为什么MobileNet的参数这么少
我是用的MobileNet v2版本，這篇文章不是什么高明的文章，實(shí)際上其他很多地方都有介紹，本人只是驗(yàn)證一下，作為備忘
像VGGNet這樣的神經(jīng)網(wǎng)絡(luò)，因?yàn)槿慷际怯玫腃onv2D，所以參數(shù)量較大，隨便一層卷積就需要2M以上的參數(shù)量，如
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block4_pool (MaxPooling2D) ? (None, 14, 14, 512) ? ? ? 0 ? ? ? ??
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block5_conv1 (Conv2D) ? ? ? ?(None, 14, 14, 512) ? ? ? 2359808 ??
?
參數(shù)量為 3 * 3 * 512 * 512 + 512 =?2359808
而MobileNet在3*3的卷積時(shí)用的是DepthwiseConv2D，而在Conv2D時(shí)用的是1*1的卷積核，所以大大減少了參數(shù)量，
MobileNet沒有用到池化，而是在用3*3卷積核做DepthwiseConv2D運(yùn)算時(shí)配置步長為2來降低尺寸，
詳細(xì)結(jié)構(gòu)參考如下：
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Layer (type) ? ? ? ? ? ? ? ? ? ?Output Shape ? ? ? ? Param # ? ? Connected to
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input_1 (InputLayer) ? ? ? ? ? ?(None, 224, 224, 3) ?0
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Conv1_pad (ZeroPadding2D) ? ? ? (None, 225, 225, 3) ?0 ? ? ? ? ? input_1[0][0]
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Conv1 (Conv2D) ? ? ? ? ? ? ? ? ?(None, 112, 112, 32) 864 ? ? ? ? Conv1_pad[0][0] ? ? ? ? ? ? ? ? ? 3 * 3 * 3 * 32
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bn_Conv1 (BatchNormalization) ? (None, 112, 112, 32) 128 ? ? ? ? Conv1[0][0]
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Conv1_relu (ReLU) ? ? ? ? ? ? ? (None, 112, 112, 32) 0 ? ? ? ? ? bn_Conv1[0][0]
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expanded_conv_depthwise (Depthw (None, 112, 112, 32) 288 ? ? ? ? Conv1_relu[0][0] ? ? ? ? ? ? ? ? ?3 * 3 * 32
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expanded_conv_depthwise_BN (Bat (None, 112, 112, 32) 128 ? ? ? ? expanded_conv_depthwise[0][0]
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expanded_conv_depthwise_relu (R (None, 112, 112, 32) 0 ? ? ? ? ? expanded_conv_depthwise_BN[0][0]
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expanded_conv_project (Conv2D) ?(None, 112, 112, 16) 512 ? ? ? ? expanded_conv_depthwise_relu[0][0 1 * 1 * 32 * 16
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expanded_conv_project_BN (Batch (None, 112, 112, 16) 64 ? ? ? ? ?expanded_conv_project[0][0]
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block_1_expand (Conv2D) ? ? ? ? (None, 112, 112, 96) 1536 ? ? ? ?expanded_conv_project_BN[0][0] ? ?1 * 1 * 16 * 96
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block_1_expand_BN (BatchNormali (None, 112, 112, 96) 384 ? ? ? ? block_1_expand[0][0]
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block_1_expand_relu (ReLU) ? ? ?(None, 112, 112, 96) 0 ? ? ? ? ? block_1_expand_BN[0][0]
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block_1_pad (ZeroPadding2D) ? ? (None, 113, 113, 96) 0 ? ? ? ? ? block_1_expand_relu[0][0]
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block_1_depthwise (DepthwiseCon (None, 56, 56, 96) ? 864 ? ? ? ? block_1_pad[0][0] ? ? ? ? ? ? ? ? 3 * 3 * 96
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block_1_depthwise_BN (BatchNorm (None, 56, 56, 96) ? 384 ? ? ? ? block_1_depthwise[0][0]
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block_1_depthwise_relu (ReLU) ? (None, 56, 56, 96) ? 0 ? ? ? ? ? block_1_depthwise_BN[0][0]
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block_1_project (Conv2D) ? ? ? ?(None, 56, 56, 24) ? 2304 ? ? ? ?block_1_depthwise_relu[0][0] ? ? ?1 * 1 * 96 * 24
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block_1_project_BN (BatchNormal (None, 56, 56, 24) ? 96 ? ? ? ? ?block_1_project[0][0]
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block_2_expand (Conv2D) ? ? ? ? (None, 56, 56, 144) ?3456 ? ? ? ?block_1_project_BN[0][0] ? ? ? ? ?1 * 1 * 24 * 144
