* Sie können alle gültigen Pydantic-Datentypen hier überprüfen: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.

## Beispiel

Hier ist ein Beispiel für eine *Pfadoperation* mit Parametern, die einige der oben genannten Typen verwenden.

=== "Python 3.10+"

    ```Python hl_lines="1  3  12-16"

	"sort"
	"strings"
	"sync"

	"github.com/tinylib/msgp/msgp"
)

// Recycler will override the internal reuse in typed handlers.
// When this is supported, the handler will not do internal pooling of objects,
// call Recycle() when the object is no longer needed.
// The recycler should handle nil pointers.
type Recycler interface {
	Recycle()
}

// MSS is a map[string]string that can be serialized.

  return std::equal(i1, e1, i2);
}

// This function removes explicit broadcasting on type1 and returns whether if
// the reduced `type1` dimensions are the same as the ending dimensions
// of `type2`.
bool IsReducedTailOfShape(Type type1, Type type2) {
  auto tail_type = mlir::dyn_cast<ShapedType>(type1);
  auto full_type = mlir::dyn_cast<ShapedType>(type2);
  if (!tail_type || !full_type || !tail_type.hasRank() || !full_type.hasRank())

  LOG(FATAL) << "Attempted to execute Op " << name() << " type "
             << type_string() << " on an XLA device. This should never happen.";
}

XlaAssignVariableOp::XlaAssignVariableOp(OpKernelConstruction* c)
    : OpKernel(c) {
  OP_REQUIRES_OK(c, c->GetAttr("dtype", &dtype_));
}

void XlaAssignVariableOp::Compute(OpKernelContext* context) {
  OP_REQUIRES(context, dtype_ == context->input(1).dtype(),

#include "tensorflow/core/framework/types.pb.h"

namespace tensorflow {

TensorSpec::TensorSpec()
    : shape_(std::initializer_list<int64_t>()), dtype_(DT_FLOAT) {}

TensorSpec::TensorSpec(PartialTensorShape shape, DataType dtype)
    : shape_(std::move(shape)), dtype_(dtype) {}

TensorSpec::TensorSpec(const TensorSpecProto& proto)
    : shape_(proto.shape()), dtype_(proto.dtype()) {}

type CharType struct {
	BasicType
}

// A UcharType represents an unsigned character type.
type UcharType struct {
	BasicType
}

// An IntType represents a signed integer type.
type IntType struct {
	BasicType
}

// A UintType represents an unsigned integer type.
type UintType struct {
	BasicType
}

// A FloatType represents a floating point type.
type FloatType struct {

            }

            byte[] type1 = new byte[size];
            int pos = 0;

            System.arraycopy(NTLMSSP_SIGNATURE, 0, type1, 0, NTLMSSP_SIGNATURE.length);
            pos += NTLMSSP_SIGNATURE.length;

            writeULong(type1, pos, NTLMSSP_TYPE1);
            pos += 4;

            writeULong(type1, pos, flags);
            pos += 4;

struct Types {
  typedef internal::Types$n<$for i, [[T$i]]> type;
};

template <>
struct Types<$for i, [[internal::None]]> {
  typedef internal::Types0 type;
};

$range i 1..n-1
$for i [[
$range j 1..i
$range k i+1..n
template <$for j, [[typename T$j]]>
struct Types<$for j, [[T$j]]$for k[[, internal::None]]> {
  typedef internal::Types$i<$for j, [[T$j]]> type;
};

]]

	// +optional
	DefaultMode *int32
}

// VolumeProjection that may be projected along with other supported volume types
type VolumeProjection struct {
	// all types below are the supported types for projection into the same volume

	// information about the secret data to project
	Secret *SecretProjection
	// information about the downwardAPI data to project

		return rv.Bool(), nil
	case reflect.Slice:
		ek := rv.Type().Elem().Kind()
		if ek == reflect.Uint8 {
			return rv.Bytes(), nil
		}
		return nil, fmt.Errorf("unsupported type %T, a slice of %s", v, ek)
	case reflect.String:
		return rv.String(), nil
	}
	return nil, fmt.Errorf("unsupported type %T, a %s", v, rv.Kind())
}

type decimalDecompose interface {