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

63 lines
2.7 KiB
Python

# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
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
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 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()