deepctr.contrib.utils module

class deepctr.contrib.utils.QAAttGRUCell(*args, **kwargs)

Bases: tensorflow.python.keras.layers.legacy_rnn.rnn_cell_impl.RNNCell

Gated Recurrent Unit cell (cf. http://arxiv.org/abs/1406.1078).

Args:

num_units: int, The number of units in the GRU cell.

activation: Nonlinearity to use. Default: tanh.

reuse: (optional) Python boolean describing whether to reuse variables

in an existing scope. If not True, and the existing scope already has

the given variables, an error is raised.

kernel_initializer: (optional) The initializer to use for the weight and

projection matrices.

bias_initializer: (optional) The initializer to use for the bias.

call(inputs, state, att_score=None)

Gated recurrent unit (GRU) with nunits cells.

property output_size

Integer or TensorShape: size of outputs produced by this cell.

property state_size

size(s) of state(s) used by this cell.

It can be represented by an Integer, a TensorShape or a tuple of Integers or TensorShapes.

class deepctr.contrib.utils.VecAttGRUCell(*args, **kwargs)

Bases: tensorflow.python.keras.layers.legacy_rnn.rnn_cell_impl.RNNCell

Gated Recurrent Unit cell (cf. http://arxiv.org/abs/1406.1078).

Args:

num_units: int, The number of units in the GRU cell.

activation: Nonlinearity to use. Default: tanh.

reuse: (optional) Python boolean describing whether to reuse variables

in an existing scope. If not True, and the existing scope already has

the given variables, an error is raised.

kernel_initializer: (optional) The initializer to use for the weight and

projection matrices.

bias_initializer: (optional) The initializer to use for the bias.

call(inputs, state, att_score=None)

Gated recurrent unit (GRU) with nunits cells.

property output_size

Integer or TensorShape: size of outputs produced by this cell.

property state_size

size(s) of state(s) used by this cell.

It can be represented by an Integer, a TensorShape or a tuple of Integers or TensorShapes.