Evgeny Lazarev
125a462400
* Initial version of ReduceL1, ReduceL2 and ReduceLp enabling in the MO * Added operations ReduceL1 and ReduceL2 to nGraph * Removed ReduceLp. Added ReduceL1 and ReduceL2 * Separated specification of ReduceLp into ReduceL1 and ReduceL2 * Updated ReduceL1 and ReduceL2 specification * Fixed ReduceL1 and ReduceL2 type prop tests * Implemented nGraph transformation to decompose ReduceL1 and ReduceL2. Disabled them for CPU and GPU plugins * Updated supported framework layers * Added unit tests for ReduceL1 and ReduceL2 reference implementation * Fixed ReduceXXX operations reference implementation by adding support for a new parameter 'keep_dims' * Fixed constant folding for v0::Any * Added ReduceL1 and ReduceL2 to Python API * Implemented ReduceL1 and ReduceL2 decomposition tests and fixed ReduceL2 decomposition * Added specific creator for ReduceXXX operations instead of NodeBuilders * Fixed conversion ReduceXXX to CNNLayer * Fixed parser for ReduceLogicalXXX operations
70 lines
2.9 KiB
Python
70 lines
2.9 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 generate, generator
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from extensions.ops.ReduceOps import reduce_infer
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from mo.front.common.partial_infer.utils import int64_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, result, connect, valued_const_with_data
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nodes_attributes = {
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**regular_op_with_shaped_data('data', [1, 3, 224, 224], {'type': 'Parameter', 'value': None,
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'_out_port_data_type': {0: np.float32}}),
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**valued_const_with_data('axis', int64_array(0)),
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**regular_op_with_shaped_data('reduce_lp', None, {'op': 'ReduceLp', 'type': None, 'name': 'my_reduce_lp'}),
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**regular_op_with_shaped_data('identity', None, {'op': 'Identity', 'name': 'identity'}),
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**result('output'),
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}
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@generator
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class ReduceLpTest(unittest.TestCase):
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@generate(*[
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([3, 2, 2], [0], True, 1),
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([3, 2, 2], [0], True, 2),
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([3, 2, 2], [1], True, 2),
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([3, 2, 2], [2], True, 2),
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([3, 2, 2], [0], False, 1),
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([3, 2, 2], [0], False, 2),
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([3, 2, 2], [1], False, 2),
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([3, 2, 2], [2], False, 2),
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])
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def test_reduce_lp(self, shape, axes, keepdims, p):
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data = np.reshape(np.arange(1, np.prod(shape) + 1, dtype=np.float32), shape)
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reduced = np.power(np.sum(a=np.abs(np.power(data, p)), axis=tuple(axes), keepdims=keepdims), 1 / p)
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axis = int64_array(axes)
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p = int64_array(p)
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graph = build_graph(nodes_attributes,
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[*connect('data', '0:reduce_lp'),
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*connect('axis', '1:reduce_lp'),
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*connect('reduce_lp', '0:identity'),
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('identity', 'identity_d', {'out': 0}),
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('identity_d', 'output')
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],
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{'data_d': {'value': data, 'shape': data.shape},
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'axis_d': {'value': axis, 'shape': axis.shape},
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'reduce_lp': {'keep_dims': keepdims}},
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nodes_with_edges_only=True)
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reduce_node = Node(graph, 'reduce_lp')
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reduce_node.op = reduce_node.type = 'ReduceL' + str(p)
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reduce_infer(reduce_node)
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self.assertTrue(np.array_equal(reduce_node.out_port(0).data.get_value(), reduced))
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