20170419-TFUG

 20170419-TFUG

4月19日のTensorFlow User Groupの発表資料です。

Ece52fe9ce913851256726020707febd?s=128

Keiji ARIYAMA

April 19, 2017
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  1. C-LIS CO., LTD.

  2. C-LIS CO., LTD.  ༗ࢁܓೋʢ,FJKJ"3*:"."ʣ $-*4$0 -5% "OESPJEΞϓϦ։ൃνϣοτσΩϧ ػցֶशॳ৺ऀͱɺݴ͍ଓ͚ͯૣ̍೥൒ Photo

    : Koji MORIGUCHI (AUN CREATIVE FIRM)
  3. None
  4.  ݄̐̕೔ʢ೔ʣ ΞΩόɾεΫΤΞ ʰٕज़ॻయ̎ ͓ʔ̍̎ʱʹͯ TensorFlow͸͡Ί·ͨ͠
 Super Resolution ʔ ௒ղ૾

    https://goo.gl/Z3Exjo ׬ച͠·ͨ͠
  5. ৞ΈࠐΈΦʔτΤϯίʔμʔ  conv1 9x9x3 64 padding: SAME conv2 9x9x64 128

    conv4 5x5x128 64 conv3-0 7x7x128 128 conv3-1 7x7x128 128 dconv1 9x9x64 3 padding: SAME dconv2 9x9x128 64 dconv4 5x5x64 128 dconv3-1 7x7x128 128 dconv3-2 7x7x128 128 conv3-2 7x7x128 128 dconv3-2 7x7x128 128 256x256 256x256
  6. None
  7.  5FOTPS'MPX6TFS(SPVQ  5FOTPS'MPX
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  8.  5FOTPS'MPXͱ(16

  9. લఏ৚݅ (16$6%"$PNQVUF$BQBCJMJUZ $6%"5PPMLJU DV%//W QJQJOTUBMMUFOTPSqPXHQV  https://www.tensorflow.org/install/install_linux

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  12. Ϛϧν(16 BWH@HSBET@@BWFSBHF@HSBEJFOUT UPXFS@HSBET 
 
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  13. 5FOTPS#PBSE

  14. (16̍ͭʹׂΓ౰ͯΔॲཧ Input Pipeline tf.train.shuffle_batch Ϟσϧ
 model.inference ޡࠩؔ਺
 __loss ޯ഑ͷܭࢉ
 compute_gradient

    __tower_loss ޯ഑ ʢgradsʣ ֶश
 σʔλ ڭࢣ
 σʔλ ਪ࿦݁Ռ ޡࠩ
  15. શମͷॲཧ TOWER ޯ഑ ʢgradsʣ TOWER ޯ഑ ʢgradsʣ TOWER ޯ഑ ʢgradsʣ

    TOWER ޯ഑ ʢgradsʣ ޯ഑ͷฏۉΛܭࢉ
 __average_gradients શମͷޯ഑ ʢavg_gradsʣ ࠷దԽ
 __apply_gradients params params params params
  16.  %FNP

  17. ৞ΈࠐΈΦʔτΤϯίʔμʔ  conv2 9x9x64 128 conv4 5x5x128 64 conv3-0 7x7x128

    128 conv3-1 7x7x128 128 dconv2 9x9x128 64 dconv4 5x5x64 128 dconv3-1 7x7x128 128 dconv3-2 7x7x128 128 conv3-2 7x7x128 128 dconv3-2 7x7x128 128 256x256 256x256 conv1 9x9x3 64 padding: SAME dconv1 9x9x64 3 padding: SAME
  18. ख࣋ͪͷ(16αʔόʔ $16*OUFM$PSFJ, .FNPSZ(# 44%(# (F'PSDF(59(#
 $6%"DPSF  

  19. ͘͞ΒͷߴՐྗίϯϐϡʔςΟϯάʢ࣮ݧػʣ $169FPO$PSFʷ .FNPSZ(# 44%(# (F'PSDF(595*5"/9ʢ1BTDBMΞʔΩςΫνϟʣ(#ʷ
 $6%"DPSF  (F'PSDF(595Jʢ1BTDBMΞʔΩςΫνϟʣ(#ʷ
 $6%"DPSF 

