Source code for gluonts.mx.model.deep_factor.RNNModel
# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "license" file accompanying this file. This file is distributed
# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
# express or implied. See the License for the specific language governing
# permissions and limitations under the License.
from mxnet.gluon import HybridBlock, nn
from gluonts.core.component import validated
from gluonts.mx.block.rnn import RNN
[docs]class RNNModel(HybridBlock):
@validated()
def __init__(
self,
mode,
num_hidden,
num_layers,
num_output,
bidirectional=False,
**kwargs,
):
super().__init__(**kwargs)
self.num_output = num_output
with self.name_scope():
self.rnn = RNN(
mode=mode,
num_hidden=num_hidden,
num_layers=num_layers,
bidirectional=bidirectional,
)
self.decoder = nn.Dense(
num_output, in_units=num_hidden, flatten=False
)