Evgeny Lazarev
970b1301b5
* Removed back phase transformations related to IRv7 * Fixed setting value for the input port using the 'set_value' method * Removed front and middle phase transformations related to IRv7 * Cleanup the rest of the Model Optimizer transformations from IRv7 specific transformations * Final cleanup of the deprecated IR v7 related code * Removed 'blobs_as_input' usage in the Model Optimizer. * Removed function '_fuse_add' from the Model Optimizer since it is not used anymore. * Removed 'keep_in_IR' node attribute for FakeQuantize ops in the MO * Disabled failing gpu_engine.user_context test
72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
"""
|
|
Copyright (C) 2018-2020 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.
|
|
"""
|
|
from extensions.back.op_versioning import OpVersioning
|
|
from mo.back.replacement import BackReplacementPattern
|
|
from mo.graph.graph import Graph
|
|
|
|
|
|
class BlobNormalizer(BackReplacementPattern):
|
|
"""
|
|
This pass affects Convolution and FullyConnected weights and biases form in IR.
|
|
Old version of those layers included weights and biases as blobs:
|
|
<layer ... type="Convolution">
|
|
...
|
|
<blobs>
|
|
<weights offset="***" size="***"/>
|
|
<biases offset="***" size="***"/>
|
|
</blobs>
|
|
</layer>
|
|
|
|
New version (after BlobNormalizer execution) weighs and biases are represented
|
|
as inputs to Convolution/FullyConnected layer
|
|
"""
|
|
enabled = True
|
|
|
|
def run_before(self):
|
|
return []
|
|
|
|
def run_after(self):
|
|
from extensions.back.pass_separator import BackFinish
|
|
return [BackFinish]
|
|
|
|
@staticmethod
|
|
def pattern():
|
|
return dict(
|
|
nodes=[('conv', dict(type=lambda type: type in ['Convolution', 'Deconvolution', 'FullyConnected']))],
|
|
edges=[]
|
|
)
|
|
|
|
def replace_pattern(self, graph: Graph, match: dict):
|
|
conv = match['conv']
|
|
for i in [1, 2]:
|
|
if i in conv.in_edges() and conv.in_edges()[i] and 'bin' in conv.in_edges()[i]:
|
|
del conv.in_edges()[i]['bin']
|
|
|
|
def find_and_replace_pattern(self, graph: Graph):
|
|
for node in graph.get_op_nodes():
|
|
if node.soft_get('type').lower() not in OpVersioning.opset_1_types and \
|
|
not node.soft_get('version') in ["opset2", "opset3", "opset4"]:
|
|
continue
|
|
|
|
for _, d in node.in_edges().items():
|
|
if 'bin' in d:
|
|
del d['bin']
|
|
|
|
for node in graph.get_data_nodes():
|
|
for d in node.in_edges():
|
|
if 'bin' in d:
|
|
del d['bin']
|