openvino/model-optimizer/extensions/front/sub.py

45 lines
1.9 KiB
Python

# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import numpy as np
from extensions.ops.elementwise import Mul, Add
from mo.front.common.replacement import FrontReplacementPattern
from mo.front.tf.graph_utils import create_op_with_const_inputs
from mo.graph.graph import Graph, Node, rename_node
class Sub(FrontReplacementPattern):
# This transformation is called directly from the 'model-optimizer/extensions/middle/fusings.py' transformation
enabled = False
@staticmethod
def sub_to_add_replacement(sub: Node):
# we execute this transformation for V10 IR later on middle phase despite graph_condition
# so we prevent Sub replacement on shape-calculating sub-graphs
if sub.in_port(0).data.get_value() is not None and sub.in_port(1).data.get_value() is not None:
return
graph = sub.graph
name = sub.soft_get('name', sub.id)
# keep Add name the same as Sub -- because of mathematical equality of output tensors
rename_node(node=sub, name=name + '/to_be_removed')
# reconnect Sub in(out)puts to Add
add = Add(graph, {'name': name}).create_node()
rename_node(add, name)
sub.in_port(0).get_connection().set_destination(add.in_port(0))
sub.in_port(1).get_connection().set_destination(add.in_port(1))
sub.out_port(0).get_connection().set_source(add.out_port(0))
# restore mathematical equivalence to Sub operation: Sub(A, B) = Add(A, Mul(B, -1))
const_dtype = sub.soft_get('data_type', np.float32)
negate = create_op_with_const_inputs(graph, Mul, {1: np.array(-1, dtype=const_dtype)}, {'name': name + '/neg_'})
add.in_port(1).get_connection().insert_node(negate)
def find_and_replace_pattern(self, graph: Graph):
for sub in graph.get_op_nodes(op='Sub'):
self.sub_to_add_replacement(sub)