Kerasに組み込まれているXceptionの実装
Posted On 2018-07-21
新刊情報
技術書典8の新刊『モザイク除去から学ぶ 最先端のディープラーニング』（A4・195ページ）好評通販中です！ 機械学習の入門からGANの最先端までを書いたおすすめの本となっています！ Boothで試し読みできます。情報まとめ・質問用GitHub
Xceptionのsummary
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) (None, None, None, 3 0
__________________________________________________________________________________________________
block1_conv1 (Conv2D) (None, None, None, 3 864 input_1[0][0]
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, None, None, 3 128 block1_conv1[0][0]
__________________________________________________________________________________________________
block1_conv1_act (Activation) (None, None, None, 3 0 block1_conv1_bn[0][0]
__________________________________________________________________________________________________
block1_conv2 (Conv2D) (None, None, None, 6 18432 block1_conv1_act[0][0]
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, None, None, 6 256 block1_conv2[0][0]
__________________________________________________________________________________________________
block1_conv2_act (Activation) (None, None, None, 6 0 block1_conv2_bn[0][0]
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, None, None, 1 8768 block1_conv2_act[0][0]
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, None, None, 1 512 block2_sepconv1[0][0]
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, None, None, 1 0 block2_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, None, None, 1 17536 block2_sepconv2_act[0][0]
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, None, None, 1 512 block2_sepconv2[0][0]
__________________________________________________________________________________________________
conv2d_1 (Conv2D) (None, None, None, 1 8192 block1_conv2_act[0][0]
__________________________________________________________________________________________________
block2_pool (MaxPooling2D) (None, None, None, 1 0 block2_sepconv2_bn[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, None, None, 1 512 conv2d_1[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, None, None, 1 0 block2_pool[0][0]
batch_normalization_1[0][0]
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, None, None, 1 0 add_1[0][0]
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, None, None, 2 33920 block3_sepconv1_act[0][0]
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, None, None, 2 1024 block3_sepconv1[0][0]
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, None, None, 2 0 block3_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, None, None, 2 67840 block3_sepconv2_act[0][0]
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, None, None, 2 1024 block3_sepconv2[0][0]
__________________________________________________________________________________________________
conv2d_2 (Conv2D) (None, None, None, 2 32768 add_1[0][0]
__________________________________________________________________________________________________
block3_pool (MaxPooling2D) (None, None, None, 2 0 block3_sepconv2_bn[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, None, None, 2 1024 conv2d_2[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, None, None, 2 0 block3_pool[0][0]
batch_normalization_2[0][0]
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, None, None, 2 0 add_2[0][0]
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, None, None, 7 188672 block4_sepconv1_act[0][0]
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block4_sepconv1[0][0]
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, None, None, 7 0 block4_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block4_sepconv2_act[0][0]
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block4_sepconv2[0][0]
__________________________________________________________________________________________________
conv2d_3 (Conv2D) (None, None, None, 7 186368 add_2[0][0]
__________________________________________________________________________________________________
block4_pool (MaxPooling2D) (None, None, None, 7 0 block4_sepconv2_bn[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, None, None, 7 2912 conv2d_3[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, None, None, 7 0 block4_pool[0][0]
batch_normalization_3[0][0]
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, None, None, 7 0 add_3[0][0]
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block5_sepconv1_act[0][0]
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block5_sepconv1[0][0]
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, None, None, 7 0 block5_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block5_sepconv2_act[0][0]
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block5_sepconv2[0][0]
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, None, None, 7 0 block5_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block5_sepconv3_act[0][0]
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block5_sepconv3[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, None, None, 7 0 block5_sepconv3_bn[0][0]
add_3[0][0]
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, None, None, 7 0 add_4[0][0]
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block6_sepconv1_act[0][0]
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block6_sepconv1[0][0]
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, None, None, 7 0 block6_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block6_sepconv2_act[0][0]
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block6_sepconv2[0][0]
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, None, None, 7 0 block6_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block6_sepconv3_act[0][0]
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block6_sepconv3[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, None, None, 7 0 block6_sepconv3_bn[0][0]
add_4[0][0]
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, None, None, 7 0 add_5[0][0]
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block7_sepconv1_act[0][0]
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block7_sepconv1[0][0]
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, None, None, 7 0 block7_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block7_sepconv2_act[0][0]
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block7_sepconv2[0][0]
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, None, None, 7 0 block7_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block7_sepconv3_act[0][0]
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block7_sepconv3[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, None, None, 7 0 block7_sepconv3_bn[0][0]
add_5[0][0]
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, None, None, 7 0 add_6[0][0]
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block8_sepconv1_act[0][0]
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block8_sepconv1[0][0]
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, None, None, 7 0 block8_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block8_sepconv2_act[0][0]
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block8_sepconv2[0][0]
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, None, None, 7 0 block8_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block8_sepconv3_act[0][0]
