Files
openvino/model-optimizer/extensions/front/kaldi/tdnn_component_replacer.py
T
Pavel Esir 2110a29b7c [MO] [Kaldi] Add TDNN Component (#1870)
* [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
2020-10-12 14:10:27 +03:00

96 lines
4.0 KiB
Python

"""
Copyright (C) 2018-2020 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from extensions.ops.MatMul import FullyConnected
from mo.front.common.replacement import FrontReplacementPattern
from mo.front.tf.graph_utils import create_op_with_const_inputs
from mo.graph.graph import Graph, Node
from mo.graph.graph import rename_nodes
from mo.ops.concat import Concat
from mo.ops.memoryoffset import MemoryOffset
class TdnnComponentReplacer(FrontReplacementPattern):
'''
Expand TdnnComponent into MemoryOffsets, Concat and FullyConected nodes
BEFORE:
placeholder
|
TdnnComponent('time_offsets': t1, t2,... tk)
|
_______________________________________________________________
AFTER:
placeholder
__________________|___________________________
/ | \ \
MemoryOffset(t1) MemoryOffset(t2) ... MemoryOffset(tk)
\_____________ _____|______________/____________/
Concat
|
FullyConnected
|
'''
enabled = True
run_not_recursively = True
def run_before(self):
from extensions.front.kaldi.memory_offset_adjustment import MemoryOffsetAdjustment
return [MemoryOffsetAdjustment]
def find_and_replace_pattern(self, graph: Graph):
for node in graph.get_op_nodes(op='tdnncomponent'):
self.replace_tdnn(graph, node)
def replace_tdnn(self, graph: Graph, tdnn_node: Node):
tdnn_name = tdnn_node.soft_get('name', tdnn_node.id)
concat_node = Concat(graph, {'axis': 1}).create_node()
rename_nodes([(tdnn_node, tdnn_name + '/to_be_removed'), (concat_node, tdnn_name)])
for offset_ind, t in enumerate(tdnn_node['time_offsets']):
concat_node.add_input_port(offset_ind)
if t != 0:
memory_name = tdnn_name + '/MemoryOffset/' + str(abs(t))
memoryoffset_node = MemoryOffset(graph, {'name': memory_name, 't': t,
'pair_name': memory_name + '_out',
'has_default': False, 'splitted': False}).create_node()
tdnn_node.in_port(0).get_source().connect(memoryoffset_node.in_port(0))
memoryoffset_node.out_port(0).connect(concat_node.in_port(offset_ind))
else:
# 0 time delay is not allowed in IE, it's meaningless
# if time offset is 0 then connect input of tdnncomponent directly to Concat without memoryoffset
tdnn_node.in_port(0).get_source().connect(concat_node.in_port(offset_ind))
weights = tdnn_node['weights']
fc_inputs = {1: weights}
bias_term = False
if tdnn_node.has_valid('biases'):
assert len(tdnn_node['biases']) == weights.shape[0]
fc_inputs.update({2: tdnn_node['biases']})
bias_term = True
fc_node = create_op_with_const_inputs(graph, FullyConnected, fc_inputs,
{'name': tdnn_name + '/FC', 'out-size': weights.shape[0],
'transpose_weights': True, 'bias_term': bias_term})
concat_node.out_port(0).connect(fc_node.in_port(0))
tdnn_node.in_port(0).disconnect()
tdnn_node.out_port(0).get_connection().set_source(fc_node.out_port(0))