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ZorzNetData.py
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ZorzNetData.py
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from typing import List
from src.neural_network.NetworkInterface import NetworkDataInterface
class ZorzNetData(NetworkDataInterface):
def __init__(self):
self.num_features: int = None
self.num_classes: int = None
self.num_dense_layers_1: int = None
self.num_units_1: List[int] = list()
self.dense_activations_1: List[int] = list()
self.batch_normalization_1: bool = False
self.batch_normalization_trainable_1: bool = False
self.keep_prob_1: List[float] = None
self.kernel_init_1 = None
self.bias_init_1 = None
self.is_bidirectional: bool = False
self.num_cell_units: List[int] = None
self.cell_activation: List[int] = None
self.keep_prob_rnn: List[float] = None
self.rnn_batch_normalization: bool = None
self.rnn_output_sizes: List[int] = None
self.num_dense_layers_2: int = None
self.num_units_2: List[int] = list()
self.dense_activations_2: List[int] = list()
self.batch_normalization_2: bool = False
self.batch_normalization_trainable_2: bool = False
self.keep_prob_2: List[float] = None
self.kernel_init_2 = None
self.bias_init_2 = None
self.rnn_regularizer: float = 0
self.dense_regularizer: float = None
self.beam_width: int = None
self.use_learning_rate_decay: bool = None
self.learning_rate_decay_steps: int = None
self.learning_rate_decay: float = None
self.clip_gradient: int = None
self.momentum: float = None
self.noise_stddev: float = None
self.num_reduce_by_half: int = None
def as_dict(self):
return self.__dict__