import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.util.Map;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * A bimap (or "bidirectional map") is a map that preserves the uniqueness of its values as well as
 * that of its keys. This constraint enables bimaps to support an "inverse view", which is another

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.util.Map;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * A bimap (or "bidirectional map") is a map that preserves the uniqueness of its values as well as
 * that of its keys. This constraint enables bimaps to support an "inverse view", which is another

import okhttp3.internal.toHeaderList
import okio.AsyncTimeout
import okio.Buffer
import okio.BufferedSource
import okio.Sink
import okio.Socket
import okio.Source
import okio.Timeout

/** A logical bidirectional stream. */
@Suppress("NAME_SHADOWING")
class Http2Stream internal constructor(
  val id: Int,
  val connection: Http2Connection,
  outFinished: Boolean,
  inFinished: Boolean,
  headers: Headers?,
) : Lockable,

</pre>

<p>
The optional <code>&lt;-</code> operator specifies the channel <i>direction</i>,
<i>send</i> or <i>receive</i>. If a direction is given, the channel is <i>directional</i>,
otherwise it is <i>bidirectional</i>.
A channel may be constrained only to send or only to receive by
<a href="#Assignment_statements">assignment</a> or
explicit <a href="#Conversions">conversion</a>.
</p>

<pre>

the destination side, a `X-Amz-Replication-Status` status of `REPLICA` indicates that the object was replicated successfully. Any replication failures are automatically re-attempted during a periodic disk scanner cycle.

To perform bi-directional replication, repeat the above process on the target site - this time setting the source bucket as the replication target. It is recommended that replication be run in a system with at least two CPU's available to the process, so that replication...

    `GRUCell`, and a number of other cells. These now reside in `tf.nn.rnn_cell`
    (with aliases in `tf.contrib.rnn` for backwards compatibility). The original
    `tf.nn.rnn` function is now `tf.nn.static_rnn`, and the bidirectional static
    and state saving static rnn functions are also now back in the `tf.nn`
    namespace.

    Notable exceptions are the `EmbeddingWrapper`, `InputProjectionWrapper` and