54 lines
1.4 KiB
Python
54 lines
1.4 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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# Concat infer : N - number of inputs to concat
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# axis - dimension number for tensors concatenation
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import copy
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from mo.graph.graph import Node, Graph
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from mo.ops.op import Op
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class DataAugmentationOp(Op):
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op = 'DataAugmentation'
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def __init__(self, graph: Graph, 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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'version': 'extension',
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'in_ports_count': 1,
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'out_ports_count': 1,
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'infer': DataAugmentationOp.data_augmentation_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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'crop_width',
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'crop_height',
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'write_augmented',
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'max_multiplier',
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'augment_during_test',
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'recompute_mean',
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'write_mean',
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'mean_per_pixel',
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'mean',
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'mode',
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'bottomwidth',
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'bottomheight',
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'num',
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'chromatic_eigvec'
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]
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@staticmethod
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def data_augmentation_infer(node: Node):
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outn = node.out_node(0)
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inn = node.in_node(0)
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outn.shape = copy.copy(inn.shape)
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if node.crop_width != 0 or node.crop_height != 0:
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outn.shape[2] = node.crop_height
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outn.shape[3] = node.crop_width
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