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- # Copyright 2020 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 logging
- import numpy as np
- import mindspore.context as context
- import mindspore.ops.composite as C
- from mindspore import Tensor
- from mindspore.nn import Cell
- from mindspore.ops import operations as P
- from mindspore.nn.composite_ops import ReLU
-
- log = logging.getLogger("ME")
- log.setLevel(level=logging.DEBUG)
- context.set_context(mode=context.GRAPH_MODE, save_graphs=True, device_target="Ascend")
-
- class NetBackwordFuse1(Cell):
- def __init__(self):
- super(NetBackwordFuse1, self).__init__()
- self.relu = ReLU()
- self.reduce_sum = P.ReduceSum(keep_dims=True)
-
- def construct(self, x):
- relu = self.relu(x)
- mul = P.Mul()(relu, 2.0)
- add = relu + mul
- out = self.reduce_sum(add, (0, ))
- return out
-
- class NetBackwordFuse2(Cell):
- def __init__(self):
- super(NetBackwordFuse2, self).__init__()
- self.relu = ReLU()
- self.reduce_sum = P.ReduceSum(keep_dims=True)
-
- def construct(self, x):
- relu = self.relu(x)
- mul = P.Mul()(relu, 2.0)
- reduce = self.reduce_sum(relu, (0, ))
- div = 1.0 / reduce
- add1 = reduce + div
- out = relu + add1
- return out
-
- def test_composite_fuse1():
- x = np.random.normal(0, 1, [2, 3, 1, 3]).astype(np.float32)
- net = NetBackwordFuse1()
- result = net(Tensor(x))
- print("================relu result=======================")
- print("x: {}".format(x))
- print("result: {}".format(result))
- print("=======================================")
-
- def test_composite_fuse2():
- x = np.random.normal(0, 1, [2, 3, 1, 3]).astype(np.float32)
- net = NetBackwordFuse2()
- result = net(Tensor(x))
- print("================relu result=======================")
- print("x: {}".format(x))
- print("result: {}".format(result))
- print("=======================================")
-
- test_composite_fuse1()
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