2110a29b7c
* [MO] [Kaldi] Added TDNN Component * TdnnComponent replacer graphical comment updated * Added SpecAugmentTimeMaskComponent * some refactor of memoryoffset shape_infer * moved memoryoffset splitting to the middle stage * some corrections - set `need_shape_inferenc`=False in split_memoryoffset - use cycle instead of pattern in tdnn_replacer * separated splitting of MemoryOffsets in LSTM and TDNN blocks * set transpose_weights=True in TdnnComponent * Corrected Supported_Frameworks_Layers * corrected comments * separate naming for tdnn and lstm memoryoffset splits * corrected BOM file * corrected generaldropout_ext.py and removed 'has_default' for tdnn_component * corrections after PR review * renamed LSTM -> recurrent; added setting element_size for paired nodes of tdnn_memoffset and othe minor changes * Update split_tdnn_memoryoffset.py * corrected partial infer with new API in elemental.py and split_tdnn_memoryoffset.py
47 lines
1.4 KiB
Python
47 lines
1.4 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 mo.front.common.partial_infer.elemental import copy_shape_infer
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from mo.graph.graph import Graph, Node
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from mo.ops.op import Op
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class MemoryOffset(Op):
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op = 'MemoryOffset'
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enabled = False
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def __init__(self, graph: Graph, attrs: dict):
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super().__init__(graph, {
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'op': 'MemoryOffset',
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'type': None,
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'pair_name': None,
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'splitted': False,
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'has_default': False,
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'infer': __class__.infer,
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'in_ports_count': 1,
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'out_ports_count': 1,
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}, attrs)
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@staticmethod
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def infer(node: Node):
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if node.has_valid('element_size'):
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# element_size should be set by Kaldi loader or by MemoryOffsetAdjustment
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node.out_port(0).data.set_shape([1, node['element_size']])
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else:
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# for TDNN blocks
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copy_shape_infer(node)
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