Loss¶
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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)
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get_state
(param_name)¶ Get the state value.
Parameters: param_name (string) – name of the state for which one wants to query the value Returns: the value of the corresponding state Return type: param_value
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_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
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_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.
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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.
Returns: loss – The loss value that must be minimized.
Return type: tf.Tensor
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_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.
Returns: loss – The loss value that must be minimized.
Return type: tf.Tensor
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