    
  20.  https://blog.keiji.io/2016/05/cuda_error_no_device.html

  21. ύλʔϯ"ɿυϥΠόʔͷΞοϓσʔτ 

  22. E tensorflow/stream_executor/cuda/cuda_dnn.cc:347] Loaded runtime CuDNN library: 4007 (compatibility version 4000)

    but source was compiled with 5103 (compatibility version 5100).  ύλʔϯ#ɿ5FOTPS'MPXͷΞοϓσʔτ https://github.com/tensorflow/tensorflow/issues/4251
  23.  ύλʔϯ$

  24. None
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  26.  खݩͰ࣮ߦՄೳͳϞσϧͱɺ
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  27. ։ൃػ ͘͞ΒͷߴՐྗαʔόʔʢ2VBE(16Ϟσϧʣ $169FPO$PSFʷ .FNPSZ(# 44%(# (F'PSDF(595*5"/9ʢ.BYXFMMΞʔΩςΫνϟʣ(#ʷ
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    sample / batch learning rate 0.001
  28. https://www.sakura.ad.jp/press/2017/0417_koukaryoku_hourly/

  29. ݕূػ
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  30. ஗͍ʜʜ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ

    4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ  128 sample / batch learning rate 0.001
  31. (PPHMF$MPVE1MBUGPSN W$16 .FNPSZ 44% (F'PSDF5FTMB,ʢ(#ʷʣ
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  36.  : :

  37.  Hello, Thank you for requesting additional quota. To help

    us ensure that this is a legitimate request and that the resources you requested are available to you, please do one of the following: Make a payment [1] of $35 or the same amount in your currency from the Transaction History page [2] and reply to this message when the charge clears. Your payment will be applied to any charges you incur in the future and will be visible as a credit in your account. Alternatively, reply to this message with the project ID of another project that you own that has cleared a charge of at least the amount mentioned. To learn more about project quota requests and cores quota requests, check out the Project Quota Request FAQ page at [3] and the Request cores quota increase FAQs page at [4]. We appreciate your patience. Sincerely, Cloud Platform Support [1] - https://support.google.com/cloud/answer/6294016 [2] - https://console.cloud.google.com/billing [3] - https://support.google.com/cloud/answer/6330231 [4] - https://support.google.com/cloud/answer/6376374
  38.  Hello, Your quota request for Project '632906615582' has been

    approved and your project quota has been adjusted accordingly. Changed Quota: +--------------------+-----------------+ | Region: asia-east1 | NVIDIA_K80_GPUS | +--------------------+-----------------+ | Changes | 0 -> 1 | +--------------------+-----------------+ To verify the quota change, please navigate to https://console.developers.google.com/project/632906615582/compute/quotas and verify what are your current project quotas. Happy Computing! Google for Work Support http://support.google.com/enterprisehelp/
  39. (PPHMF$MPVE1MBUGPSN W$16 .FNPSZ(# 44%(# (F'PSDF5FTMB,ʢ(#ʷʣ
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  42. ˈUPQ 

  43.  (16͕ಈ͍ͯͳ͍

  44. DPOGJHUG$POGJH1SPUP 
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  45. I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_26: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_25: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841]

    save/RestoreV2_25: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_24: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_24: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_23: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_23: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_22: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_22: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_21: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_21: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_20: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 
  46. I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_8: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_7: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841]

    save/RestoreV2_7: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_6: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_6: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_5: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_5: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_4: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_4: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_3: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_3: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_2: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 
  47. I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2_2: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2_1: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841]

    save/RestoreV2_1: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 save/RestoreV2: (RestoreV2): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/RestoreV2: (RestoreV2)/ job:localhost/replica:0/task:0/cpu:0 conv3/biases/ExponentialMovingAverage: (VariableV2): /job:localhost/replica:0/task:0/ cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] conv3/biases/ ExponentialMovingAverage: (VariableV2)/job:localhost/replica:0/task:0/cpu:0 save/Assign_22: (Assign): /job:localhost/replica:0/task:0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] save/Assign_22: (Assign)/ job:localhost/replica:0/task:0/cpu:0 conv3/biases/ExponentialMovingAverage/read: (Identity): /job:localhost/replica:0/task: 0/cpu:0 I tensorflow/core/common_runtime/simple_placer.cc:841] conv3/biases/  ҎԼུ
  48. ΦϖϨʔγϣϯ͕࣮ߦ͞ΕΔσόΠε (16 $16 

  49. I tensorflow/core/common_runtime/simple_placer.cc:841] tower_0/image_loader_vvv/ ReaderReadV2: (ReaderReadV2)/job:localhost/replica:0/task:0/cpu:0 tower_0/image_loader_vvv/DecodeJpeg: (DecodeJpeg): /job:localhost/replica:0/task: 0/cpu:0 I

    tensorflow/core/common_runtime/simple_placer.cc:841] tower_0/image_loader_vvv/ DecodeJpeg: (DecodeJpeg)/job:localhost/replica:0/task:0/cpu:0 tower_0/image_loader_vvv/random_crop/Shape: (Shape): /job:localhost/replica:0/ task:0/gpu:0  EFDPEF@KQFH
  50. 

