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

133 lines
6.4 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.
"""
import numpy as np
from extensions.ops.Cast import Cast
from extensions.ops.gather import Gather
from mo.front.caffe.extractors.utils import get_canonical_axis_index
from mo.front.common.partial_infer.utils import int64_array
from mo.front.tf.graph_utils import create_op_with_const_inputs
from mo.graph.graph import Graph, rename_nodes
from mo.graph.port import Port
from mo.middle.replacement import MiddleReplacementPattern
from mo.ops.clamp import Clamp
from mo.ops.concat import Concat
from mo.ops.const import Const
from mo.ops.strided_slice import StridedSlice
def create_ss_interval_border(graph: Graph, slice_border_port: Port, shape: np.ndarray, axes: np.ndarray, node_name: str):
"""
This function creates "begin"/"end" parameters for the StridedSlice based on Slice's "starts"/"ends"
:param graph: graph to operate on.
:param slice_border_port: node output port that provides "starts"/"ends" values for the Slice.
:param shape: input shape of the Slice
:param axes: axes that "starts" and "ends" apply to
:param node_name: Slice node name
:return: Concat node that forms "begin"/"end" values for the StridedSlice
"""
# the value for 'starts' or 'ends' might be maximum/minimum possible value of int64. This
# value must be converted to maximum/minimum of int32 because such big values do not fit into the int32 which is
# supported by the StridedSlice layer
clamp = create_op_with_const_inputs(
graph, Clamp, port_value_dict={1: np.iinfo(np.int32).min, 2: np.iinfo(np.int32).max},
op_attrs=dict(name=node_name + '/Clamp'))
clamp.in_port(0).connect(slice_border_port)
# we have to convert "starts"/"ends" values from the network to one data type with constant values that are created
# here to prevent type errors in Concat node
cast = Cast(graph, dict(name=node_name + '/CastToI64', dst_type=np.int64)).create_node()
cast.in_port(0).connect(clamp.out_port(0))
concat = Concat(graph, dict(name=node_name + '/Concat', axis=0)).create_node()
for value_idx, port_idx in enumerate(axes):
concat.add_input_port(port_idx)
# "axes" may not be sorted, so we need to split "starts"/"ends" values and connect each value to the correct
# Concat input port
value = create_op_with_const_inputs(
graph, Gather, port_value_dict={1: int64_array([value_idx]), 2: int64_array(0)},
op_attrs={'name': node_name + '/Gather'})
cast.out_port(0).connect(value.in_port(0))
value.out_port(0).connect(concat.in_port(port_idx))
for port_idx in range(len(shape)):
if not concat.is_in_port_connected(port_idx):
concat.add_input_port(port_idx)
# This border value would be ignored in StridedSlice because of the begin_mask\end_mask
const = Const(graph, dict(name=node_name + '/Const', value=int64_array([0]))).create_node()
const.out_port(0).connect(concat.in_port(port_idx))
return concat
class ConvertSlice(MiddleReplacementPattern):
"""
This class converts a Slice operation to StridedSlice in reshape-able way by parsing the 'starts' and 'ends'
parameters based on the 'axes' parameter
"""
enabled = True
force_clean_up = True
def find_and_replace_pattern(self, graph: Graph):
for node in graph.get_op_nodes(op='Slice'):
node_name = node.soft_get('name', node.id)
input_shape = node.in_port(0).data.get_shape()
if node.is_in_port_connected(3):
axes = node.in_port(3).data.get_value().copy()
assert axes is not None, 'The input with axes is not constant for node {}'.format(node_name)
for i, val in enumerate(axes):
axes[i] = get_canonical_axis_index(input_shape, val)
else:
axes = int64_array(range(len(input_shape)))
ss_begin = create_ss_interval_border(graph, node.in_port(1).get_source(), input_shape, axes, node_name)
ss_end = create_ss_interval_border(graph, node.in_port(2).get_source(), input_shape, axes, node_name)
node.in_port(1).disconnect()
node.in_port(2).disconnect()
rename_nodes([(ss_begin, node_name + '/Begin'), (ss_end, node_name + '/End')])
if node.is_in_port_connected(4):
steps = node.in_port(4).data.get_value()
assert steps is not None, 'The input with steps is not constant for node {}'.format(node_name)
else:
steps = np.ones([axes.size])
ss_begin_mask = np.zeros(len(input_shape), dtype=np.int64)
ss_end_mask = np.zeros(len(input_shape), dtype=np.int64)
ss_step = np.ones(len(input_shape), dtype=np.int64)
for i, axis in enumerate(axes):
ss_begin_mask[axis] = 1
ss_end_mask[axis] = 1
ss_step[axis] = steps[i]
ss_strides = Const(graph, dict(name=node_name + '/Strides', value=ss_step)).create_node()
ss = StridedSlice(graph, dict(name='ss', new_axis_mask=np.zeros(len(input_shape), dtype=np.int64),
shrink_axis_mask=np.zeros(len(input_shape), dtype=np.int64),
ellipsis_mask=np.zeros(len(input_shape), dtype=np.int64),
begin_mask=ss_begin_mask,
end_mask=ss_end_mask)).create_node()
node.in_port(0).get_connection().set_destination(ss.in_port(0))
ss.in_port(1).connect(ss_begin.out_port(0))
ss.in_port(2).connect(ss_end.out_port(0))
ss.in_port(3).connect(ss_strides.out_port(0))
node.out_port(0).get_connection().set_source(ss.out_port(0))
rename_nodes([(node, node_name + '/ShouldBeDeleted'), (ss, node_name)])