dwSun commented on a change in pull request #8894: Mobilenet URL: https://github.com/apache/incubator-mxnet/pull/8894#discussion_r155160506
########## File path: example/image-classification/symbols/mobilenet.py ########## @@ -14,48 +14,129 @@ # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. - +# -*- coding:utf-8 -*- import mxnet as mx -def Conv(data, num_filter=1, kernel=(1, 1), stride=(1, 1), pad=(0, 0), num_group=1, name=None, suffix=''): - conv = mx.sym.Convolution(data=data, num_filter=num_filter, kernel=kernel, num_group=num_group, stride=stride, pad=pad, no_bias=True, name='%s%s_conv2d' %(name, suffix)) - bn = mx.sym.BatchNorm(data=conv, name='%s%s_batchnorm' %(name, suffix), fix_gamma=True) - act = mx.sym.Activation(data=bn, act_type='relu', name='%s%s_relu' %(name, suffix)) +__author__ = 'qingzhouzhen' +modified_date = '17/8/5' +__modify__ = 'dwSun' +modified_date = '17/11/30' + +''' +mobilenet + Suittable for image with around resolution x resolution, resolution is multiple of 32. + +Reference: + MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications + https://arxiv.org/abs/1704.04861 +''' + +alpha_values = [0.25, 0.50, 0.75, 1.0] + + +def Conv(data, num_filter=1, kernel=(1, 1), stride=(1, 1), pad=(0, 0), num_group=1, name='', suffix=''): + conv = mx.sym.Convolution(data=data, num_filter=num_filter, kernel=kernel, num_group=num_group, stride=stride, pad=pad, no_bias=True, name='%s%s_conv2d' % (name, suffix)) + bn = mx.sym.BatchNorm(data=conv, name='%s%s_batchnorm' % (name, suffix), fix_gamma=True) + act = mx.sym.Activation(data=bn, act_type='relu', name='%s%s_relu' % (name, suffix)) return act -def get_symbol(num_classes, **kwargs): - data = mx.symbol.Variable(name="data") # 224 - conv_1 = Conv(data, num_filter=32, kernel=(3, 3), pad=(1, 1), stride=(2, 2), name="conv_1") # 224/112 - conv_2_dw = Conv(conv_1, num_group=32, num_filter=32, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_2_dw") # 112/112 - conv_2 = Conv(conv_2_dw, num_filter=64, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_2") # 112/112 - conv_3_dw = Conv(conv_2, num_group=64, num_filter=64, kernel=(3, 3), pad=(1, 1), stride=(2, 2), name="conv_3_dw") # 112/56 - conv_3 = Conv(conv_3_dw, num_filter=128, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_3") # 56/56 - conv_4_dw = Conv(conv_3, num_group=128, num_filter=128, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_4_dw") # 56/56 - conv_4 = Conv(conv_4_dw, num_filter=128, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_4") # 56/56 - conv_5_dw = Conv(conv_4, num_group=128, num_filter=128, kernel=(3, 3), pad=(1, 1), stride=(2, 2), name="conv_5_dw") # 56/28 - conv_5 = Conv(conv_5_dw, num_filter=256, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_5") # 28/28 - conv_6_dw = Conv(conv_5, num_group=256, num_filter=256, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_6_dw") # 28/28 - conv_6 = Conv(conv_6_dw, num_filter=256, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_6") # 28/28 - conv_7_dw = Conv(conv_6, num_group=256, num_filter=256, kernel=(3, 3), pad=(1, 1), stride=(2, 2), name="conv_7_dw") # 28/14 - conv_7 = Conv(conv_7_dw, num_filter=512, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_7") # 14/14 - - conv_8_dw = Conv(conv_7, num_group=512, num_filter=512, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_8_dw") # 14/14 - conv_8 = Conv(conv_8_dw, num_filter=512, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_8") # 14/14 - conv_9_dw = Conv(conv_8, num_group=512, num_filter=512, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_9_dw") # 14/14 - conv_9 = Conv(conv_9_dw, num_filter=512, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_9") # 14/14 - conv_10_dw = Conv(conv_9, num_group=512, num_filter=512, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_10_dw") # 14/14 - conv_10 = Conv(conv_10_dw, num_filter=512, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_10") # 14/14 - conv_11_dw = Conv(conv_10, num_group=512, num_filter=512, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_11_dw") # 14/14 - conv_11 = Conv(conv_11_dw, num_filter=512, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_11") # 14/14 - conv_12_dw = Conv(conv_11, num_group=512, num_filter=512, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_12_dw") # 14/14 - conv_12 = Conv(conv_12_dw, num_filter=512, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_12") # 14/14 - - conv_13_dw = Conv(conv_12, num_group=512, num_filter=512, kernel=(3, 3), pad=(1, 1), stride=(2, 2), name="conv_13_dw") # 14/7 - conv_13 = Conv(conv_13_dw, num_filter=1024, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_13") # 7/7 - conv_14_dw = Conv(conv_13, num_group=1024, num_filter=1024, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_14_dw") # 7/7 - conv_14 = Conv(conv_14_dw, num_filter=1024, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_14") # 7/7 - - pool = mx.sym.Pooling(data=conv_14, kernel=(7, 7), stride=(1, 1), pool_type="avg", name="global_pool") + +def Conv_DPW(data, depth=1, stride=(1, 1), name='', idx=0, suffix=''): + conv_dw = Conv(data, num_group=depth, num_filter=depth, kernel=(3, 3), pad=(1, 1), stride=stride, name="conv_%d_dw" % (idx), suffix=suffix) + conv = Conv(conv_dw, num_filter=depth * stride[0], kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_%d" % (idx), suffix=suffix) + return conv + + +def get_symbol_compact(num_classes, alpha=1, resolution=224, **kwargs): Review comment: This function is a compact version of **get_symbol** with less lines of code. The network defined in this function is identical with **get_symbol**. I should add more docstring to explain that. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services
