# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License 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.

"""
a simple multilayer perceptron
"""
import mxnet as mx


def get_symbol(num_classes=10, **kwargs):
    data = mx.symbol.Variable("data")
    data = mx.sym.Flatten(data=data)
    try:
        fc1 = mx.symbol.FullyConnected(data=data, name="fc1", num_hidden=128, flatten=False)
        act1 = mx.symbol.Activation(data=fc1, name="relu1", act_type="relu")
        fc2 = mx.symbol.FullyConnected(data=act1, name="fc2", num_hidden=64, flatten=False)
        act2 = mx.symbol.Activation(data=fc2, name="relu2", act_type="relu")
        fc3 = mx.symbol.FullyConnected(data=act2, name="fc3", num_hidden=num_classes, flatten=False)
        mlp = mx.symbol.softmax(data=fc3, name="softmax")
    except:
        fc1 = mx.symbol.FullyConnected(data=data, name="fc1", num_hidden=128)
        act1 = mx.symbol.Activation(data=fc1, name="relu1", act_type="relu")
        fc2 = mx.symbol.FullyConnected(data=act1, name="fc2", num_hidden=64)
        act2 = mx.symbol.Activation(data=fc2, name="relu2", act_type="relu")
        fc3 = mx.symbol.FullyConnected(data=act2, name="fc3", num_hidden=num_classes)
        mlp = mx.symbol.softmax(data=fc3, name="softmax")
    return mlp