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"""
Copyright (c) 2018 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.
"""
import networkx as nx
import numpy as np
from mo.middle.replacement import MiddleReplacementPattern
from mo.ops.crop import Crop
from mo.ops.op import Op
def convert_negative_indices(indices: np.array, shape: np.array):
for ind, value in enumerate(indices):
if value < 0:
indices[ind] += shape[ind]
class ConvertSlice(MiddleReplacementPattern):
"""
This class convert Slice operation to Crop or Split depends on parameters
"""
enabled = True
op = "Slice"
def pattern(self):
return dict(
nodes=[
('slice',dict(kind='op', op='Slice'))
],
edges=[]
)
def replace_pattern(self, graph: nx.MultiDiGraph, match: dict):
node = match['slice']
# Caffe case
if not node.has_valid('start') or not node.has_valid('end'):
return
begin = node.start
end = node.end
input = node.in_node(0)
output_data = node.out_node()
# Check whether operation use only one axis or not
dims = 0
axes = np.zeros(begin.size)
for i in range(begin.size):
if begin[i] != 0 or end[i] != input.shape[i]:
dims += 1
axes[i] = 1
axes = np.array(axes, dtype=bool)
if dims == 0:
return
elif dims == 1:
# If Slice use only one axis, than
# convert Slice to StridedSlice
node['op'] = 'StridedSlice'
node['type'] = 'StridedSlice'
convert_negative_indices(begin, input.shape)
convert_negative_indices(end, input.shape)
else:
# If Slice use more than one axis use Crop layer
crop = Crop(graph, dict(axis=np.arange(begin.size)[axes],
offset=begin[axes]))
# creating node with data
crop.create_node_with_data(inputs=[input], data_nodes=[output_data])
# Remove unnecessary edges from and to to Slice vertex
graph.remove_edge(input.id, node.id)
graph.remove_edge(node.id, output_data.id)
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