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block_2_expand_BN (BatchNormali (None, 56, 56, 144) ?576 ? ? ? ? block_2_expand[0][0]
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block_2_expand_relu (ReLU) ? ? ?(None, 56, 56, 144) ?0 ? ? ? ? ? block_2_expand_BN[0][0]
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block_2_depthwise (DepthwiseCon (None, 56, 56, 144) ?1296 ? ? ? ?block_2_expand_relu[0][0] ? ? ? ? 3 * 3 * 144
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block_2_depthwise_BN (BatchNorm (None, 56, 56, 144) ?576 ? ? ? ? block_2_depthwise[0][0]
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block_2_depthwise_relu (ReLU) ? (None, 56, 56, 144) ?0 ? ? ? ? ? block_2_depthwise_BN[0][0]
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block_2_project (Conv2D) ? ? ? ?(None, 56, 56, 24) ? 3456 ? ? ? ?block_2_depthwise_relu[0][0] ? ? ?1 * 1 * 24 * 144
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block_2_project_BN (BatchNormal (None, 56, 56, 24) ? 96 ? ? ? ? ?block_2_project[0][0]
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block_2_add (Add) ? ? ? ? ? ? ? (None, 56, 56, 24) ? 0 ? ? ? ? ? block_1_project_BN[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_2_project_BN[0][0]
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block_3_expand (Conv2D) ? ? ? ? (None, 56, 56, 144) ?3456 ? ? ? ?block_2_add[0][0] ? ? ? ? ? ? ? ? 1 * 1 * 24 * 144
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block_3_expand_BN (BatchNormali (None, 56, 56, 144) ?576 ? ? ? ? block_3_expand[0][0]
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block_3_expand_relu (ReLU) ? ? ?(None, 56, 56, 144) ?0 ? ? ? ? ? block_3_expand_BN[0][0]
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block_3_pad (ZeroPadding2D) ? ? (None, 57, 57, 144) ?0 ? ? ? ? ? block_3_expand_relu[0][0]
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block_3_depthwise (DepthwiseCon (None, 28, 28, 144) ?1296 ? ? ? ?block_3_pad[0][0] ? ? ? ? ? ? ? ? 3 * 3 * 144
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block_3_depthwise_BN (BatchNorm (None, 28, 28, 144) ?576 ? ? ? ? block_3_depthwise[0][0]
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block_3_depthwise_relu (ReLU) ? (None, 28, 28, 144) ?0 ? ? ? ? ? block_3_depthwise_BN[0][0]
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block_3_project (Conv2D) ? ? ? ?(None, 28, 28, 32) ? 4608 ? ? ? ?block_3_depthwise_relu[0][0] ? ? ?1 * 1 * 32 * 144
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block_3_project_BN (BatchNormal (None, 28, 28, 32) ? 128 ? ? ? ? block_3_project[0][0]
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block_4_expand (Conv2D) ? ? ? ? (None, 28, 28, 192) ?6144 ? ? ? ?block_3_project_BN[0][0] ? ? ? ? ?1 * 1 * 32 * 192
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block_4_expand_BN (BatchNormali (None, 28, 28, 192) ?768 ? ? ? ? block_4_expand[0][0]
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block_4_expand_relu (ReLU) ? ? ?(None, 28, 28, 192) ?0 ? ? ? ? ? block_4_expand_BN[0][0]
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block_4_depthwise (DepthwiseCon (None, 28, 28, 192) ?1728 ? ? ? ?block_4_expand_relu[0][0] ? ? ? ? 3 * 3 * 192
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block_4_depthwise_BN (BatchNorm (None, 28, 28, 192) ?768 ? ? ? ? block_4_depthwise[0][0]
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block_4_depthwise_relu (ReLU) ? (None, 28, 28, 192) ?0 ? ? ? ? ? block_4_depthwise_BN[0][0]
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block_4_project (Conv2D) ? ? ? ?(None, 28, 28, 32) ? 6144 ? ? ? ?block_4_depthwise_relu[0][0] ? ? ?1 * 1 * 192 * 32
