def __init__(self,
input_size_dyn: int,
input_size_stat: int,
hidden_size: int,
embedding_hiddens: List = [],
initial_forget_bias: int = 5,
dropout: float = 0.0,
concat_static: bool = True):
"""Initialize model.
Parameters
----------
input_size_dyn: int
Number of dynamic input features.
input_size_stat: int
Number of static input features (used in the EA-LSTM input gate).
hidden_size: int
Number of LSTM cells/hidden units.
initial_forget_bias: int
Value of the initial forget gate bias. (default: 5)
dropout: float
Dropout probability in range(0,1). (default: 0.0)
concat_static: bool
If True, uses standard LSTM otherwise uses EA-LSTM
"""
super(Model, self).__init__()
self.input_size_dyn = input_size_dyn
self.input_size_stat = input_size_stat
self.hidden_size = hidden_size
self.embedding_hiddens = embedding_hiddens
self.initial_forget_bias = initial_forget_bias
self.dropout_rate = dropout
self.concat_static = concat_static
if self.concat_static:
if self.embedding_hiddens:
self.lstm = EmbLSTM(input_size_dyn=input_size_dyn,
input_size_stat=input_size_stat,
hidden_size=hidden_size,
embedding_hiddens=embedding_hiddens,
initial_forget_bias=initial_forget_bias)
else:
self.lstm = LSTM(
input_size=input_size_dyn,
hidden_size=hidden_size,
initial_forget_bias=initial_forget_bias)
else:
self.lstm = EALSTM(
input_size_dyn=input_size_dyn,
input_size_stat=input_size_stat,
hidden_size=hidden_size,
initial_forget_bias=initial_forget_bias)
self.dropout = nn.Dropout(p=dropout)
self.fc = nn.Linear(hidden_size, 1)
def __init__(self,
input_size_dyn: int,
hidden_size: int,
initial_forget_bias: int = 5,
dropout: float = 0.0,
concat_static: bool = False,
no_static: bool = False):
"""Initialize model.
Parameters
----------
input_size_dyn: int
Number of dynamic input features.
hidden_size: int
Number of LSTM cells/hidden units.
initial_forget_bias: int
Value of the initial forget gate bias. (default: 5)
dropout: float
Dropout probability in range(0,1). (default: 0.0)
concat_static: bool
If True, uses standard LSTM otherwise uses EA-LSTM
no_static: bool
If True, runs standard LSTM
"""
super(Model, self).__init__()
self.input_size_dyn = input_size_dyn
self.hidden_size = hidden_size
self.initial_forget_bias = initial_forget_bias
self.dropout_rate = dropout
self.concat_static = concat_static
self.no_static = no_static
self.lstm = LSTM(input_size=input_size_dyn,
hidden_size=hidden_size,
initial_forget_bias=initial_forget_bias)
self.dropout = nn.Dropout(p=dropout)
self.fc = nn.Linear(hidden_size, 1)