122 lines
4.3 KiB
Python
122 lines
4.3 KiB
Python
"""
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Copyright (C) 2018-2020 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import numpy as np
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from extensions.ops.split import AttributedSplit
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from mo.back.replacement import BackReplacementPattern
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from mo.front.common.partial_infer.utils import int64_array
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from mo.graph.graph import Graph
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class SplitNormalizer(BackReplacementPattern):
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enabled = True
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graph_condition = [lambda graph: not graph.graph['cmd_params'].generate_experimental_IR_V10]
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def find_and_replace_pattern(self, graph: Graph):
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for node in graph.get_op_nodes(op='Split'):
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name = node.soft_get('name', node.id)
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input_shape = node.in_port(0).data.get_shape()
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assert input_shape is not None
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axis = node.in_port(1).data.get_value()
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assert axis is not None
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num_splits = node.soft_get('num_splits', None)
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assert num_splits is not None
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if axis < 0:
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axis += input_shape.size
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split = AttributedSplit(graph, {'name': name, 'axis': axis, 'num_splits': num_splits}).create_node()
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for idx, port in node.out_ports().items():
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node.out_port(idx).get_connection().set_source(split.out_port(idx))
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node.in_port(0).get_connection().set_destination(split.in_port(0))
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graph.remove_node(node.id)
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class VariadicSplitNormalizer(BackReplacementPattern):
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enabled = True
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graph_condition = [lambda graph: not graph.graph['cmd_params'].generate_experimental_IR_V10]
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def find_and_replace_pattern(self, graph: Graph):
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for node in graph.get_op_nodes(op='VariadicSplit'):
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name = node.soft_get('name', node.id)
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input_shape = node.in_port(0).data.get_shape()
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assert input_shape is not None
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axis = node.in_port(1).data.get_value()
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assert axis is not None
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size_splits = node.in_port(2).data.get_value()
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assert size_splits is not None
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connected_outputs = {idx: port for idx, port in node.out_ports().items() if not port.disconnected()}
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assert len(size_splits) >= len(connected_outputs)
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split_size = connected_outputs[list(connected_outputs.keys())[0]].data.get_shape()[axis]
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if np.unique(size_splits).size != 1:
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return
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# all split sizes are equal
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assert input_shape[axis] % split_size == 0
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num_splits = int64_array(input_shape[axis] / split_size)
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assert num_splits is not None
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if axis < 0:
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axis += input_shape.size
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split = AttributedSplit(graph, {'name': name, 'axis': axis, 'num_splits': num_splits}).create_node()
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for idx, port in node.out_ports().items():
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node.out_port(idx).get_connection().set_source(split.out_port(idx))
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node.in_port(0).get_connection().set_destination(split.in_port(0))
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graph.remove_node(node.id)
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class PassVariadicSplitAsIs(BackReplacementPattern):
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enabled = True
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force_clean_up = True
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graph_condition = [lambda graph: not graph.graph['cmd_params'].generate_experimental_IR_V10]
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def run_after(self):
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return [VariadicSplitNormalizer]
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def find_and_replace_pattern(self, graph: Graph):
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for node in graph.get_op_nodes(op='VariadicSplit'):
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input_shape = node.in_port(0).data.get_shape()
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assert input_shape is not None
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axis = node.in_port(1).data.get_value()
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assert axis is not None
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node.in_port(1).disconnect()
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size_splits = node.in_port(2).data.get_value()
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assert size_splits is not None
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node.in_port(2).disconnect()
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if axis < 0:
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axis += input_shape.size
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node['type'] = 'Split'
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node['axis'] = axis
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