d86019d104
* Refactored LeakyRelu transformation * Added unit test for LeakyRelu transformation + removed duplicate test function valued_const
74 lines
2.8 KiB
Python
74 lines
2.8 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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import unittest
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import numpy as np
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from generator import generator, generate
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from extensions.ops.one_hot import OneHot
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from mo.front.common.partial_infer.utils import int64_array, float_array
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from mo.graph.graph import Node
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from mo.utils.unittest.graph import build_graph, regular_op_with_shaped_data, valued_const_with_data, connect
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def generate_nodes(data, axis=-1, depth=4, on_value=1., off_value=0.):
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return {
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'indices': {'Op': 'Parameter', 'value': data, 'shape': int64_array(data.shape)},
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'indices_d': {'kind': 'data', 'value': data, 'shape': int64_array(data.shape)},
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**valued_const_with_data('depth', int64_array(depth)),
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**valued_const_with_data('on_value', float_array(on_value)),
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**valued_const_with_data('off_value', float_array(off_value)),
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**regular_op_with_shaped_data('one_hot', None, {'type': 'OneHot', 'axis': axis, 'Op': 'OneHot'})
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}
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edges = [
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*connect('indices:0', 'one_hot:0'),
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*connect('depth:0', 'one_hot:1'),
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*connect('on_value:0', 'one_hot:2'),
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*connect('off_value:0', 'one_hot:3'),
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('one_hot', 'one_hot_d')
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]
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@generator
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class TestOneHotInfer(unittest.TestCase):
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@generate(*[
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# 0d input
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(1, [0, 1, 0, 0]),
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# 1d input
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([1, 2], [[0, 1, 0, 0], [0, 0, 1, 0]]),
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# 2D input
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([[1, 2], [3, 4]], [[[0, 1, 0, 0], [0, 0, 1, 0]],
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[[0, 0, 0, 1], [0, 0, 0, 0]]]),
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# 3d input
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([[[0, 2], [1, 2]], [[2, 1], [3, 0]]],
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[[[[1, 0, 0, 0], [0, 0, 1, 0]], [[0, 1, 0, 0], [0, 0, 1, 0]]],
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[[[0, 0, 1, 0], [0, 1, 0, 0]], [[0, 0, 0, 1], [1, 0, 0, 0]]]]),
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# 1d input with negative indices
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([-2, 2], [[0, 0, 1, 0], [0, 0, 1, 0]]),
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# check if axis is neither 0 nor -1
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([[1, 2], [3, 4]], [[[0, 0], [1, 0], [0, 1], [0, 0]],
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[[0, 0], [0, 0], [0, 0], [1, 0]]], 1)
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])
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def test_infer(self, input_value, exp_value, axis=-1):
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graph = build_graph(generate_nodes(int64_array(input_value), axis), edges)
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onehot_node = Node(graph, 'one_hot')
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OneHot.infer(onehot_node)
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res_value = graph.node['one_hot_d']['value']
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self.assertTrue(np.array_equal(exp_value, int64_array(res_value)))
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