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block_4_project_BN (BatchNormal (None, 28, 28, 32) ? 128 ? ? ? ? block_4_project[0][0]
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block_4_add (Add) ? ? ? ? ? ? ? (None, 28, 28, 32) ? 0 ? ? ? ? ? block_3_project_BN[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_4_project_BN[0][0]
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block_5_expand (Conv2D) ? ? ? ? (None, 28, 28, 192) ?6144 ? ? ? ?block_4_add[0][0] ? ? ? ? ? ? ? ? 1 * 1 * 32 * 192
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block_5_expand_BN (BatchNormali (None, 28, 28, 192) ?768 ? ? ? ? block_5_expand[0][0]
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block_5_expand_relu (ReLU) ? ? ?(None, 28, 28, 192) ?0 ? ? ? ? ? block_5_expand_BN[0][0]
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block_5_depthwise (DepthwiseCon (None, 28, 28, 192) ?1728 ? ? ? ?block_5_expand_relu[0][0] ? ? ? ? 3 * 3 * 192
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block_5_depthwise_BN (BatchNorm (None, 28, 28, 192) ?768 ? ? ? ? block_5_depthwise[0][0]
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block_5_depthwise_relu (ReLU) ? (None, 28, 28, 192) ?0 ? ? ? ? ? block_5_depthwise_BN[0][0]
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block_5_project (Conv2D) ? ? ? ?(None, 28, 28, 32) ? 6144 ? ? ? ?block_5_depthwise_relu[0][0] ? ? ?1 * 1 * 192 * 32
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block_5_project_BN (BatchNormal (None, 28, 28, 32) ? 128 ? ? ? ? block_5_project[0][0]
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block_5_add (Add) ? ? ? ? ? ? ? (None, 28, 28, 32) ? 0 ? ? ? ? ? block_4_add[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_5_project_BN[0][0]
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block_6_expand (Conv2D) ? ? ? ? (None, 28, 28, 192) ?6144 ? ? ? ?block_5_add[0][0] ? ? ? ? ? ? ? ? 1 * 1 * 32 * 192
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block_6_expand_BN (BatchNormali (None, 28, 28, 192) ?768 ? ? ? ? block_6_expand[0][0]
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block_6_expand_relu (ReLU) ? ? ?(None, 28, 28, 192) ?0 ? ? ? ? ? block_6_expand_BN[0][0]
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block_6_pad (ZeroPadding2D) ? ? (None, 29, 29, 192) ?0 ? ? ? ? ? block_6_expand_relu[0][0]
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block_6_depthwise (DepthwiseCon (None, 14, 14, 192) ?1728 ? ? ? ?block_6_pad[0][0] ? ? ? ? ? ? ? ? 3 * 3 * 192
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block_6_depthwise_BN (BatchNorm (None, 14, 14, 192) ?768 ? ? ? ? block_6_depthwise[0][0]
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block_6_depthwise_relu (ReLU) ? (None, 14, 14, 192) ?0 ? ? ? ? ? block_6_depthwise_BN[0][0]
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block_6_project (Conv2D) ? ? ? ?(None, 14, 14, 64) ? 12288 ? ? ? block_6_depthwise_relu[0][0] ? ? ?1 * 1 * 192 * 64
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block_6_project_BN (BatchNormal (None, 14, 14, 64) ? 256 ? ? ? ? block_6_project[0][0]
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block_7_expand (Conv2D) ? ? ? ? (None, 14, 14, 384) ?24576 ? ? ? block_6_project_BN[0][0] ? ? ? ? ?1 * 1 * 64 * 384
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block_7_expand_BN (BatchNormali (None, 14, 14, 384) ?1536 ? ? ? ?block_7_expand[0][0]
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block_7_expand_relu (ReLU) ? ? ?(None, 14, 14, 384) ?0 ? ? ? ? ? block_7_expand_BN[0][0]
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block_7_depthwise (DepthwiseCon (None, 14, 14, 384) ?3456 ? ? ? ?block_7_expand_relu[0][0] ? ? ? ? 3 * 3 * 384
