import os
import sys
import torch
import logging
import torch.nn as nn
def loadModel(netname = 'basemodel',dropout_rate = 0.5, channels = 1):
    Netpath = 'Model'
    
    Netfile = os.path.join(Netpath, netname)
    Netfile = os.path.join(Netfile, netname + '.py')
    assert os.path.isfile(Netfile), "No python file found for {}, (file name is case sensitive)".format(Netfile)
    netname = netname.lower()
    if netname == 'basemodel': 
        model = loadBaseModel(channels, dropout_rate)
    elif netname == 'fc_1h':
        model = loadFC_1HModel(channels, dropout_rate)
    elif netname == 'fc_2h':
        model = loadFC_2HModel(channels, dropout_rate)
    elif netname == 'fc_3h':
        model = loadFC_3HModel(channels, dropout_rate)
    else:
        logging.warning("No model with the name {} found, please check your spelling.".format(netname))
        logging.warning("Net List:")
        logging.warning("    basemodel")
        logging.warning("    FC_1H")
        logging.warning("    FC_2H")
        logging.warning("    FC_3H")
        sys.exit()
    return model

def get_model_list(netname = ''):
    if netname == '':
        return ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']

    if netname in ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']:
        return [netname]

    logging.warning("No model with the name {} found, please check your spelling.".format(netname))
    logging.warning("Net List:")
    logging.warning("    basemodel")
    logging.warning("    FC_1H")
    logging.warning("    FC_2H")
    logging.warning("    FC_3H")
    sys.exit()
    
def loadBaseModel(channels, dropout_rate):
    from Model.basemodel.basemodel import Base_Model
    logging.warning("Loading Base Model")
    return Base_Model(channels, dropout_rate)

def loadFC_1HModel(channels, dropout_rate):
    from Model.FC_1H.FC_1H import FC_1H
    logging.warning("Loading 1 hidden layer model")
    return FC_1H(channels, dropout_rate)
    
def loadFC_2HModel(channels, dropout_rate):
    from Model.FC_2H.FC_2H import FC_2H
    logging.warning("Loading 2 hidden layer model")
    return FC_2H(channels, dropout_rate)

def loadFC_3HModel(channels, dropout_rate):
    from Model.FC_3H.FC_3H import FC_3H
    logging.warning("Loading 3 hidden layer model")
    return FC_3H(channels, dropout_rate)

def weight_reset(m):
    if isinstance(m, nn.Linear):
        m.reset_parameters()
    


8e31024f56d6685ab74a010d4913bb967d310ad1
<mask token>


def loadModel(netname='basemodel', dropout_rate=0.5, channels=1):
    Netpath = 'Model'
    Netfile = os.path.join(Netpath, netname)
    Netfile = os.path.join(Netfile, netname + '.py')
    assert os.path.isfile(Netfile
        ), 'No python file found for {}, (file name is case sensitive)'.format(
        Netfile)
    netname = netname.lower()
    if netname == 'basemodel':
        model = loadBaseModel(channels, dropout_rate)
    elif netname == 'fc_1h':
        model = loadFC_1HModel(channels, dropout_rate)
    elif netname == 'fc_2h':
        model = loadFC_2HModel(channels, dropout_rate)
    elif netname == 'fc_3h':
        model = loadFC_3HModel(channels, dropout_rate)
    else:
        logging.warning(
            'No model with the name {} found, please check your spelling.'.
            format(netname))
        logging.warning('Net List:')
        logging.warning('    basemodel')
        logging.warning('    FC_1H')
        logging.warning('    FC_2H')
        logging.warning('    FC_3H')
        sys.exit()
    return model


def get_model_list(netname=''):
    if netname == '':
        return ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']
    if netname in ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']:
        return [netname]
    logging.warning(
        'No model with the name {} found, please check your spelling.'.
        format(netname))
    logging.warning('Net List:')
    logging.warning('    basemodel')
    logging.warning('    FC_1H')
    logging.warning('    FC_2H')
    logging.warning('    FC_3H')
    sys.exit()


def loadBaseModel(channels, dropout_rate):
    from Model.basemodel.basemodel import Base_Model
    logging.warning('Loading Base Model')
    return Base_Model(channels, dropout_rate)


