1# Copyright 2019 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================ 15import numpy as np 16 17import mindspore.context as context 18import mindspore.nn as nn 19from mindspore import Tensor 20from mindspore.common.api import ms_function 21from mindspore.common.initializer import initializer 22from mindspore.common.parameter import Parameter 23from mindspore.ops import operations as P 24 25context.set_context(device_target="Ascend") 26 27 28class Net(nn.Cell): 29 def __init__(self): 30 super(Net, self).__init__() 31 out_channel = 64 32 kernel_size = 7 33 self.conv = P.Conv2D(out_channel, 34 kernel_size, 35 mode=1, 36 pad_mode="valid", 37 pad=0, 38 stride=1, 39 dilation=1, 40 group=1) 41 self.w = Parameter(initializer( 42 'normal', [64, 3, 7, 7]), name='w') 43 44 @ms_function 45 def construct(self, x): 46 return self.conv(x, self.w) 47 48 49def test_net(): 50 x = np.random.randn(32, 3, 224, 224).astype(np.float32) 51 conv = Net() 52 output = conv(Tensor(x)) 53 print(output.asnumpy()) 54