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block_7_depthwise_BN (BatchNorm (None, 14, 14, 384) ?1536 ? ? ? ?block_7_depthwise[0][0]
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block_7_depthwise_relu (ReLU) ? (None, 14, 14, 384) ?0 ? ? ? ? ? block_7_depthwise_BN[0][0]
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block_7_project (Conv2D) ? ? ? ?(None, 14, 14, 64) ? 24576 ? ? ? block_7_depthwise_relu[0][0] ? ? ?1 * 1 * 384 * 64
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block_7_project_BN (BatchNormal (None, 14, 14, 64) ? 256 ? ? ? ? block_7_project[0][0]
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block_7_add (Add) ? ? ? ? ? ? ? (None, 14, 14, 64) ? 0 ? ? ? ? ? block_6_project_BN[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_7_project_BN[0][0]
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block_8_expand (Conv2D) ? ? ? ? (None, 14, 14, 384) ?24576 ? ? ? block_7_add[0][0] ? ? ? ? ? ? ? ? 1 * 1 * 64 * 384
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block_8_expand_BN (BatchNormali (None, 14, 14, 384) ?1536 ? ? ? ?block_8_expand[0][0]
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block_8_expand_relu (ReLU) ? ? ?(None, 14, 14, 384) ?0 ? ? ? ? ? block_8_expand_BN[0][0]
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block_8_depthwise (DepthwiseCon (None, 14, 14, 384) ?3456 ? ? ? ?block_8_expand_relu[0][0] ? ? ? ? 3 * 3 * 384
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block_8_depthwise_BN (BatchNorm (None, 14, 14, 384) ?1536 ? ? ? ?block_8_depthwise[0][0]
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block_8_depthwise_relu (ReLU) ? (None, 14, 14, 384) ?0 ? ? ? ? ? block_8_depthwise_BN[0][0]
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block_8_project (Conv2D) ? ? ? ?(None, 14, 14, 64) ? 24576 ? ? ? block_8_depthwise_relu[0][0] ? ? ?1 * 1 * 384 * 64
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block_8_project_BN (BatchNormal (None, 14, 14, 64) ? 256 ? ? ? ? block_8_project[0][0]
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block_8_add (Add) ? ? ? ? ? ? ? (None, 14, 14, 64) ? 0 ? ? ? ? ? block_7_add[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_8_project_BN[0][0]
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block_9_expand (Conv2D) ? ? ? ? (None, 14, 14, 384) ?24576 ? ? ? block_8_add[0][0] ? ? ? ? ? ? ? ? 1 * 1 * 64 * 384
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block_9_expand_BN (BatchNormali (None, 14, 14, 384) ?1536 ? ? ? ?block_9_expand[0][0]
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block_9_expand_relu (ReLU) ? ? ?(None, 14, 14, 384) ?0 ? ? ? ? ? block_9_expand_BN[0][0]
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block_9_depthwise (DepthwiseCon (None, 14, 14, 384) ?3456 ? ? ? ?block_9_expand_relu[0][0] ? ? ? ? 3 * 3 * 384
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block_9_depthwise_BN (BatchNorm (None, 14, 14, 384) ?1536 ? ? ? ?block_9_depthwise[0][0]
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block_9_depthwise_relu (ReLU) ? (None, 14, 14, 384) ?0 ? ? ? ? ? block_9_depthwise_BN[0][0]
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block_9_project (Conv2D) ? ? ? ?(None, 14, 14, 64) ? 24576 ? ? ? block_9_depthwise_relu[0][0] ? ? ?1 * 1 * 384 * 64
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block_9_project_BN (BatchNormal (None, 14, 14, 64) ? 256 ? ? ? ? block_9_project[0][0]
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block_9_add (Add) ? ? ? ? ? ? ? (None, 14, 14, 64) ? 0 ? ? ? ? ? block_8_add[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_9_project_BN[0][0]