<mask token>

<mask token>


def loadModel(netname='basemodel', dropout_rate=0.5, channels=1):
    Netpath = 'Model'
    Netfile = os.path.join(Netpath, netname)
    Netfile = os.path.join(Netfile, netname + '.py')
    assert os.path.isfile(Netfile
        ), 'No python file found for {}, (file name is case sensitive)'.format(
        Netfile)
    netname = netname.lower()
    if netname == 'basemodel':
        model = loadBaseModel(channels, dropout_rate)
    elif netname == 'fc_1h':
        model = loadFC_1HModel(channels, dropout_rate)
    elif netname == 'fc_2h':
        model = loadFC_2HModel(channels, dropout_rate)
    elif netname == 'fc_3h':
        model = loadFC_3HModel(channels, dropout_rate)
    else:
        logging.warning(
            'No model with the name {} found, please check your spelling.'.
            format(netname))
        logging.warning('Net List:')
        logging.warning('    basemodel')
        logging.warning('    FC_1H')
        logging.warning('    FC_2H')
        logging.warning('    FC_3H')
        sys.exit()
    return model


def get_model_list(netname=''):
    if netname == '':
        return ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']
    if netname in ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']:
        return [netname]
    logging.warning(
        'No model with the name {} found, please check your spelling.'.
        format(netname))
    logging.warning('Net List:')
    logging.warning('    basemodel')
    logging.warning('    FC_1H')
    logging.warning('    FC_2H')
    logging.warning('    FC_3H')
    sys.exit()


def loadBaseModel(channels, dropout_rate):
    from Model.basemodel.basemodel import Base_Model
    logging.warning('Loading Base Model')
    return Base_Model(channels, dropout_rate)


def loadFC_1HModel(channels, dropout_rate):
    from Model.FC_1H.FC_1H import FC_1H
    logging.warning('Loading 1 hidden layer model')
    return FC_1H(channels, dropout_rate)


def loadFC_2HModel(channels, dropout_rate):
    from Model.FC_2H.FC_2H import FC_2H
    logging.warning('Loading 2 hidden layer model')
    return FC_2H(channels, dropout_rate)


<mask token>


def weight_reset(m):
    if isinstance(m, nn.Linear):
        m.reset_parameters()

<mask token>


def loadModel(netname='basemodel', dropout_rate=0.5, channels=1):
    Netpath = 'Model'
    Netfile = os.path.join(Netpath, netname)
    Netfile = os.path.join(Netfile, netname + '.py')
    assert os.path.isfile(Netfile
        ), 'No python file found for {}, (file name is case sensitive)'.format(
        Netfile)
    netname = netname.lower()
    if netname == 'basemodel':
        model = loadBaseModel(channels, dropout_rate)
    elif netname == 'fc_1h':
        model = loadFC_1HModel(channels, dropout_rate)
    elif netname == 'fc_2h':
        model = loadFC_2HModel(channels, dropout_rate)
    elif netname == 'fc_3h':
        model = loadFC_3HModel(channels, dropout_rate)
    else:
        logging.warning(
            'No model with the name {} found, please check your spelling.'.
            format(netname))
        logging.warning('Net List:')
        logging.warning('    basemodel')
        logging.warning('    FC_1H')
        logging.warning('    FC_2H')
        logging.warning('    FC_3H')
        sys.exit()
    return model


def get_model_list(netname=''):
    if netname == '':
        return ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']
    if netname in ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']:
        return [netname]
    logging.warning(
        'No model with the name {} found, please check your spelling.'.
        format(netname))
    logging.warning('Net List:')
    logging.warning('    basemodel')
    logging.warning('    FC_1H')
    logging.warning('    FC_2H')
    logging.warning('    FC_3H')
    sys.exit()


def loadBaseModel(channels, dropout_rate):
    from Model.basemodel.basemodel import Base_Model
    logging.warning('Loading Base Model')
    return Base_Model(channels, dropout_rate)


def loadFC_1HModel(channels, dropout_rate):
    from Model.FC_1H.FC_1H import FC_1H
    logging.warning('Loading 1 hidden layer model')
    return FC_1H(channels, dropout_rate)


def loadFC_2HModel(channels, dropout_rate):
    from Model.FC_2H.FC_2H import FC_2H
    logging.warning('Loading 2 hidden layer model')
    return FC_2H(channels, dropout_rate)


def loadFC_3HModel(channels, dropout_rate):
    from Model.FC_3H.FC_3H import FC_3H
    logging.warning('Loading 3 hidden layer model')
    return FC_3H(channels, dropout_rate)


def weight_reset(m):
    if isinstance(m, nn.Linear):
        m.reset_parameters()

