Roman Kazantsev
bacb8420f0
* [MO] Implement TensorFlow 2 While support in MO Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Add extractors for both While and StatelessWhile and do minor changes Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Improve update_body_graph function and manage graph names properly Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Fix a map for original name of parameters from body and cond Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Implement draft version of support of TF2 Keras RNN Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Implement Keras LSTM and GRU support in MO Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Improve code for Keras RNN support Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Finalize implementation of TF2 Keras RNN support in MO Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Apply the first part of the comments after review #1 Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Avoid use of explicit values of port indices in the transformation Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Finalize code after the first-round review Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Apply comments after the second-round review Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
"""
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Copyright (C) 2018-2021 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 logging as log
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from mo.front.common.replacement import FrontReplacementSubgraph
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from mo.graph.graph import Graph
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class StandaloneConstEraser(FrontReplacementSubgraph):
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enabled = True
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# TODO: remove this transformation once all plugins support constant value network.
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# Now it avoids to be run recursively since Const->Result sub-graph can be encountered in a body graph of Loop node
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run_not_recursively = True
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@staticmethod
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def pattern():
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return dict(
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nodes=[('const', dict(kind='op', op='Const')),
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('output', dict(kind='op', op='Result'))
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],
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edges=[('const', 'output')]
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)
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@staticmethod
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def replace_sub_graph(graph: Graph, match: dict):
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if not len(match['const'].in_edges()) and len(match['const'].out_edges()) == 1:
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graph.erase_node(match['const'])
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graph.erase_node(match['output'])
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log.info("Standalone Const node \"{}\" was removed from the graph".format(match['const'].id))
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