# Path: nmt_chainer/additional_links/layer_normalization.py
# def get_layer_normalization_class():
#     global use_chainer_layer_normalization
#     if use_chainer_layer_normalization:
#         return L.LayerNormalization
#     else:
#         log.info("using faster LayerNormalization")
#         return LayerNormalizationLink


import chainer
import numpy as np
import chainer.functions as F
import chainer.links as L
from chainer import Variable, Chain, ChainList
from nmt_chainer.additional_links.layer_normalization import get_layer_normalization_class
#!/usr/bin/env python
from __future__ import absolute_import, division, print_function, unicode_literals


# LayerNormalization = L.LayerNormalization
# from nmt_chainer.additional_links.layer_normalization import LayerNormalizationLink as LayerNormalization

class DropoutAndAddAndNormalize(Chain):
    def __init__(self, dropout=None, residual_mode="normal", no_normalize=False):
        super(DropoutAndAddAndNormalize, self).__init__()
        
        if not no_normalize:

# Path: nmt_chainer/additional_links/layer_normalization.py
# def get_layer_normalization_class():
#     global use_chainer_layer_normalization
#     if use_chainer_layer_normalization:
#         return L.LayerNormalization
#     else:
#         log.info("using faster LayerNormalization")
#         return LayerNormalizationLink


# Path: nmt_chainer/models/feedforward/utils.py
import chainer
import numpy as np
import chainer.functions as F
import chainer.links as L
from chainer import Variable, Chain, ChainList
from nmt_chainer.additional_links.layer_normalization import get_layer_normalization_class

#!/usr/bin/env python
from __future__ import absolute_import, division, print_function, unicode_literals


# LayerNormalization = L.LayerNormalization
# from nmt_chainer.additional_links.layer_normalization import LayerNormalizationLink as LayerNormalization

class DropoutAndAddAndNormalize(Chain):
    def __init__(self, dropout=None, residual_mode="normal", no_normalize=False):
        super(DropoutAndAddAndNormalize, self).__init__()
        
        if not no_normalize:

            LayerNormalization = get_layer_normalization_class()