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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 slice_hidden(x, hidden_size, num_blocks):
 """Slice encoder hidden state under num_blocks. Args: x: Encoder hidden state of shape [batch_size, latent_dim, hidden_size]. hidden_size: Dimension of the latent space. num_blocks: Number of blocks in DVQ. Returns: Sliced states of shape [batch_size, latent_dim, num_blocks, block_dim]. """

  batch_size, latent_dim, _ = common_layers.shape_list(x)
  block_dim = hidden_size // num_blocks
  x_sliced = tf.reshape(x,
                        shape=[batch_size, latent_dim, num_blocks, block_dim])
  return x_sliced