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block_10_expand (Conv2D) ? ? ? ?(None, 14, 14, 384) ?24576 ? ? ? block_9_add[0][0] ? ? ? ? ? ? ? ? 1 * 1 * 64 * 384
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block_10_expand_BN (BatchNormal (None, 14, 14, 384) ?1536 ? ? ? ?block_10_expand[0][0]
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block_10_expand_relu (ReLU) ? ? (None, 14, 14, 384) ?0 ? ? ? ? ? block_10_expand_BN[0][0]
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block_10_depthwise (DepthwiseCo (None, 14, 14, 384) ?3456 ? ? ? ?block_10_expand_relu[0][0] ? ? ? ?3 * 3 * 384
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block_10_depthwise_BN (BatchNor (None, 14, 14, 384) ?1536 ? ? ? ?block_10_depthwise[0][0]
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block_10_depthwise_relu (ReLU) ?(None, 14, 14, 384) ?0 ? ? ? ? ? block_10_depthwise_BN[0][0]
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block_10_project (Conv2D) ? ? ? (None, 14, 14, 96) ? 36864 ? ? ? block_10_depthwise_relu[0][0] ? ? 1 * 1 * 384 * 96
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block_10_project_BN (BatchNorma (None, 14, 14, 96) ? 384 ? ? ? ? block_10_project[0][0]
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block_11_expand (Conv2D) ? ? ? ?(None, 14, 14, 576) ?55296 ? ? ? block_10_project_BN[0][0] ? ? ? ? 1 * 1 * 96 * 576
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block_11_expand_BN (BatchNormal (None, 14, 14, 576) ?2304 ? ? ? ?block_11_expand[0][0]
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block_11_expand_relu (ReLU) ? ? (None, 14, 14, 576) ?0 ? ? ? ? ? block_11_expand_BN[0][0]
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block_11_depthwise (DepthwiseCo (None, 14, 14, 576) ?5184 ? ? ? ?block_11_expand_relu[0][0] ? ? ? ?3 * 3 * 576
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block_11_depthwise_BN (BatchNor (None, 14, 14, 576) ?2304 ? ? ? ?block_11_depthwise[0][0]
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block_11_depthwise_relu (ReLU) ?(None, 14, 14, 576) ?0 ? ? ? ? ? block_11_depthwise_BN[0][0]
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block_11_project (Conv2D) ? ? ? (None, 14, 14, 96) ? 55296 ? ? ? block_11_depthwise_relu[0][0] ? ? 1 * 1 * 576 * 96
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block_11_project_BN (BatchNorma (None, 14, 14, 96) ? 384 ? ? ? ? block_11_project[0][0]
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block_11_add (Add) ? ? ? ? ? ? ?(None, 14, 14, 96) ? 0 ? ? ? ? ? block_10_project_BN[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_11_project_BN[0][0]
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block_12_expand (Conv2D) ? ? ? ?(None, 14, 14, 576) ?55296 ? ? ? block_11_add[0][0] ? ? ? ? ? ? ? ?1 * 1 * 96 * 576
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block_12_expand_BN (BatchNormal (None, 14, 14, 576) ?2304 ? ? ? ?block_12_expand[0][0]
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block_12_expand_relu (ReLU) ? ? (None, 14, 14, 576) ?0 ? ? ? ? ? block_12_expand_BN[0][0]
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block_12_depthwise (DepthwiseCo (None, 14, 14, 576) ?5184 ? ? ? ?block_12_expand_relu[0][0] ? ? ? ?3 * 3 * 576
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block_12_depthwise_BN (BatchNor (None, 14, 14, 576) ?2304 ? ? ? ?block_12_depthwise[0][0]
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block_12_depthwise_relu (ReLU) ?(None, 14, 14, 576) ?0 ? ? ? ? ? block_12_depthwise_BN[0][0]
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block_12_project (Conv2D) ? ? ? (None, 14, 14, 96) ? 55296 ? ? ? block_12_depthwise_relu[0][0] ? ? 1 * 1 * 576 * 96
