}

	configuredPartSize := minPartSize
	// Use floats for part size for all calculations to avoid
	// overflows during float64 to int64 conversions.
	partSizeFlt := float64(objectSize / maxPartsCount)
	partSizeFlt = math.Ceil(partSizeFlt/float64(configuredPartSize)) * float64(configuredPartSize)

	// Part size.
	partSize = int64(partSizeFlt)
	if partSize == 0 {
		return minPartSize, nil
	}
	return partSize, nil
}

// of crashing.
func ceilFrac(numerator, denominator int64) (ceil int64) {
	if denominator == 0 {
		// do nothing on invalid input
		return
	}
	// Make denominator positive
	if denominator < 0 {
		numerator = -numerator
		denominator = -denominator
	}
	ceil = numerator / denominator
	if numerator > 0 && numerator%denominator != 0 {
		ceil++
	}
	return
}

	}

	// Pass in relative days from current time, to additionally
	// to verify "object-lock-remaining-retention-days" policy if any.
	days := int(math.Ceil(math.Abs(objRetention.RetainUntilDate.Sub(t).Hours()) / 24))

	ret := objectlock.GetObjectRetentionMeta(oi.UserDefined)
	if ret.Mode.Valid() {
		// Retention has expired you may change whatever you like.

      // write, we won't see copying because of the new threshold. So it is always OK to use the
      // calculation here.
      return (int) Math.ceil(expectedSize / 0.75);
    }
    return Integer.MAX_VALUE; // any large value
  }

  /**
   * Creates a <i>mutable</i>, empty, insertion-ordered {@code LinkedHashMap} instance.
   *

  return context->GetContextId();
}

void TFE_MonitoringCounterCellIncrementBy(TFE_MonitoringCounterCell* cell,
                                          int64_t value) {
  cell->cell.IncrementBy(value);
}

int64_t TFE_MonitoringCounterCellValue(TFE_MonitoringCounterCell* cell) {
  return cell->cell.value();
}

TFE_MonitoringCounter0* TFE_MonitoringNewCounter0(const char* name,

        checkNotNull(cell.getValue(), "value");
        @SuppressWarnings("unchecked") // all supported methods are covariant
        Cell<R, C, V> immutableCell = (Cell<R, C, V>) cell;
        cells.add(immutableCell);
      } else {
        put(cell.getRowKey(), cell.getColumnKey(), cell.getValue());
      }
      return this;
    }

    /**

Si vous souhaitez un rappel de 2 minutes sur l'utilisation des types en Python (même si vous ne comptez pas utiliser FastAPI), jetez un oeil au tutoriel suivant: [Python Types](python-types.md){.internal-link target=_blank}.

Vous écrivez du python standard avec des annotations de types:

```Python
from datetime import date

from pydantic import BaseModel

		return nil
	}
	w := table.NewStyleWriter(writer)
	w.SetAddRowFunc(func(obj interface{}) table.Row {
		wa := obj.(webhookAnalysis)
		row := table.Row{
			Cells: make([]table.Cell, 0),
		}
		row.Cells = append(row.Cells, table.NewCell(wa.Name), table.NewCell(wa.Revision))
		if wa.Injected {
			row.Cells = append(row.Cells, table.NewCell("✔", color.FgGreen))
		} else {

    *   tf.optimizers => tf.keras.optimizers
    *   Add tf.keras.layers.AbstractRNNCell as the preferred implementation of
        RNN cell for TF v2. User can use it to implement RNN cell with custom
        behavior.
    *   Adding `clear_losses` API to be able to clear losses at the end of
        forward pass in a custom training loop in eager.

- CEL can now correctly handle a CRD `openAPIV3Schema` that has neither `Properties` nor `AdditionalProperties`. ([#121459](https://github.com/kubernetes/kubernetes/pull/121459), [@jiahuif](https://github.com/jiahuif))