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