44 lines
1.4 KiB
Python
44 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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import numpy as np
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from mo.front.common.partial_infer.utils import int64_array
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from mo.graph.graph import Graph
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from mo.ops.op import Op
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class Reverse(Op):
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op = 'Reverse'
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def __init__(self, graph: Graph, attrs: dict):
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mandatory_props = {
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# 'type': __class__.op, # Internal MO primitive
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'axis': None,
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'op': __class__.op,
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'in_ports_count': 2,
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'out_ports_count': 1,
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'infer': __class__.infer,
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}
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super().__init__(graph, mandatory_props, attrs)
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@staticmethod
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def infer(node):
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input_data_shape = node.in_node(0).shape
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assert input_data_shape is not None
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if not node.has_valid('axis'):
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assert 1 in node.in_nodes()
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assert node.in_node(1).has_valid('value')
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assert node.in_node(1).value.size == 1
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node['axis'] = node.in_node(1).value.item()
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node.in_port(1).disconnect()
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assert node.has_valid('axis')
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assert len(node.out_nodes()) == 1
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node.out_node().shape = input_data_shape.copy()
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if node.in_node().value is not None:
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node.out_node().value = np.flip(node.in_node().value, node['axis'])
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assert np.array_equal(int64_array(node.out_node().value.shape), input_data_shape)
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