openvino/model-optimizer/extensions/middle/ReplaceSpliceNodePattern.py

146 lines
7.1 KiB
Python

"""
Copyright (c) 2018-2019 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.front.kaldi.replace_lstm_node_pattern import unique_id
from extensions.ops.splitv import SplitV
from mo.front.common.partial_infer.utils import int64_array
from mo.graph.graph import Graph
from mo.middle.replacement import MiddleReplacementPattern
from mo.ops.concat import Concat
from mo.ops.crop import Crop
from mo.ops.memory import Memory
from mo.ops.result import Result
class ReplaceSpliceNodePattern(MiddleReplacementPattern):
"""
This pass decomposes Splice layer to the sequence Slice Concat and Memory layers
For example:
Let's suppose we have next graph:
Input (N, H) -> Slice -> Next_Layer (N, k*H)
Where (N, k*H) is is real input of subsequent topology.
Splice is used for accumulation next (k-1)/2 and previous (k-1)/2 input data
So this pass will convert this graph to the next one:
Input [N, H] __
\ /
Concat [N, k*H]
/ \
Memory [N, k*H] -> Slice [N, (k-1)*H] Memory [N, k*H]
"""
enabled = False
@staticmethod
def pattern():
return dict(
nodes=[('op', dict(op='Splice'))],
edges=[])
@staticmethod
def replace_pattern(graph: Graph, match: dict):
node = match['op']
in_shape = node.in_port(0).data.get_shape().copy()
memory_element = in_shape[1] - node.const_dim
memory_size = memory_element * len(node.context)
memory_pair_id = unique_id('id')
# Memory(in)
input_memory = Memory(graph, {'name': 'prev_splice_memory',
'id': memory_pair_id,
'index': 1,
'size': 2,
'shape': int64_array([memory_size])}).create_node()
# Memory(in) \
# Crop
# Input(temp) /
crop = Crop(graph, {'name': 'Splice_Crop',
'axis': int64_array([1]),
'offset': int64_array([memory_element]),
'dim': int64_array([memory_size - memory_element])}).create_node()
crop.in_port(0).connect(input_memory.out_port(0))
# Crop \
# Concat
# Input /
concat_node = Concat(graph, {'name': 'Splice_Concat',
'in_ports_count': 2,
'axis': 1}).create_node()
concat_node.in_port(0).connect(crop.out_port(0))
# Concat -> Memory(out)
mem_out = Memory(graph, {'name': 'out_splice_memory',
'id': memory_pair_id,
'index': 0,
'size': 2,
'shape': int64_array([memory_size])}).create_node()
mem_out.in_port(0).connect(concat_node.out_port(0))
Result(graph).create_node().in_port(0).connect(mem_out.out_port(0))
if node.const_dim != 0:
memory_element_constdim = node.const_dim
memory_size_constdim = memory_element_constdim * len(node.context)
split = SplitV(graph, {'name': node.id + '_split_const', 'axis': 1, 'out_ports_count': 2,
'size_splits': int64_array([memory_element, memory_element_constdim])}).create_node()
split.out_port(0).connect(concat_node.in_port(1))
# create separate splice construction for const_dim
memory_pair_id = unique_id('memory_for_const_dim')
input_memory_const_dim = Memory(graph, {'name': 'const_dim_in_memory',
'id': memory_pair_id,
'index': 1,
'size': 2,
'shape': int64_array([memory_size_constdim])}).create_node()
crop_const_dim = Crop(graph, {'name': 'const_dim_crop',
'axis': int64_array([1]),
'offset': int64_array([memory_element_constdim]),
'dim': int64_array([memory_size_constdim - memory_element_constdim])}).create_node()
crop_const_dim.in_port(0).connect(input_memory_const_dim.out_port(0))
concat_node_const_dim = Concat(graph, {'name': 'const_dim_concat',
'in_ports_count': 2,
'axis': 1}).create_node()
concat_node_const_dim.in_port(0).connect(crop_const_dim.out_port(0))
mem_out_const_dim = Memory(graph, {'name': 'const_dim_out_memory',
'id': memory_pair_id,
'index': 0,
'size': 2,
'shape': int64_array([memory_size_constdim])}).create_node()
mem_out_const_dim.in_port(0).connect(concat_node_const_dim.out_port(0))
Result(graph).create_node().in_port(0).connect(mem_out_const_dim.out_port(0))
# connect splice to Split as begin and Concat as the end
split.out_port(1).connect(concat_node_const_dim.in_port(1))
crop_first = Crop(graph, {'name': 'const_dim_crop_first',
'axis': int64_array([1]),
'offset': int64_array([0]),
'dim': int64_array([memory_element_constdim])}).create_node()
crop_first.in_port(0).connect(concat_node_const_dim.out_port(0))
concat_const = Concat(graph, {'name': node.id+'_concat_const', 'axis': 1,
'in_ports_count': 2}).create_node()
concat_const.in_port(1).connect(crop_first.out_port(0))
concat_const.in_port(0).connect(concat_node.out_port(0))
node.in_port(0).get_connection().set_destination(split.in_port(0))
node.out_port(0).get_connection().set_source(concat_const.out_port(0))
else:
node.in_port(0).get_connection().set_destination(concat_node.in_port(1))
node.out_port(0).get_connection().set_source(concat_node.out_port(0))