tf.contrib.rnn.AttentionCellWrapper.__init__()

tf.contrib.rnn.AttentionCellWrapper.__init__(cell, attn_length, attn_size=None, attn_vec_size=None, input_size=None, state_is_tuple=False)

Create a cell with attention.

Args:

• cell: an RNNCell, an attention is added to it.
• attn_length: integer, the size of an attention window.
• attn_size: integer, the size of an attention vector. Equal to cell.output_size by default.
• attn_vec_size: integer, the number of convolutional features calculated on attention state and a size of the hidden layer built from base cell state. Equal attn_size to by default.
• input_size: integer, the size of a hidden linear layer, built from inputs and attention. Derived from the input tensor by default.
• state_is_tuple: If True, accepted and returned states are n-tuples, where n = len(cells). By default (False), the states are all concatenated along the column axis.

Raises:

• TypeError: if cell is not an RNNCell.
• ValueError: if cell returns a state tuple but the flag state_is_tuple is False or if attn_length is zero or less.