openvino/model-optimizer/extensions/middle/ScaleInput.py

72 lines
2.4 KiB
Python

"""
Copyright (c) 2019 Intel 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 numpy as np
from mo.graph.graph import Graph
from mo.middle.replacement import MiddleReplacementPattern
from extensions.ops.elementwise import Mul
from mo.ops.op import Op
from mo.utils.error import Error
class ScaleInput(MiddleReplacementPattern):
enabled = True
def run_after(self):
from extensions.middle.pass_separator import PreMiddleStart
return [PreMiddleStart]
def run_before(self):
from extensions.middle.AddMeanScaleValues import AddMeanScaleValues
return [AddMeanScaleValues]
def pattern(self):
return dict(
nodes=[
('placeholder', dict(kind='op', op='Parameter')),
('data', dict(kind='data'))],
edges=[
('placeholder', 'data'),
],
)
def replace_pattern(self, graph: Graph, match: dict):
scale = graph.graph['cmd_params'].scale
if scale is None or scale == 1:
return
assert (len(match['placeholder'].out_nodes()))
tinput = match['placeholder']
if not tinput.has_valid('shape'):
raise Error("Node {} has not valid shape attribute".format(tinput.id))
input_shape = tinput.shape
toutput = match['data']
# Create Mul node
value = np.array([1 / scale])
# Disconnect input with data node
graph.remove_edge(tinput.id, toutput.id)
# Create Mul node
mul_node = Mul(graph, dict(name="Mul1_"))
mul_data = Op.create_input_data_node(graph, "data_mul_scale_", np.array(value))
Op.expand_node_shape(mul_data, len(input_shape) - 2 if graph.graph['layout'] == 'NCHW' else 0)
mul_input = Op.create_data_node(graph, tinput, {'shape': toutput.shape})
mul_node.create_node_with_data(inputs=[mul_input, mul_data], data_nodes=toutput)