  51. 

  52. 

  53. 

  54. I tensorflow/core/common_runtime/simple_placer.cc:841] tower_0/image_loader_vvv/ ReaderReadV2: (ReaderReadV2)/job:localhost/replica:0/task:0/cpu:0 tower_0/image_loader_vvv/DecodeJpeg: (DecodeJpeg): /job:localhost/replica:0/task: 0/cpu:0 I

    tensorflow/core/common_runtime/simple_placer.cc:841] tower_0/image_loader_vvv/ DecodeJpeg: (DecodeJpeg)/job:localhost/replica:0/task:0/cpu:0 tower_0/image_loader_vvv/random_crop/Shape: (Shape): /job:localhost/replica:0/ task:0/gpu:0  EFDPEF@KQFH
  55. DPOGJHUG$POGJH1SPUP 
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  56. BMMPX@TPGU@QMBDFNFOU  If you would like TensorFlow to automatically choose

    an existing and supported device to run the operations in case the specified one doesn't exist, you can set allow_soft_placement to True in the configuration option when creating the session. https://www.tensorflow.org/tutorials/using_gpu
  57. EFG@MPBE@JNBHF GJMF@MJTU JOQVU@TJ[F PVUQVU@TJ[F DIBOOFMT TDBMF 
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  58.  510x510 decode_jpeg random_crop

  59.  όονʹ͖ͭɺ
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  61. MS@JNBHFT<>
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 PGGTFU@UPQ PGGTFU@MFGU 
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  62.  510x510 decode_jpeg random_crop

  63. MPBE@JNBHF  [batch_size, height, width, channels] [height, width, channels]

  64. MS@JNBHF@CBUDI HSPVOE@USVUI@CBUDIUGUSBJOTIVGGMF@CBUDI 
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  65.  4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ

    4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 4UFQ -PTT 5JNFNTTUFQ 128 sample / batch learning rate 0.001
  66.  ύλʔϯ$ɿ$16ͷΦʔόʔϔου

  67. ·ͱΊ (16͸଎͍ɻίʔυ͕গ͠൥ࡶʹͳΔ͚ͲɺಘΒΕΔ଎͞͸ັྗ ͘͞ΒͷߴՐྗ͸շదɻଟগɺඇޮ཰తͳίʔυΛॻ͍ͯ΋ؾ͔ͮͳ͍͘Β͍ ($&ͷ(16Πϯελϯε΋଎͍ɻW$16ͷ਺ͱ͔ϝϞϦ༰ྔͱ͔ɺ՝୊ʹର͢ Δ࠷దεϖοΫΛಋ͘ϊ΢ϋ΢͕ཉ͍͠ .-&OHJOFʜʜʁ 

  68. Impress R&DࣾΑΓ
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    ΞΩόɾεΫΤΞ ʰٕज़ॻయ̎ ͓ʔ̍̎ʱʹͯ TensorFlow͸͡Ί·ͨ͠
 Super Resolution ʔ ௒ղ૾ ׬ച͠·ͨ͠
  69. C-LIS CO., LTD. ֤੡඼໊ɾϒϥϯυ໊ɺձ໊ࣾͳͲ͸ɺҰൠʹ֤ࣾͷ঎ඪ·ͨ͸ొ࿥঎ඪͰ͢ɻຊࢿྉதͰ͸ɺ˜ɺšɺäΛׂѪ͍ͯ͠·͢ɻ ຊࢿྉ͸ɺ༗ݶձࣾγʔϦεͷஶ࡞෺Ͱ͋ΓɺΫϦΤΠςΟϒίϞϯζͷදࣔඇӦརܧঝ6OQPSUFEϥΠηϯεͷݩͰެ։͍ͯ͠·͢ɻ