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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def encode(x, x_space, hparams, name):
 """Transformer preparations and encoder."""

  with tf.variable_scope(name):
    (encoder_input, encoder_self_attention_bias,
     ed) = transformer.transformer_prepare_encoder(x, x_space, hparams)
    encoder_input = tf.nn.dropout(encoder_input, 1.0 - hparams.dropout)
    return transformer.transformer_encoder(
        encoder_input, encoder_self_attention_bias, hparams), ed