import os
import sys
import torch
import logging
import torch.nn as nn


def loadModel(netname='basemodel', dropout_rate=0.5, channels=1):
    Netpath = 'Model'
    Netfile = os.path.join(Netpath, netname)
    Netfile = os.path.join(Netfile, netname + '.py')
    assert os.path.isfile(Netfile
        ), 'No python file found for {}, (file name is case sensitive)'.format(
        Netfile)
    netname = netname.lower()
    if netname == 'basemodel':
        model = loadBaseModel(channels, dropout_rate)
    elif netname == 'fc_1h':
        model = loadFC_1HModel(channels, dropout_rate)
    elif netname == 'fc_2h':
        model = loadFC_2HModel(channels, dropout_rate)
    elif netname == 'fc_3h':
        model = loadFC_3HModel(channels, dropout_rate)
    else:
        logging.warning(
            'No model with the name {} found, please check your spelling.'.
            format(netname))
        logging.warning('Net List:')
        logging.warning('    basemodel')
        logging.warning('    FC_1H')
        logging.warning('    FC_2H')
        logging.warning('    FC_3H')
        sys.exit()
    return model


def get_model_list(netname=''):
    if netname == '':
        return ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']
    if netname in ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']:
        return [netname]
    logging.warning(
        'No model with the name {} found, please check your spelling.'.
        format(netname))
    logging.warning('Net List:')
    logging.warning('    basemodel')
    logging.warning('    FC_1H')
    logging.warning('    FC_2H')
    logging.warning('    FC_3H')
    sys.exit()


def loadBaseModel(channels, dropout_rate):
    from Model.basemodel.basemodel import Base_Model
    logging.warning('Loading Base Model')
    return Base_Model(channels, dropout_rate)


def loadFC_1HModel(channels, dropout_rate):
    from Model.FC_1H.FC_1H import FC_1H
    logging.warning('Loading 1 hidden layer model')
    return FC_1H(channels, dropout_rate)


def loadFC_2HModel(channels, dropout_rate):
    from Model.FC_2H.FC_2H import FC_2H
    logging.warning('Loading 2 hidden layer model')
    return FC_2H(channels, dropout_rate)


def loadFC_3HModel(channels, dropout_rate):
    from Model.FC_3H.FC_3H import FC_3H
    logging.warning('Loading 3 hidden layer model')
    return FC_3H(channels, dropout_rate)


def weight_reset(m):
    if isinstance(m, nn.Linear):
        m.reset_parameters()

import os
import sys
import torch
import logging
import torch.nn as nn
def loadModel(netname = 'basemodel',dropout_rate = 0.5, channels = 1):
    Netpath = 'Model'
    
    Netfile = os.path.join(Netpath, netname)
    Netfile = os.path.join(Netfile, netname + '.py')
    assert os.path.isfile(Netfile), "No python file found for {}, (file name is case sensitive)".format(Netfile)
    netname = netname.lower()
    if netname == 'basemodel': 
        model = loadBaseModel(channels, dropout_rate)
    elif netname == 'fc_1h':
        model = loadFC_1HModel(channels, dropout_rate)
    elif netname == 'fc_2h':
        model = loadFC_2HModel(channels, dropout_rate)
    elif netname == 'fc_3h':
        model = loadFC_3HModel(channels, dropout_rate)
    else:
        logging.warning("No model with the name {} found, please check your spelling.".format(netname))
        logging.warning("Net List:")
        logging.warning("    basemodel")
        logging.warning("    FC_1H")
        logging.warning("    FC_2H")
        logging.warning("    FC_3H")
        sys.exit()
    return model

def get_model_list(netname = ''):
    if netname == '':
        return ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']

    if netname in ['basemodel', 'FC_1H', 'FC_2H', 'FC_3H']:
        return [netname]

    logging.warning("No model with the name {} found, please check your spelling.".format(netname))
    logging.warning("Net List:")
    logging.warning("    basemodel")
    logging.warning("    FC_1H")
    logging.warning("    FC_2H")
    logging.warning("    FC_3H")
    sys.exit()
    
def loadBaseModel(channels, dropout_rate):
    from Model.basemodel.basemodel import Base_Model
    logging.warning("Loading Base Model")
    return Base_Model(channels, dropout_rate)

def loadFC_1HModel(channels, dropout_rate):
    from Model.FC_1H.FC_1H import FC_1H
    logging.warning("Loading 1 hidden layer model")
    return FC_1H(channels, dropout_rate)
    
def loadFC_2HModel(channels, dropout_rate):
    from Model.FC_2H.FC_2H import FC_2H
    logging.warning("Loading 2 hidden layer model")
    return FC_2H(channels, dropout_rate)

def loadFC_3HModel(channels, dropout_rate):
    from Model.FC_3H.FC_3H import FC_3H
    logging.warning("Loading 3 hidden layer model")
    return FC_3H(channels, dropout_rate)

def weight_reset(m):
    if isinstance(m, nn.Linear):
        m.reset_parameters()
    

