da47cb05be
* Commit. * Written draft of NonMaxSuppression-5 class. * Written conversion of the value of the second output of MO NonMaxSuppression-5 into TF format. * Fixed type infer for the port 1 of NonMaxSuppression-5. * Added Reshape to [1] for 0D inputs of NMS-5. * Small fix. * Corrected assert for number of inputs. * Fixed docstrings for transformations TFNonMaxSuppressionNormalize and NonMaxSuppressionNormalize. * Now the transformation TFNonMaxSuppressionNormalize uses find_and_replace_pattern(). * Moved model-optimizer/extensions/front/onnx/non_max_suppression_normalize.py to model-optimizer/extensions/front/non_max_suppression_normalize.py, to delete duplicate code. * Deleted commented code. * Fixed BOM-file. * Deleted out_ports_count from NMS. * Fixes in type_infer of NMS-5. * Small changes. * Added some comment. * Small fix. * Some fixes.
40 lines
1.8 KiB
Python
40 lines
1.8 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 mo.front.common.partial_infer.utils import int64_array
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from mo.front.common.replacement import FrontReplacementSubgraph
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from mo.front.tf.graph_utils import create_op_node_with_second_input
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from mo.graph.graph import Graph
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from mo.ops.reshape import Reshape
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class NonMaxSuppressionNormalize(FrontReplacementSubgraph):
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"""
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The transformation converts several inputs of the NonMaxSuppression layer to be 1D instead of 0D with shape [1] to
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comply with the layer specification.
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"""
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enabled = True
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def find_and_replace_pattern(self, graph: Graph):
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for nms in graph.get_op_nodes(op='NonMaxSuppression'):
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# make inputs 2 to 5 to have shape [1] instead of [0] (convert 0D to 1D)
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nms_name = nms.soft_get('name', nms.id)
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for port_id in range(2, 6):
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if port_id in nms.in_ports() and not nms.in_port(port_id).disconnected():
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reshape_1d = create_op_node_with_second_input(graph, Reshape, int64_array([1]),
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{'name': nms_name + '/Reshape_1D_{}'.format(port_id)})
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nms.in_port(port_id).get_connection().insert_node(reshape_1d)
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