# Copyright 2020,2021 Sony Corporation.
# Copyright 2021 Sony Group Corporation.
#
# Licensed 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.
import nnabla.functions as F
from .graph_converter import FunctionModifier
[docs]class BatchNormBatchStatModifier(FunctionModifier):
"""
Change `batch_stat` to `False`.
Supported functions: `BatchNormalization`, `FusedBatchNormalization`, `SyncBatchNormalization`.
Examples:
.. code-block:: python
pred = Model(...)
import nnabla.experimental.graph_converters as GC
modifiers = [GC.BatchNormBatchStatModifier()]
gc = GC.GraphConverter(modifiers)
pred = gc.convert(pred)
"""
def __init__(self):
super(BatchNormBatchStatModifier, self).__init__()
self._fct_set = {
'BatchNormalization': F.batch_normalization,
'FusedBatchNormalization': F.fused_batch_normalization,
'SyncBatchNormalization': F.sync_batch_normalization
}
def connect(self, fname, inputs, args):
fct = self._fct_set[fname]
args['batch_stat'] = False
if 'no_scale' in args:
del args['no_scale']
if 'no_bias' in args:
del args['no_bias']
h = fct(*inputs, **args)
return h
def modify(self, f, inputs):
if not f.info.type_name in self._fct_set:
return
h = self.connect(f.info.type_name, inputs, f.info.args)
return h