75 lines
2.1 KiB
Python
75 lines
2.1 KiB
Python
"""
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Copyright (c) 2018 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 mo.front.extractor import attr_getter
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from mo.graph.graph import Node
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from mo.ops.op import Op
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class PriorBoxClusteredOp(Op):
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op = 'PriorBoxClustered'
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def __init__(self, graph: nx.MultiDiGraph, attrs: dict):
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mandatory_props = {
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'type': __class__.op,
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'op': __class__.op,
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'infer': PriorBoxClusteredOp.priorbox_clustered_infer
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}
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super().__init__(graph, mandatory_props, attrs)
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def supported_attrs(self):
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return [
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'width',
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'height',
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'flip',
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'clip',
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'variance',
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'img_size',
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'img_h',
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'img_w',
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'step',
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'step_h',
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'step_w',
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'offset'
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]
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def backend_attrs(self):
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return [
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'flip',
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'clip',
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'img_size',
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'img_h',
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'img_w',
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'step',
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'step_h',
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'step_w',
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'offset',
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('variance', lambda node: attr_getter(node, 'variance')),
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('width', lambda node: attr_getter(node, 'width')),
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('height', lambda node: attr_getter(node, 'height'))
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]
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@staticmethod
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def priorbox_clustered_infer(node: Node):
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data_shape = node.in_node(0).shape
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num_ratios = len(node.width)
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res_prod = data_shape[2] * data_shape[3] * num_ratios * 4
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node.out_node(0).shape = np.array([1, 2, res_prod], dtype=np.int64)
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