pyprobound.base.Binding

class Binding(name='')

Bases: Transform, ABC

Abstract base class for binding modes and binding cooperativity.

Each Binding component links a specification storing experiment-independent parameters with the matching experiment and its specific parameters.

__init__(name='')

Initialize internal Module state, shared by both nn.Module and ScriptModule.

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.
expected_log_score()	Calculates the expected log score.
expected_sequence()	Uninformative prior of input, used for calculating expectations.
forward(seqs)	A transformation applied to a sequence tensor.
freeze()	Turns off gradient calculation for all parameters.
key()	The specification of a Binding component.
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.
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.
score_windows(seqs)	Calculates the score of each window before summing over them.
unfreeze([parameter])	Turns on gradient calculation for the specified parameter.

Attributes

unfreezable

alias of Literal['all']

Non-Inherited Members

abstract key()

The specification of a Binding component.

All Binding components with the same specification will be optimized together in the sequential optimization procedure.

Return type:

tuple[Spec, ...]

abstract expected_sequence()

Uninformative prior of input, used for calculating expectations.

Return type:

Tensor

expected_log_score()

Calculates the expected log score.

Return type:

float

abstract score_windows(seqs)

Calculates the score of each window before summing over them.

Parameters:

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

Return type:

Tensor

Returns:

A tensor with the score of each window.