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block_12_project_BN (BatchNorma (None, 14, 14, 96) ? 384 ? ? ? ? block_12_project[0][0]
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block_12_add (Add) ? ? ? ? ? ? ?(None, 14, 14, 96) ? 0 ? ? ? ? ? block_11_add[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_12_project_BN[0][0]
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block_13_expand (Conv2D) ? ? ? ?(None, 14, 14, 576) ?55296 ? ? ? block_12_add[0][0] ? ? ? ? ? ? ? ?1 * 1 * 96 * 576
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block_13_expand_BN (BatchNormal (None, 14, 14, 576) ?2304 ? ? ? ?block_13_expand[0][0]
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block_13_expand_relu (ReLU) ? ? (None, 14, 14, 576) ?0 ? ? ? ? ? block_13_expand_BN[0][0]
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block_13_pad (ZeroPadding2D) ? ?(None, 15, 15, 576) ?0 ? ? ? ? ? block_13_expand_relu[0][0]
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block_13_depthwise (DepthwiseCo (None, 7, 7, 576) ? ?5184 ? ? ? ?block_13_pad[0][0] ? ? ? ? ? ? ? ?3 * 3 * 576
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block_13_depthwise_BN (BatchNor (None, 7, 7, 576) ? ?2304 ? ? ? ?block_13_depthwise[0][0]
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block_13_depthwise_relu (ReLU) ?(None, 7, 7, 576) ? ?0 ? ? ? ? ? block_13_depthwise_BN[0][0]
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block_13_project (Conv2D) ? ? ? (None, 7, 7, 160) ? ?92160 ? ? ? block_13_depthwise_relu[0][0] ? ? 1 * 1 * 576 * 160
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block_13_project_BN (BatchNorma (None, 7, 7, 160) ? ?640 ? ? ? ? block_13_project[0][0]
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block_14_expand (Conv2D) ? ? ? ?(None, 7, 7, 960) ? ?153600 ? ? ?block_13_project_BN[0][0] ? ? ? ? 1 * 1 * 160 * 960
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block_14_expand_BN (BatchNormal (None, 7, 7, 960) ? ?3840 ? ? ? ?block_14_expand[0][0]
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block_14_expand_relu (ReLU) ? ? (None, 7, 7, 960) ? ?0 ? ? ? ? ? block_14_expand_BN[0][0]
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block_14_depthwise (DepthwiseCo (None, 7, 7, 960) ? ?8640 ? ? ? ?block_14_expand_relu[0][0] ? ? ? ?3 * 3 * 960
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block_14_depthwise_BN (BatchNor (None, 7, 7, 960) ? ?3840 ? ? ? ?block_14_depthwise[0][0]
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block_14_depthwise_relu (ReLU) ?(None, 7, 7, 960) ? ?0 ? ? ? ? ? block_14_depthwise_BN[0][0]
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block_14_project (Conv2D) ? ? ? (None, 7, 7, 160) ? ?153600 ? ? ?block_14_depthwise_relu[0][0] ? ? 1 * 1 * 960 * 160
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block_14_project_BN (BatchNorma (None, 7, 7, 160) ? ?640 ? ? ? ? block_14_project[0][0]
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block_14_add (Add) ? ? ? ? ? ? ?(None, 7, 7, 160) ? ?0 ? ? ? ? ? block_13_project_BN[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_14_project_BN[0][0]
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block_15_expand (Conv2D) ? ? ? ?(None, 7, 7, 960) ? ?153600 ? ? ?block_14_add[0][0] ? ? ? ? ? ? ? ?1 * 1 * 160 * 960
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block_15_expand_BN (BatchNormal (None, 7, 7, 960) ? ?3840 ? ? ? ?block_15_expand[0][0]
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block_15_expand_relu (ReLU) ? ? (None, 7, 7, 960) ? ?0 ? ? ? ? ? block_15_expand_BN[0][0]
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block_15_depthwise (DepthwiseCo (None, 7, 7, 960) ? ?8640 ? ? ? ?block_15_expand_relu[0][0] ? ? ? ?3 * 3 * 960
