forked from mindspore-Ecosystem/mindspore
79 lines
2.1 KiB
Python
79 lines
2.1 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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"""
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test pooling api
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"""
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import numpy as np
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.common.api import _executor
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class AvgNet(nn.Cell):
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def __init__(self,
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kernel_size,
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stride=None):
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super(AvgNet, self).__init__()
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self.avgpool = nn.AvgPool2d(kernel_size, stride)
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def construct(self, x):
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return self.avgpool(x)
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def test_compile_avg():
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net = AvgNet(3, 1)
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x = Tensor(np.ones([1, 3, 16, 50]).astype(np.float32))
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_executor.compile(net, x)
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class MaxNet(nn.Cell):
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""" MaxNet definition """
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def __init__(self,
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kernel_size,
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stride=None,
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padding=0):
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_ = padding
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super(MaxNet, self).__init__()
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self.maxpool = nn.MaxPool2d(kernel_size,
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stride)
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def construct(self, x):
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return self.maxpool(x)
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def test_compile_max():
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net = MaxNet(3, stride=1, padding=0)
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x = Tensor(np.random.randint(0, 255, [1, 3, 6, 6]).astype(np.float32))
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_executor.compile(net, x)
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class Avg1dNet(nn.Cell):
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def __init__(self,
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kernel_size,
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stride=None):
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super(Avg1dNet, self).__init__()
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self.avg1d = nn.AvgPool1d(kernel_size, stride)
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def construct(self, x):
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return self.avg1d(x)
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def test_avg1d():
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net = Avg1dNet(6, 1)
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input_ = Tensor(np.random.randint(0, 255, [1, 3, 6]).astype(np.float32))
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_executor.compile(net, input_)
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