pyprobound.layers.module.ModuleLayer

class ModuleLayer(layer_spec, input_shape, min_input_length, max_input_length)

Bases: Layer

Layer wrapper for torch.nn.Module.

The forward implementation of the module must take a sequence tensor of shape \((\text{minibatch},\text{in_channels},\text{in_length})\) and return a tensor of shape \((\text{minibatch},1,1)\).

__init__(layer_spec, input_shape, min_input_length, max_input_length)

Initializes the Module layer.

Parameters:

• layer_spec (ModuleSpec) – The specification of the Module layer.

• input_shape (int) – The number of elements in an input sequence.

• min_input_length (int) – The minimum number of finite elements in an input sequence.

• max_input_length (int) – The maximum number of finite elements in an input sequence.

Methods

cache(fun)	Decorator for a function to cache its output.
check_length_consistency()	Checks that input lengths of Binding components are consistent.
components()	Iterator of child components.
forward(seqs)	Applies the module.
freeze()	Turns off gradient calculation for all parameters.
from_spec(spec, prev)	Creates a new instance from a specification and an input component.
in_len(length[, mode])	Calculates the receptive field.
lengths(seqs)	Counts the number of finite elements in each sequence.
max_embedding_size()	The maximum number of bytes needed to encode a sequence.
optim_procedure([ancestry, current_order])	The sequential optimization procedure for all Binding components.
out_len(length[, mode])	Calculates the number of elements in the output length dimension.
reload(checkpoint)	Loads the model from a checkpoint file.
reload_from_state_dict(state_dict)	Loads the model from a state dict.
save(checkpoint[, flank_lengths])	Saves the model to a file with "state_dict" and "metadata" fields.
unfreeze([parameter])	Turns on gradient calculation for the specified parameter.
update_binding_optim(binding_optim)	Updates a BindingOptim with the specification's optimization steps.
update_input_length([left_shift, ...])	Updates input shapes, called by a child LayerSpec after its update.

Attributes

in_channels	The number of input channels.
input_shape	The number of elements in an input sequence.
max_input_length	The maximum number of finite elements in an input sequence.
min_input_length	The minimum number of finite elements in an input sequence.
out_channels	The number of output channels.
unfreezable	alias of Literal['all']

Non-Inherited Members

classmethod from_spec(spec, prev)

Creates a new instance from a specification and an input component.

Parameters:

• spec (ModuleSpec) – The specification of the Module layer.

• prev (Union[Table[Any], Layer]) – If used as the first layer, the table that will be passed as an input; otherwise, the layer that precedes it.

Return type:

Self

forward(seqs)

Applies the module.

Parameters:

seqs (Tensor) – A sequence tensor of shape \((\text{minibatch},\text{length})\) or \((\text{minibatch},\text{in_channels},\text{in_length})\).

Return type:

Tensor

Returns:

A tensor of shape \((\text{minibatch},1,1)\).