}
  }

  companion object {
    internal const val EMIT_BUFFER_SIZE = 16384L
  }

  /** [delta] will be negative if a settings frame initial window is smaller than the last. */
  fun addBytesToWriteWindow(delta: Long) {
    writeBytesMaximum += delta
    if (delta > 0L) {
      condition.signalAll()
    }
  }

  @Throws(IOException::class)
  internal fun checkOutNotClosed() {

              }
            }

          val peerInitialWindowSize = newPeerSettings.initialWindowSize.toLong()
          delta = peerInitialWindowSize - previousPeerSettings.initialWindowSize.toLong()
          streamsToNotify =
            when {
              delta == 0L || streams.isEmpty() -> null // No adjustment is necessary.
              else -> streams.values.toTypedArray()
            }

    val startNanos = System.nanoTime()
    assertFailsWith<InterruptedIOException> {
      stream.takeHeaders()
    }
    val elapsedNanos = System.nanoTime() - startNanos
    awaitWatchdogIdle()
    // 200ms delta
    assertThat(TimeUnit.NANOSECONDS.toMillis(elapsedNanos).toDouble())
      .isCloseTo(500.0, 200.0)
    assertThat(connection.openStreamCount()).isEqualTo(0)

    // Verify the peer received what was expected.

*   Disallow conversion of python floating types to uint32/64 (matching behavior
    of other integer types) in `tf.constant`.
*   Make the `gain` argument of convolutional orthogonal initializers
    (`convolutional_delta_orthogonal`, `convolutional_orthogonal_1D`,
    `convolutional_orthogonal_2D`, `convolutional_orthogonal_3D`) have
    consistent behavior with the `tf.initializers.orthogonal` initializer, i.e.