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- # Copyright 2022 Huawei Technologies Co., Ltd
- #
- # 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
-
- import mindspore
- from mindspore import Tensor, nn
- from mindspore.ops import operations as P
- from mindspore.rewrite import SymbolTree, ScopedValue, Node, NodeType, TreeNodeHelper
- from mindspore.common.api import _cell_graph_executor
-
-
- class SubNet(nn.Cell):
- def __init__(self):
- super().__init__()
- self.conv = nn.Conv2d(1, 10, 3)
- self.bn = nn.BatchNorm2d(10)
-
- def construct(self, x):
- x = self.conv(x)
- x = self.bn(x)
- return x
-
-
- class MainNet(nn.Cell):
- def __init__(self):
- super(MainNet, self).__init__()
- self.conv1 = SubNet()
- self.conv2 = SubNet()
- self.add = P.Add()
-
- def construct(self, x):
- x1 = self.conv1(x)
- x2 = self.conv2(x)
- x = self.add(x1, x2)
- return x
-
-
- def add_relu_in_conv1(stree: SymbolTree):
- for node in stree.nodes():
- if node.get_node_type() != NodeType.Tree:
- continue
- if node.get_name() == "conv1":
- modify_stree: SymbolTree = TreeNodeHelper.get_sub_tree(node)
- for inner_node in modify_stree.nodes():
- if inner_node.get_node_type() != NodeType.Output:
- continue
- position = modify_stree.before(inner_node)
- new_relu = nn.ReLU()
- new_relu_node = Node.create_call_cell(new_relu, targets=['x'], name='new_relu',
- args=[ScopedValue.create_naming_value('x')])
- modify_stree.insert(position, new_relu_node)
- modify_stree.set_output(0, new_relu_node.get_targets()[0].value)
- break
- break
-
-
- def replace_bn_in_conv2(stree: SymbolTree):
- for node in stree.nodes():
- if node.get_node_type() != NodeType.Tree:
- continue
- if node.get_name() == "conv2":
- modify_stree: SymbolTree = TreeNodeHelper.get_sub_tree(node)
- for inner_node in modify_stree.nodes():
- if inner_node.get_instance_type() != nn.BatchNorm2d:
- continue
- new_relu = nn.ReLU()
- new_relu_node = Node.create_call_cell(new_relu, targets=['x'], name='new_relu',
- args=inner_node.get_args(), kwargs=inner_node.get_kwargs())
- modify_stree.replace(inner_node, [new_relu_node])
- break
- break
-
-
- def erase_relu_in_conv2(stree: SymbolTree):
- for node in stree.nodes():
- if node.get_node_type() != NodeType.Tree:
- continue
- if node.get_name() == "conv2":
- modify_stree: SymbolTree = TreeNodeHelper.get_sub_tree(node)
- for inner_node in modify_stree.nodes():
- if inner_node.get_instance_type() != nn.ReLU:
- continue
- assert len(inner_node.get_args()) == 1
- arg = inner_node.get_args()[0]
- modify_stree.set_output(0, arg.value)
- modify_stree.erase_node(inner_node)
- break
- break
-
-
- def transform(stree: SymbolTree):
- add_relu_in_conv1(stree)
- replace_bn_in_conv2(stree)
- erase_relu_in_conv2(stree)
-
-
- def test_subtree_net():
- """
- Feature: Rewrite package api: sub-tree.
- Description: Use Rewrite to parse and transform a network with sub-network.
- Expectation: Rewrite can parse a network with sub-network and can modify node in sub-network successfully.
- """
-
- net = MainNet()
- stree = SymbolTree.create(net)
- transform(stree)
- print(stree.get_code())
- print(stree.get_handler().get_global_vars().keys())
- net_opt = stree.get_network()
- data_in = Tensor(np.ones([1, 1, 32, 32]), mindspore.float32)
- _cell_graph_executor.compile(net_opt, data_in)
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