extra // subtraction due to which coefficients were negated. // 5. Rename x and y to a and n, to capture that one is a modulus. // 6. Rearrange steps 4 through 6 slightly. Merge the loops in steps 4 and // 5 into the main loop (step 7's goto), and move step 6 to the start of // the loop iteration, ensuring each loop iteration halves at least one // value. // // Note this algorithm does not handle either input being zero. if a.IsZero() == yes || m.IsZero() == yes { return nil, nil, errors.New("extendedGCD:...

    return CollectSpliterators.indexed(size(), characteristics, this::get);
  }

  @Override
  int copyIntoArray(@Nullable Object[] dst, int offset) {
    // this loop is faster for RandomAccess instances, which ImmutableLists are
    int size = size();
    for (int i = 0; i < size; i++) {
      dst[offset + i] = get(i);
    }
    return offset + size;
  }

  /**

		if err != nil {
			return result, err
		}
	}

	result.ObjectSize, err = latestMeta.ToObjectInfo(bucket, object, true).GetActualSize()
	if err != nil {
		return result, err
	}

	// Loop to find number of disks with valid data, per-drive
	// data state and a list of outdated disks on which data needs
	// to be healed.
	outDatedDisks := make([]StorageAPI, len(storageDisks))

 *  Fix: Don't crash after a web socket fails its connection upgrade. We incorrectly released
    the web socket's connections back to the pool before their resources were cleaned up.

 *  Fix: Don't infinite loop when a received web socket message has self-terminating compressed
    data.

 *  Fix: Don't fail the call when the response code is ‘HTTP 102 Processing’ or ‘HTTP 103 Early
    Hints’.

/// note | Detalles Técnicos

Usó <a href="https://github.com/MagicStack/uvloop" class="external-link" target="_blank">`uvloop`</a> en lugar del loop `asyncio` por defecto de Python. Eso fue lo que lo hizo tan rápido.

Claramente inspiró a Uvicorn y Starlette, que actualmente son más rápidos que Sanic en benchmarks abiertos.

///

/// note | Detalhes Técnicos

Ele utilizava <a href="https://github.com/MagicStack/uvloop" class="external-link" target="_blank">`uvloop`</a> em vez do loop `asyncio` padrão do Python. É isso que o deixava tão rápido.

Ele claramente inspirou Uvicorn e Starlette, que atualmente são mais rápidos que o Sanic em benchmarks abertos.

///

          return this;
        } else if (tableEntry.equals(e)) { // not a new element, ignore
          return this;
        }
      }
      // we fell out of the loop due to a long run; fall back to JDK impl
      return new JdkBackedSetBuilderImpl<E>(this).add(e);
    }

    @Override
    SetBuilderImpl<E> copy() {
      return new RegularSetBuilderImpl<>(this);
    }

func NewEndpoints(args ...string) (endpoints Endpoints, err error) {
	var endpointType EndpointType
	var scheme string

	uniqueArgs := set.NewStringSet()
	// Loop through args and adds to endpoint list.
	for i, arg := range args {
		endpoint, err := NewEndpoint(arg)
		if err != nil {
			return nil, fmt.Errorf("'%s': %s", arg, err.Error())
		}

				globalLocalDrivesMu.Unlock()
			}
			s.erasureDisksMu.Unlock()
		}(endpoint)
	}

	wg.Wait()
}

// monitorAndConnectEndpoints this is a monitoring loop to keep track of disconnected
// endpoints by reconnecting them and making sure to place them into right position in
// the set topology, this monitoring happens at a given monitoring interval.

        scaling with distribution strategy and custom training loops. `AUTO`
        indicates that the reduction option will be determined by the usage
        context. For almost all cases this defaults to `SUM_OVER_BATCH_SIZE`.
        When used in distribution strategy scope, outside of built-in training
        loops such as `tf.keras` `compile` and `fit`, we expect reduction value