Initializer¶
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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.
Create a tensorflow node for initializer
get_np_initializer(in_shape, out_shape)Create an initialized numpy array
Display the parameter values
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__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
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_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
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get_tf_initializer()¶ Create a tensorflow node for initializer
- Returns
initializer_instance
- Return type
An Initializer instance.
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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
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_display_params()¶ Display the parameter values
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