from .videoGRU import videoGRU
from .vedioLSTM import vedioLSTM
from .resnet import resnet50, resnet18, resnet34
from .inceptionv4 import inceptionv4
from .mobilev2 import mobilenetv2
encoder_nets = {'resnet50': resnet50, 'resnet18': resnet18, 'resnet34':
    resnet34, 'inceptionv4': inceptionv4, 'mobilenetv2': mobilenetv2}
classification_nets = {'gru': videoGRU, 'lstm': vedioLSTM}


def get_encoder_net(name=None):
    if name is None:
        raise ValueError('Name of encoder network is None')
    if name not in encoder_nets:
        raise ValueError('Name of encoder network unknown %s' % name)
    return encoder_nets[name]


def get_end_net(name=None):
    if name is None:
        raise ValueError('Name of classification network is None')
    if name not in classification_nets:
        raise ValueError('Name of classification network unknown %s' % name)
    return classification_nets[name]

5213ccd506b88d0b863e0d264a06cacd7c438652
<mask token>


def get_encoder_net(name=None):
    if name is None:
        raise ValueError('Name of encoder network is None')
    if name not in encoder_nets:
        raise ValueError('Name of encoder network unknown %s' % name)
    return encoder_nets[name]


<mask token>

<mask token>


def get_encoder_net(name=None):
    if name is None:
        raise ValueError('Name of encoder network is None')
    if name not in encoder_nets:
        raise ValueError('Name of encoder network unknown %s' % name)
    return encoder_nets[name]


def get_end_net(name=None):
    if name is None:
        raise ValueError('Name of classification network is None')
    if name not in classification_nets:
        raise ValueError('Name of classification network unknown %s' % name)
    return classification_nets[name]

<mask token>
encoder_nets = {'resnet50': resnet50, 'resnet18': resnet18, 'resnet34':
    resnet34, 'inceptionv4': inceptionv4, 'mobilenetv2': mobilenetv2}
classification_nets = {'gru': videoGRU, 'lstm': vedioLSTM}


def get_encoder_net(name=None):
    if name is None:
        raise ValueError('Name of encoder network is None')
    if name not in encoder_nets:
        raise ValueError('Name of encoder network unknown %s' % name)
    return encoder_nets[name]


def get_end_net(name=None):
    if name is None:
        raise ValueError('Name of classification network is None')
    if name not in classification_nets:
        raise ValueError('Name of classification network unknown %s' % name)
    return classification_nets[name]

from .videoGRU import videoGRU
from .vedioLSTM import vedioLSTM
from .resnet import resnet50, resnet18, resnet34
from .inceptionv4 import inceptionv4
from .mobilev2 import mobilenetv2
encoder_nets = {'resnet50': resnet50, 'resnet18': resnet18, 'resnet34':
    resnet34, 'inceptionv4': inceptionv4, 'mobilenetv2': mobilenetv2}
classification_nets = {'gru': videoGRU, 'lstm': vedioLSTM}


def get_encoder_net(name=None):
    if name is None:
        raise ValueError('Name of encoder network is None')
    if name not in encoder_nets:
        raise ValueError('Name of encoder network unknown %s' % name)
    return encoder_nets[name]


def get_end_net(name=None):
    if name is None:
        raise ValueError('Name of classification network is None')
    if name not in classification_nets:
        raise ValueError('Name of classification network unknown %s' % name)
    return classification_nets[name]
