openvino/model-optimizer/extensions/back/FuseTransposesSequence.py

80 lines
3.3 KiB
Python

"""
Copyright (c) 2018-2019 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.back.replacement import BackReplacementPattern
from mo.front.common.partial_infer.utils import int64_array
from mo.graph.graph import Graph
from mo.middle.passes.eliminate import merge_data_nodes, graph_clean_up_tf
from mo.middle.passes.fusing.helpers import get_next_operation
from mo.utils.error import Error
class FuseTransposesSequence(BackReplacementPattern):
"""
This pass finds sequence of Transpose operations and merge them to single Transpose operation
In case if resulting Permutation do nothing, we just remove it
"""
enabled = True
def run_before(self):
from extensions.back.TransposeToPermute import TransposeToPermute
return [TransposeToPermute]
def find_and_replace_pattern(self, graph: Graph):
for permute_node in graph.get_op_nodes(type='Transpose'):
if permute_node.id not in graph.nodes():
continue
list_of_permutes = [permute_node]
# Get sequence of permutations
node = permute_node
while True:
next_ops = get_next_operation(node)
if len(next_ops) != 1:
break
next_op = next_ops[0]
if next_op.soft_get('type') == 'Transpose':
list_of_permutes.append(next_op)
node = next_op
else:
break
final_permutation = int64_array([x for x in range(len(list_of_permutes[0].in_port(1).data.get_value()))])
for permute in list_of_permutes:
order = permute.in_port(1).data.get_value()
if order is None:
raise Error("Transpose node {} has wrong order for permute = None".format(permute.name))
final_permutation = final_permutation[int64_array(order)]
if np.array_equal(final_permutation, [x for x in range(len(list_of_permutes[0].in_port(1).data.get_value()))]):
first_data_node, last_data_node = list_of_permutes[0].in_node(), list_of_permutes[-1].out_node()
graph.remove_edge(first_data_node.id, list_of_permutes[0].id)
else:
if len(list_of_permutes) < 2:
continue
first_data_node, last_data_node = list_of_permutes[0].out_node(), list_of_permutes[-1].out_node()
list_of_permutes[0].in_port(1).data.set_value(final_permutation)
graph.remove_edge(first_data_node.id, first_data_node.out_node().id)
graph.remove_edge(last_data_node.in_node().id, last_data_node.id)
merge_data_nodes(graph, first_data_node, last_data_node)
graph.remove_node(last_data_node.id)
graph_clean_up_tf(graph)