kiwi/modules/common/feedforward.py
# OpenKiwi: Open-Source Machine Translation Quality Estimation
# Copyright (C) 2020 Unbabel <openkiwi@unbabel.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
#
from collections import OrderedDict
from torch import nn
def feedforward(
in_dim,
n_layers,
shrink=2,
out_dim=None,
activation=nn.Tanh,
final_activation=False,
dropout=0.0,
):
"""Constructor for FeedForward Layers"""
dim = in_dim
module_dict = OrderedDict()
for layer_i in range(n_layers - 1):
next_dim = dim // shrink
module_dict['linear_{}'.format(layer_i)] = nn.Linear(dim, next_dim)
module_dict['activation_{}'.format(layer_i)] = activation()
module_dict['dropout_{}'.format(layer_i)] = nn.Dropout(dropout)
dim = next_dim
next_dim = out_dim or (dim // 2)
module_dict['linear_{}'.format(n_layers - 1)] = nn.Linear(dim, next_dim)
if final_activation:
module_dict['activation_{}'.format(n_layers - 1)] = activation()
return nn.Sequential(module_dict)