# Loss¶

class ampligraph.latent_features.Loss(eta, hyperparam_dict, verbose=False)

Abstract class for loss function.

Methods

 __init__(eta, hyperparam_dict[, verbose]) Initialize Loss. get_state(param_name) Get the state value. _init_hyperparams(hyperparam_dict) Initializes the hyperparameters needed by the algorithm. _inputs_check(scores_pos, scores_neg) Creates any dependencies that need to be checked before performing loss computations apply(scores_pos, scores_neg) Interface to external world. _apply(scores_pos, scores_neg) Apply the loss function.
__init__(eta, hyperparam_dict, verbose=False)

Initialize Loss.

Parameters: eta (int) – number of negatives hyperparam_dict (dict) – dictionary of hyperparams. (Keys are described in the hyperparameters section)
get_state(param_name)

Get the state value.

Parameters: param_name (string) – Name of the state for which one wants to query the value. The value of the corresponding state. param_value
_init_hyperparams(hyperparam_dict)

Initializes the hyperparameters needed by the algorithm.

Parameters: hyperparam_dict (dictionary) – Consists of key value pairs. The Loss will check the keys to get the corresponding params.
_inputs_check(scores_pos, scores_neg)

Creates any dependencies that need to be checked before performing loss computations

Parameters: scores_pos (tf.Tensor) – A tensor of scores assigned to positive statements. scores_neg (tf.Tensor) – A tensor of scores assigned to negative statements.
apply(scores_pos, scores_neg)

Interface to external world. This function does the input checks, preprocesses input and finally applies loss function.

Parameters: scores_pos (tf.Tensor) – A tensor of scores assigned to positive statements. scores_neg (tf.Tensor) – A tensor of scores assigned to negative statements. loss – The loss value that must be minimized. tf.Tensor
_apply(scores_pos, scores_neg)

Apply the loss function. Every inherited class must implement this function. (All the TF code must go in this function.)

Parameters: scores_pos (tf.Tensor) – A tensor of scores assigned to positive statements. scores_neg (tf.Tensor) – A tensor of scores assigned to negative statements. loss – The loss value that must be minimized. tf.Tensor