFunc(

      }
    }

    // Special type fixes for scalar tensor types.
    // TFLite flatbuffer schema doesn't distinguish scalar tensor shapes
    // and unranked tensor shapes (i.e. they are both represented as an empty
    // INT32 list), see b/138865275. MLIR importer conservatively treats them as
    // unranked tensor types. Here we set them to scalar tensor types when it is
    // safe.