maxs[channel_index] = std::max(maxs[channel_index], ele_value);
    }
    // Expand range to include 0.
    for (int i = 0; i < dim_size; ++i) {
      maxs[i] = std::max(maxs[i], 0.0);
      mins[i] = std::min(mins[i], 0.0);
    }
    if (symmetric) {
      for (int i = 0; i < dim_size; ++i) {
        maxs[i] = std::max(std::abs(mins[i]), std::abs(maxs[i]));
        mins[i] = -maxs[i];

        mins.push_back(rmin);
        maxs.push_back(rmax);
      }
      quant_type = quantfork::fakeQuantAttrsToType(
          op.getLoc(), num_bits, *op.getAxis(), mins, maxs, narrow_range,
          expressed, is_signed);
      if (legacy_float_scale) {
        quant_type = DownCastScale(quant_type, mins, maxs, op->getLoc());
      }
    } else if (auto stats =

      SmallVector<double, 4> mins(1, std::numeric_limits<double>::max());
      SmallVector<double, 4> maxs(1, std::numeric_limits<double>::min());
      // Computes the effective min/max values of the attribute values.
      quant::ExtractMinMaxFromAttr(attr, /*dim_size=*/1, /*slice_size=*/1,
                                   /*symmetric=*/true, mins, maxs);
      double scale = maxs[0] / -llvm::minIntN(tensor_property.number_of_bits);

                    Map<String, String> map = Maps.newHashMap();
                    putEntries(map, entries);
                    map.putAll(ENTRIES_TO_FILTER);
                    map = Maps.filterEntries(map, FILTER_ENTRIES_1);
                    return Maps.filterEntries(map, FILTER_ENTRIES_2);
                  }
                })
            .named("Maps.filterEntries[Maps.filterEntries[Map, Predicate], Predicate]")

    assertEquals(Maps.immutableEntry("foo", 5), entryIterator.next());
    assertEquals(Maps.immutableEntry("bar", 4), entryIterator.next());
    assertEquals(Maps.immutableEntry("foo", 3), entryIterator.next());
    assertEquals(Maps.immutableEntry("cow", 2), entryIterator.next());
    assertEquals(Maps.immutableEntry("bar", 1), entryIterator.next());

    }

    @Override
    Set<K> createKeySet() {
      @WeakOuter
      class KeySetImpl extends Maps.KeySet<K, Collection<V>> {
        KeySetImpl() {
          super(AsMap.this);
        }

        @Override
        public boolean removeAll(Collection<?> c) {
          return removeEntriesIf(Maps.<K>keyPredicateOnEntries(in(c)));
        }

        @Override

    }

    @Override
    Set<K> createKeySet() {
      @WeakOuter
      class KeySetImpl extends Maps.KeySet<K, Collection<V>> {
        KeySetImpl() {
          super(AsMap.this);
        }

        @Override
        public boolean removeAll(Collection<?> c) {
          return removeEntriesIf(Maps.<K>keyPredicateOnEntries(in(c)));
        }

        @Override

    assertFalse(entrySet.remove(Maps.immutableEntry(10, 'X')));
    assertTrue(entrySet.remove(Maps.immutableEntry(20, 'X')));
    assertFalse(entrySet.remove(Maps.immutableEntry(15, 'X')));
    entrySet = row.entrySet();
    assertTrue(entrySet.remove(Maps.immutableEntry(10, 'X')));
    assertFalse(entrySet.remove(Maps.immutableEntry(20, 'X')));
    assertFalse(entrySet.remove(Maps.immutableEntry(15, 'X')));
  }

#### Burgers parallèles

Imaginons désormais que ce ne sont pas des "burgers concurrents" mais des "burgers parallèles".

Vous allez avec votre crush 😍 dans un fast food 🍔 parallélisé.

        ImmutableList.of(
            Maps.immutableEntry("foo", 99),
            Maps.immutableEntry("foo", 88),
            Maps.immutableEntry("bar", 77));

    for (final int startIndex : new int[] {0, 3, 5}) {
      List<Entry<String, Integer>> list =
          Lists.newArrayList(
              Maps.immutableEntry("foo", 2),
              Maps.immutableEntry("foo", 3),