/// info

Bedenken Sie, dass Datenklassen nicht alles können, was Pydantic-Modelle können.

Daher müssen Sie möglicherweise weiterhin Pydantic-Modelle verwenden.

Wenn Sie jedoch eine Menge Datenklassen herumliegen haben, ist dies ein guter Trick, um sie für eine Web-API mithilfe von FastAPI zu verwenden. 🤓

///

## Datenklassen als `response_model`

Sie können `dataclasses` auch im Parameter `response_model` verwenden:

  /**
   * The hashtable. Its values are indexes to the keys, values, and entries arrays.
   *
   * <p>Currently, the UNSET value means "null pointer", and any non negative value x is the actual
   * index.
   *
   * <p>Its size must be a power of two.
   */
  private transient int[] table;

  /**
   * Contains the logical entries, in the range of [0, size()). The high 32 bits of each long is the

TF_CAPI_EXPORT extern TF_DataType TF_CheckpointReaderGetVariableDataType(
    TF_CheckpointReader* reader, const char* name);
// Read the shape of a variable and write to `dims`
TF_CAPI_EXPORT extern void TF_CheckpointReaderGetVariableShape(
    TF_CheckpointReader* reader, const char* name, int64_t* dims, int num_dims,
    TF_Status* status);
// Get the number of dimension of a variable
TF_CAPI_EXPORT extern int TF_CheckpointReaderGetVariableNumDims(

    mutated[0]++;
    assertTrue(Arrays.equals(original, hash.asBytes()));
  }

  private static void assertReadableBytes(HashCode hashCode) {
    assertTrue(hashCode.bits() >= 32); // sanity
    byte[] hashBytes = hashCode.asBytes();
    int totalBytes = hashCode.bits() / 8;

    for (int bytes = 0; bytes < totalBytes; bytes++) {
      byte[] bb = new byte[bytes];
      hashCode.writeBytesTo(bb, 0, bb.length);

TF_Tensor* BoolTensor(int32_t v);

// Create a tensor with values of type TF_INT8 provided by `values`.
TF_Tensor* Int8Tensor(const int64_t* dims, int num_dims, const char* values);

// Create a tensor with values of type TF_INT32 provided by `values`.
TF_Tensor* Int32Tensor(const int64_t* dims, int num_dims,
                       const int32_t* values);

// Create 1 dimensional tensor with values from `values`

# Lernen

Hier finden Sie die einführenden Kapitel und Tutorials zum Erlernen von **FastAPI**.

package pubsub

import (
	"math"
	"math/bits"
)

// Mask allows filtering by a bitset mask.
type Mask uint64

const (
	// MaskAll is the mask for all entries.
	MaskAll Mask = math.MaxUint64
)

// MaskFromMaskable extracts mask from an interface.
func MaskFromMaskable(m Maskable) Mask {
	return Mask(m.Mask())
}

// Contains returns whether *all* flags in other is present in t.
func (t Mask) Contains(other Mask) bool {

   * <i>might</i> perform better than its longhand equivalent, but should not perform worse.
   *
   * @since 14.0
   */
  <T extends @Nullable Object> HashCode hashObject(
      @ParametricNullness T instance, Funnel<? super T> funnel);

  /**
   * Returns the number of bits (a multiple of 32) that each hash code produced by this hash
   * function has.
   */
  int bits();

   * <i>might</i> perform better than its longhand equivalent, but should not perform worse.
   *
   * @since 14.0
   */
  <T extends @Nullable Object> HashCode hashObject(
      @ParametricNullness T instance, Funnel<? super T> funnel);

  /**
   * Returns the number of bits (a multiple of 32) that each hash code produced by this hash
   * function has.
   */
  int bits();

    long numeratorAccum = n;
    long denominatorAccum = 1;

    int bits = LongMath.log2(n, CEILING);

    int numeratorBits = bits;

    for (int i = 1; i < k; i++) {
      int p = n - i;
      int q = i + 1;

      // log2(p) >= bits - 1, because p >= n/2

      if (numeratorBits + bits >= Long.SIZE - 1) {
        // The numerator is as big as it can get without risking overflow.