100 lines
3.9 KiB
Python
100 lines
3.9 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.middle.ONNXRNNSequenceNormalize import ONNXRNNSequenceNormalize
|
|
from extensions.middle.TF_lstm_cell_to_generic import TensorFlowLSTMtoGeneric
|
|
from extensions.middle.TensorIteratorMerge import TensorIteratorMerge
|
|
from mo.graph.graph import Graph
|
|
from mo.middle.pattern_match import find_isomorphisms
|
|
from mo.middle.replacement import MiddleReplacementPattern
|
|
from mo.utils.error import Error
|
|
|
|
|
|
class TensorIteratorLSTM(MiddleReplacementPattern):
|
|
""" Detects TensorIterator with LSTMCell of supported form.
|
|
|
|
Collect original operation names of supported LSTMCells in
|
|
the list LSTMCell.instances_supported_by_IE. It will be used at the second
|
|
round of the network translation. Mark all supported LSTMCell with flag
|
|
supported_by_IE to have a chance to detect all not-supported instances
|
|
in a separate pass.
|
|
"""
|
|
|
|
enabled = False
|
|
|
|
def run_after(self):
|
|
return [TensorIteratorMerge, ONNXRNNSequenceNormalize, TensorFlowLSTMtoGeneric]
|
|
|
|
def pattern(self):
|
|
return dict(
|
|
nodes=[
|
|
('ti', dict(kind='op', op='TensorIterator')),
|
|
],
|
|
edges=[
|
|
]
|
|
)
|
|
|
|
@staticmethod
|
|
def replace_pattern(graph: Graph, match: dict):
|
|
nodes = [
|
|
('input_unsqueezed'),
|
|
('squeeze', dict(op='Reshape')),
|
|
('input_squeezed'),
|
|
('input_hidden'),
|
|
('input_cell'),
|
|
('weights'),
|
|
('biases'),
|
|
|
|
('lstm', dict(op='LSTMCell')),
|
|
|
|
('output_hidden'),
|
|
('output_cell'),
|
|
('unsqueeze', dict(op='Reshape')),
|
|
('output_unsqueezed'),
|
|
]
|
|
edges = [
|
|
('input_unsqueezed', 'squeeze'),
|
|
('squeeze', 'input_squeezed'),
|
|
|
|
('input_squeezed', 'lstm', {'in': 0}),
|
|
('input_hidden', 'lstm', {'in': 1}),
|
|
('input_cell', 'lstm', {'in': 2}),
|
|
('weights', 'lstm', {'in': 3}),
|
|
('biases', 'lstm', {'in': 4}),
|
|
|
|
('lstm', 'output_hidden', {'out': 0}),
|
|
('lstm', 'output_cell', {'out': 1}),
|
|
|
|
('output_hidden', 'unsqueeze'),
|
|
('unsqueeze', 'output_unsqueezed'),
|
|
]
|
|
ti = match['ti']
|
|
isomorphisms = find_isomorphisms(ti.body, nodes, edges)
|
|
if len(list(isomorphisms)) != 1:
|
|
raise Error('Unsupported TensorIterator layer {} was found: either its body, ports or '
|
|
'edges are not supported by Inference Engine. '
|
|
'Only TensorIterator with LSTMCell in a body of strict form is supported. '
|
|
'Please modify the original network '
|
|
'to meet the requirements.'.format(ti.soft_get('name')))
|
|
body_match = isomorphisms[0]
|
|
if body_match['input_hidden'].has_valid('value') or body_match['input_cell'].has_valid('value'):
|
|
raise Error('Unsupported TensorIterator layer {} was found: initial hidden and/or cell states '
|
|
'for LSTMCell are constants. This is not supported. '
|
|
'Only TensorIterator with LSTMCell in a body of strict form is supported. '
|
|
'Please modify the original network '
|
|
'to meet the requirements.'.format(ti.soft_get('name')))
|
|
# TODO Additional checks for port indices
|