49 lines
2.1 KiB
Python
49 lines
2.1 KiB
Python
"""
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Copyright (C) 2018-2020 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import networkx as nx
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import numpy as np
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from extensions.middle.EltwiseInputReshape import EltwiseInputReshape
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from mo.graph.graph import Graph
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from mo.middle.replacement import MiddleReplacementPattern
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class EltwiseInputNormalize(EltwiseInputReshape, MiddleReplacementPattern):
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# This pass should be called directly from pipeline before layout change and other permutations
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enabled = False
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def find_and_replace_pattern(self, graph: Graph):
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eltwise_nodes = graph.get_op_nodes(is_eltwise=True)
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# Iterating over all Eltwise operations and check that every input has similar shape
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# in case of different shapes, we inserts new_shape attribute and then call EltwiseInputReshape extension
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# that insert reshapes (in case of not constant nodes) or directly reshapes values in data nodes for specified
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# shape
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for node in eltwise_nodes:
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output_shape = node.out_node().shape
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for in_node in node.in_nodes().values():
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if len(in_node.shape) != len(output_shape):
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# Set edge attribute new_shape for further transformation pass
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new_shape = in_node.shape
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for x in range(len(output_shape) - len(in_node.shape)):
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new_shape = np.insert(new_shape, 0, 1)
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nx.set_edge_attributes(G=node.graph,
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values={(in_node.id, node.id, 0): new_shape},
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name='new_shape')
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super().find_and_replace_pattern(graph)
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