# 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.
from .graph_converter import FunctionModifier
[docs]class RemoveFunctionModifier(FunctionModifier):
"""
Remove specified function layer(s) from a graph.
A convenient converter when one or more functions in
an existing graph needs to be removed. This converter
remove specified function(s) without recreating a new
graph from scratch.
Args:
rm_funcs (list of :obj:`str`): list of function name
Examples:
.. code-block:: python
pred = Model(...)
import nnabla.experimental.graph_converters as GC
modifiers = [GC.RemoveFunctionModifier(rm_funcs=['BatchNormalization', 'MulScalar'])]
gc = GC.GraphConverter(modifiers)
pred = gc.convert(pred)
"""
def __init__(self, rm_funcs=[]):
super(RemoveFunctionModifier, self).__init__()
self._rm_funcs = rm_funcs
def modify(self, f, inputs):
if f.info.type_name in self._rm_funcs:
# Get next func and inputs[0]
next_func = f.outputs[0].function_references[0]
inp = next_func.inputs[0]
# BWINA:
# Map inputs to next func for the very beginning function when its inputs[0] is 'x'
if f.rank == 0 and inp.name == 'x':
self._map_func_inputs[next_func].append(inp)
return inputs[0]
def __finish__(self):
pass