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block8_sepconv3[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, None, None, 7 0 block8_sepconv3_bn[0][0]
add_6[0][0]
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, None, None, 7 0 add_7[0][0]
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block9_sepconv1_act[0][0]
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block9_sepconv1[0][0]
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, None, None, 7 0 block9_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block9_sepconv2_act[0][0]
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block9_sepconv2[0][0]
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, None, None, 7 0 block9_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block9_sepconv3_act[0][0]
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block9_sepconv3[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, None, None, 7 0 block9_sepconv3_bn[0][0]
add_7[0][0]
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, None, None, 7 0 add_8[0][0]
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, None, None, 7 536536 block10_sepconv1_act[0][0]
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block10_sepconv1[0][0]
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, None, None, 7 0 block10_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, None, None, 7 536536 block10_sepconv2_act[0][0]
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, None, None, 7 2912 block10_sepconv2[0][0]
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, None, None, 7 0 block10_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, None, None, 7 536536 block10_sepconv3_act[0][0]
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, None, None, 7 2912 block10_sepconv3[0][0]
__________________________________________________________________________________________________
add_9 (Add) (None, None, None, 7 0 block10_sepconv3_bn[0][0]
add_8[0][0]
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, None, None, 7 0 add_9[0][0]
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, None, None, 7 536536 block11_sepconv1_act[0][0]
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block11_sepconv1[0][0]
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, None, None, 7 0 block11_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, None, None, 7 536536 block11_sepconv2_act[0][0]
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, None, None, 7 2912 block11_sepconv2[0][0]
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, None, None, 7 0 block11_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, None, None, 7 536536 block11_sepconv3_act[0][0]
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, None, None, 7 2912 block11_sepconv3[0][0]
__________________________________________________________________________________________________
add_10 (Add) (None, None, None, 7 0 block11_sepconv3_bn[0][0]
add_9[0][0]
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, None, None, 7 0 add_10[0][0]
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, None, None, 7 536536 block12_sepconv1_act[0][0]
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block12_sepconv1[0][0]
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, None, None, 7 0 block12_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, None, None, 7 536536 block12_sepconv2_act[0][0]
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, None, None, 7 2912 block12_sepconv2[0][0]
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, None, None, 7 0 block12_sepconv2_bn[0][0]
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, None, None, 7 536536 block12_sepconv3_act[0][0]
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, None, None, 7 2912 block12_sepconv3[0][0]
__________________________________________________________________________________________________
add_11 (Add) (None, None, None, 7 0 block12_sepconv3_bn[0][0]
add_10[0][0]
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, None, None, 7 0 add_11[0][0]
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, None, None, 7 536536 block13_sepconv1_act[0][0]
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block13_sepconv1[0][0]
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, None, None, 7 0 block13_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, None, None, 1 752024 block13_sepconv2_act[0][0]
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, None, None, 1 4096 block13_sepconv2[0][0]
__________________________________________________________________________________________________
conv2d_4 (Conv2D) (None, None, None, 1 745472 add_11[0][0]
__________________________________________________________________________________________________
block13_pool (MaxPooling2D) (None, None, None, 1 0 block13_sepconv2_bn[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, None, None, 1 4096 conv2d_4[0][0]
__________________________________________________________________________________________________
add_12 (Add) (None, None, None, 1 0 block13_pool[0][0]
batch_normalization_4[0][0]
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, None, None, 1 1582080 add_12[0][0]
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, None, None, 1 6144 block14_sepconv1[0][0]
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, None, None, 1 0 block14_sepconv1_bn[0][0]
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, None, None, 2 3159552 block14_sepconv1_act[0][0]
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, None, None, 2 8192 block14_sepconv2[0][0]
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, None, None, 2 0 block14_sepconv2_bn[0][0]
__________________________________________________________________________________________________
avg_pool (GlobalAveragePooling2 (None, 2048) 0 block14_sepconv2_act[0][0]
__________________________________________________________________________________________________
predictions (Dense) (None, 1000) 2049000 avg_pool[0][0]
==================================================================================================
Total params: 22,910,480
Trainable params: 22,855,952
Non-trainable params: 54,528
__________________________________________________________________________________________________
モデル一覧
https://keras.io/ja/applicationsより
新刊情報
技術書典8の新刊『モザイク除去から学ぶ 最先端のディープラーニング』好評通販中（A4・195ページ）です！ Boothで試し読みもできるのでよろしくね！
【一般同人】「じゅ～しぃ～すくりぷと」の『モザイク除去から学ぶ 最先端のディープラーニング』が3Fにて好評販売中！今作は誰もが夢見る"モザイク除去"を起点として機械学習・ディープラーニングの知識をたっぷり学べる注目作品。初心者向けの話題からマニアックな情報まで網羅しております！！ pic.twitter.com/HX1wAXESod
— とらのあな 秋葉原店A (@tora_akiba_a) March 8, 2020
これが君の望んでいる、「ディープラーニング－ロマン－」
— こしあん@技術書典8 Day2 あ03 委託 (@js_koshian2) March 22, 2020
誰もが夢見る「モザイク除去」から機械学習を学ぼう。ご好評につき鋭意増刷中！
Booth：https://t.co/d2oXBf0kQ6
とら：https://t.co/5P0HJ7r8sL
試し読み：https://t.co/1z2XScVNsz#技術書典 pic.twitter.com/tttO6VnTXG
- Booth（物理、電子版）：https://koshian2.booth.pm/items/1835219
- とらのあな（物理版：お急ぎの場合はとらのあなをお使いください。Boothよりも物理本の到着が早いです（即日で発送されます）。電子版プレゼントキャンペーンもあります ：https://ec.toranoana.shop/tora/ec/item/040030818462/
- メロンブックス（物理版）https://www.melonbooks.co.jp/detail/detail.php?product_id=670234（電子版とセットになります）
- 感想・情報まとめ・質問用：https://github.com/koshian2/MosaicDeeplearningBook