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block_15_depthwise_BN (BatchNor (None, 7, 7, 960) ? ?3840 ? ? ? ?block_15_depthwise[0][0]
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block_15_depthwise_relu (ReLU) ?(None, 7, 7, 960) ? ?0 ? ? ? ? ? block_15_depthwise_BN[0][0]
__________________________________________________________________________________________________
block_15_project (Conv2D) ? ? ? (None, 7, 7, 160) ? ?153600 ? ? ?block_15_depthwise_relu[0][0] ? ? 1 * 1 * 960 * 160
__________________________________________________________________________________________________
block_15_project_BN (BatchNorma (None, 7, 7, 160) ? ?640 ? ? ? ? block_15_project[0][0]
__________________________________________________________________________________________________
block_15_add (Add) ? ? ? ? ? ? ?(None, 7, 7, 160) ? ?0 ? ? ? ? ? block_14_add[0][0]
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?block_15_project_BN[0][0]
__________________________________________________________________________________________________
block_16_expand (Conv2D) ? ? ? ?(None, 7, 7, 960) ? ?153600 ? ? ?block_15_add[0][0] ? ? ? ? ? ? ? ?1 * 1 * 160 * 960
__________________________________________________________________________________________________
block_16_expand_BN (BatchNormal (None, 7, 7, 960) ? ?3840 ? ? ? ?block_16_expand[0][0]
__________________________________________________________________________________________________
block_16_expand_relu (ReLU) ? ? (None, 7, 7, 960) ? ?0 ? ? ? ? ? block_16_expand_BN[0][0]
__________________________________________________________________________________________________
block_16_depthwise (DepthwiseCo (None, 7, 7, 960) ? ?8640 ? ? ? ?block_16_expand_relu[0][0] ? ? ? ?3 * 3 * 960
__________________________________________________________________________________________________
block_16_depthwise_BN (BatchNor (None, 7, 7, 960) ? ?3840 ? ? ? ?block_16_depthwise[0][0]
__________________________________________________________________________________________________
block_16_depthwise_relu (ReLU) ?(None, 7, 7, 960) ? ?0 ? ? ? ? ? block_16_depthwise_BN[0][0]
__________________________________________________________________________________________________
block_16_project (Conv2D) ? ? ? (None, 7, 7, 320) ? ?307200 ? ? ?block_16_depthwise_relu[0][0] ? ? 1 * 1 * 960 * 320
__________________________________________________________________________________________________
block_16_project_BN (BatchNorma (None, 7, 7, 320) ? ?1280 ? ? ? ?block_16_project[0][0]
__________________________________________________________________________________________________
Conv_1 (Conv2D) ? ? ? ? ? ? ? ? (None, 7, 7, 1280) ? 409600 ? ? ?block_16_project_BN[0][0] ? ? ? ? 1 * 1 * 320 * 1280
__________________________________________________________________________________________________
Conv_1_bn (BatchNormalization) ?(None, 7, 7, 1280) ? 5120 ? ? ? ?Conv_1[0][0]
__________________________________________________________________________________________________
out_relu (ReLU) ? ? ? ? ? ? ? ? (None, 7, 7, 1280) ? 0 ? ? ? ? ? Conv_1_bn[0][0]
__________________________________________________________________________________________________
flatten_1 (Flatten) ? ? ? ? ? ? (None, 62720) ? ? ? ?0 ? ? ? ? ? out_relu[0][0]
__________________________________________________________________________________________________
dense_1 (Dense) ? ? ? ? ? ? ? ? (None, 0) ? ? ? ? ? ?0 ? ? ? ? ? flatten_1[0][0]
==================================================================================================
Total params: 2,257,984
Trainable params: 2,223,872
Non-trainable params: 34,112
?
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