return new RegularImmutableBiMap<K, V>(
        new Object[] {
          k1, v1, k2, v2, k3, v3, k4, v4, k5, v5, k6, v6, k7, v7, k8, v8, k9, v9, k10, v10
        },
        10);
  }

  // looking for of() with > 10 entries? Use the builder or ofEntries instead.

  /**
   * Returns an immutable map containing the given entries, in order.
   *

    builder.put(k1, v1);
    builder.put(k2, v2);
    builder.put(k3, v3);
    builder.put(k4, v4);
    builder.put(k5, v5);
    return builder.build();
  }

  // looking for of() with > 5 entries? Use the builder instead.

  /**
   * Returns a new builder. The generated builder is equivalent to the builder created by the {@link
   * Builder} constructor.
   */

    builder.put(k1, v1);
    builder.put(k2, v2);
    builder.put(k3, v3);
    builder.put(k4, v4);
    builder.put(k5, v5);
    return builder.build();
  }

  // looking for of() with > 5 entries? Use the builder instead.

  /** Returns a new {@link Builder}. */
  public static <K, V> Builder<K, V> builder() {
    return new Builder<>();
  }

  /**

    return RegularImmutableMap.create(
        10,
        new Object[] {
          k1, v1, k2, v2, k3, v3, k4, v4, k5, v5, k6, v6, k7, v7, k8, v8, k9, v9, k10, v10
        });
  }

  // looking for of() with > 10 entries? Use the builder or ofEntries instead.

  /**
   * Returns an immutable map containing the given entries, in order.
   *
   * @throws IllegalArgumentException if duplicate keys are provided

## 0.29.0

* Add support for declaring a `Response` parameter:
    * This allows declaring:
        * [Response Cookies](https://fastapi.tiangolo.com/advanced/response-cookies/).
        * [Response Headers](https://fastapi.tiangolo.com/advanced/response-headers/).

    *   Added complex128 support to FFT, FFT2D, FFT3D, IFFT, IFFT2D, and IFFT3D.
    *   Making ids unique in `nn.embedding_lookup_sparse`. This helps to reduce
        RPC calls for looking up the embeddings when there are repeated ids in
        the batch.
    *   Support indicator column in boosted trees.
    *   Prevent `tf.gradients()` from backpropagating through integer tensors.