Evgeny Lazarev
970b1301b5
* Removed back phase transformations related to IRv7 * Fixed setting value for the input port using the 'set_value' method * Removed front and middle phase transformations related to IRv7 * Cleanup the rest of the Model Optimizer transformations from IRv7 specific transformations * Final cleanup of the deprecated IR v7 related code * Removed 'blobs_as_input' usage in the Model Optimizer. * Removed function '_fuse_add' from the Model Optimizer since it is not used anymore. * Removed 'keep_in_IR' node attribute for FakeQuantize ops in the MO * Disabled failing gpu_engine.user_context test
72 lines
3.0 KiB
Python
72 lines
3.0 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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from extensions.ops.topk import TopK
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from mo.graph.graph import Graph
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from mo.middle.replacement import MiddleReplacementPattern
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from mo.ops.concat import Concat
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from mo.ops.const import Const
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class ArgMaxToTopK(MiddleReplacementPattern):
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"""
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The transformation replaces ArgMax with the TopK layer.
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"""
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op = "ArgMax"
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enabled = True
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force_clean_up = True
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def pattern(self):
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return dict(
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nodes=[
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('argmax', dict(op='ArgMax')),
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],
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edges=[]
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)
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def replace_pattern(self, graph: Graph, match: dict):
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node = match['argmax']
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node_name = node.soft_get('name', node.id)
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connected_ports = [port for port in node.in_ports().values() if not port.disconnected()]
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if len(connected_ports) == 2:
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axis = node.in_port(1).data.get_value()
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else:
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axis = node.axis
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assert axis is not None, 'The "axis" should be defined for node "{}"'.format(node_name)
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assert node.has_and_set('output_type'), 'The data type is not set for node "{}"'.format(node_name)
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topk_node = TopK(graph, {'axis': axis, 'mode': 'max', 'sort': 'index',
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'remove_values_output': node.has_and_set('remove_values_output'),
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'index_element_type': node.output_type}).create_node()
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node.in_port(0).get_connection().set_destination(topk_node.in_port(0))
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if node.has_and_set('out_max_val'): # in this mode the ArgMax produces tuples (max_ind, max_value)
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concat_node = Concat(graph, {'axis': 1, 'name': node.name + '/Concat'}).create_node()
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concat_node.add_input_port(0, skip_if_exist=True)
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concat_node.add_input_port(1, skip_if_exist=True)
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topk_node.out_port(0).connect(concat_node.in_port(1)) # indices
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topk_node.out_port(1).connect(concat_node.in_port(0)) # values
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if not node.out_port(0).disconnected():
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node.out_port(0).get_connection().set_source(concat_node.out_port(1))
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else:
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if not node.out_port(0).disconnected():
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node.out_port(0).get_connection().set_source(topk_node.out_port(1))
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topk_node.in_port(1).connect(Const(graph, {'name': node.soft_get('name') + '/TopK',
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'value': node.top_k}).create_node().out_port(0))
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graph.remove_nodes_from([node.id, node.out_node(0).id])
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