Linear module

class nnodely.layers.linear.Linear(*args, **kwargs)[source]

Represents a Linear relation in the neural network model.

Notes

Note

The Linear relation works along the input dimension (third dimension) of the input tensor. You can find some initialization functions inside the initializer module.

Parameters:

output_dimension (int, optional) – The output dimension of the Linear relation.
W_init (Callable, optional) – A callable for initializing the weights.
W_init_params (dict, optional) – A dictionary of parameters for the weight initializer.
b_init (Callable, optional) – A callable for initializing the bias.
b_init_params (dict, optional) – A dictionary of parameters for the bias initializer.
W (Parameter or str, optional) – The weight parameter object or name. If not given a new parameter will be auto-generated.
b (bool, str, or Parameter, optional) – The bias parameter object, name, or a boolean indicating whether to use bias. If set to ‘True’ a new parameter will be auto-generated.
dropout (int or float, optional) – The dropout rate. Default is 0.

relation_name

The name of the relation.

Type:: str

W_init

The weight initializer.

Type:: Callable

W_init_params

The parameters for the weight initializer.

Type:: dict

b_init

The bias initializer.

Type:: Callable

b_init_params

The parameters for the bias initializer.

Type:: dict

W

The weight parameter object or name.

Type:: Parameter or str

b

The bias parameter object, name, or a boolean indicating whether to use bias.

Type:: bool, str, or Parameter

Wname

The name of the weight parameter.

Type:: str

bname

The name of the bias parameter.

Type:: str

dropout

The dropout rate.

Type:: int or float

output_dimension

The output dimension of the Linear relation.

Type:: int

Examples

Basic usage:

input = Input('in').tw(0.05)
relation = Linear(input)

Passing a weight and bias parameter:

input = Input('in').last()

weight = Parameter('W', values=[[[1]]])
bias = Parameter('b', values=[[1]])

relation = Linear(W=weight, b=bias)(input)

Parameters initialization:

input = Input('in').last()

relation = Linear(
    b=True,
    W_init=init_negexp,
    b_init=init_constant,
    b_init_params={'value': 1}
)(input)

For more examples of how to use the linear module, please refer to the Linear tutorial.