Initializer¶

class ampligraph.latent_features.Initializer(initializer_params={}, verbose=True, seed=0)¶

Abstract class for initializer .

Methods

`__init__`([initializer_params, verbose, seed])	Initialize the Class
`_init_hyperparams`(hyperparam_dict)	Initializes the hyperparameters.
`get_tf_initializer`()	Create a tensorflow node for initializer
`get_np_initializer`(in_shape, out_shape)	Create an initialized numpy array
`_display_params`()	Display the parameter values

__init__(initializer_params={}, verbose=True, seed=0)¶

Initialize the Class

Parameters:	initializer_params (dict) – dictionary of hyperparams that would be used by the initializer. verbose (bool) – set/reset verbose mode seed (int/np.random.RandomState) – random state for random number generator

_init_hyperparams(hyperparam_dict)¶

Initializes the hyperparameters.

Parameters:	hyperparam_dict (dictionary) – Consists of key value pairs. The initializer will check the keys to get the corresponding params

get_tf_initializer()¶

Create a tensorflow node for initializer

Returns:	initializer_instance
Return type:	An Initializer instance.

get_np_initializer(in_shape, out_shape)¶

Create an initialized numpy array

Parameters:	in_shape (int) – number of inputs to the layer (fan in) out_shape (int) – number of outputs of the layer (fan out)
Returns:	initialized_values – Initialized weights
Return type:	n-d array