openvino/model-optimizer/extensions/back/ProposalMutation.py

89 lines
4.2 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 logging as log
import numpy as np
from extensions.back.ReshapeMutation import ReshapeMutation
from extensions.back.StridedSliceMasksNormalizer import StridedSliceMasksNormalizer
from mo.back.replacement import BackReplacementPattern
from mo.front.common.partial_infer.utils import int64_array
from mo.graph.graph import Graph
from mo.ops.const import Const
from mo.ops.reshape import Reshape
from mo.ops.strided_slice import StridedSlice
class ProposalMutation(BackReplacementPattern):
enabled = True
force_clean_up = True
graph_condition = [lambda graph: graph.graph['cmd_params'].generate_experimental_IR_V10]
def run_before(self):
return [ReshapeMutation, StridedSliceMasksNormalizer]
@staticmethod
def pattern():
return dict(
nodes=[('proposal', {'type': 'Proposal'})],
edges=[],
)
@staticmethod
def replace_pattern(graph: Graph, match: dict):
node = match['proposal']
assert len(node.in_ports()) == 3, "Proposal op must have exactly 3 input ports"
im_info_shape = node.in_port(2).data.get_shape()
assert im_info_shape is not None
if np.array_equal(im_info_shape, [1, 6]):
log.error('The model contains Proposal layer "{}" with input of shape [1, 6]. Inference Engine '
'implementation of the Proposal layer uses only 4 first values (indices 0, 1, 2 and 3). '
'Elements with indices 4 and 5 will be ignored.'.format(node.soft_get('name', node.id)),
extra={'is_warning': True})
begin = Const(graph, {'value': np.array([0, 0], dtype=np.int32)}).create_node()
end = Const(graph, {'value': np.array([1, 3], dtype=np.int32)}).create_node()
stride = Const(graph, {'value': np.array([1, 1], dtype=np.int32)}).create_node()
cropped_im_info = StridedSlice(graph, {'name': 'cropped_im_info',
'begin_mask': int64_array([1, 1]),
'end_mask': int64_array([1, 1]),
'new_axis_mask': int64_array([0]),
'shrink_axis_mask': int64_array([0]),
'ellipsis_mask': int64_array([0]),
'override_output_shape': True,
}).create_node()
node.in_port(2).get_connection().insert_node(cropped_im_info)
begin.out_port(0).connect(cropped_im_info.in_port(1))
end.out_port(0).connect(cropped_im_info.in_port(2))
stride.out_port(0).connect(cropped_im_info.in_port(3))
# update the im_info_shape so the next 'if' statement become true
im_info_shape = int64_array([1, 3])
if np.array_equal(im_info_shape, [1, 3]) or np.array_equal(im_info_shape, [1, 4]):
reshape = Reshape(graph, dict(name="im_info/Reshape")).create_node()
const = Const(graph, dict(value=[im_info_shape[1]])).create_node()
node.in_port(2).get_connection().set_destination(reshape.in_port(0))
const.out_port(0).connect(reshape.in_port(1))
reshape.out_port(0).connect(node.in_port(2))
if node.has_port('out', 1) and not node.out_port(1).disconnected():
# This is the case when Proposal layer is used from extension, not from opset.
# Setting version attribute is not recommended, this will be fixed after Proposal will be updated in IE.
graph.node[node.id]['version'] = 'extension'