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
81 lines
3.3 KiB
Python
81 lines
3.3 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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from typing import Dict
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import numpy as np
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from extensions.back.FuseTransposesSequence import FuseTransposesSequence
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from extensions.back.ReduceMerge import ReduceMerge
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from extensions.ops.ReduceOps import reduce_map
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from extensions.ops.gather import Gather
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from mo.back.replacement import BackReplacementPattern
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from mo.front.common.partial_infer.utils import int64_array
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from mo.front.tf.graph_utils import create_op_with_const_inputs
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from mo.graph.graph import Graph, Node
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class TransposeReduce(BackReplacementPattern):
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"""
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Fuse Transpose--->Reduce to Reduce with correct reduce axis input
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"""
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# TODO: Make another implementation, this is a temporary solution for one case
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enabled = True
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force_clean_up = True
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def run_before(self):
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return [ReduceMerge]
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def run_after(self):
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return [FuseTransposesSequence]
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@staticmethod
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def pattern():
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return dict(
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nodes=[
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('transpose_const', dict(kind='op', type='Const', value=lambda v: v is not None and
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np.array_equal(v, int64_array([0, 2, 3, 1])))),
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('transpose_const_data', dict(kind='data')),
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('transpose', dict(kind='op', type='Transpose')),
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('transpose_data', dict(kind='data')),
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('reduce_const', dict(kind='op', type='Const', value=lambda v: v is not None and
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np.array_equal(v, int64_array([1, 2])))),
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('reduce_const_data', dict(kind='data')),
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('reduce', dict(kind='op', type=lambda t: t in reduce_map.keys(), keep_dims=False))
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],
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edges=[
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('transpose_const', 'transpose_const_data'),
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('transpose_const_data', 'transpose', {'in': 1}),
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('transpose', 'transpose_data'),
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('transpose_data', 'reduce', {'in': 0}),
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('reduce_const', 'reduce_const_data'),
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('reduce_const_data', 'reduce', {'in': 1})
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]
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)
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@staticmethod
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def replace_pattern(graph: Graph, match: Dict[str, Node]):
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transpose = match['transpose']
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reduce = match['reduce']
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gather = create_op_with_const_inputs(graph, op=Gather, port_value_dict={2: int64_array(0)},
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op_attrs={'name': reduce.name + 'Gather'})
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transpose.in_port(1).get_connection().set_destination(gather.in_port(0))
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reduce.in_port(1).get_connection().set_destination(gather.in_port(1))
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gather.out_port(0).connect(reduce.in_port(1))
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transpose.out_port(0).disconnect()
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transpose.in_port(0).get_connection().set_destination(reduce.in_port(0))
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