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  1. awwong1 revised this gist Apr 12, 2018. 1 changed file with 1 addition and 0 deletions.
    1 change: 1 addition & 0 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -54,6 +54,7 @@ export DYLD_LIBRARY_PATH="$CUDA_HOME/lib:$CUDA_HOME:$CUDA_HOME/extras/CUPTI/lib"
    export LD_LIBRARY_PATH=$DYLD_LIBRARY_PATH
    ```
    (If your bash_profile does not exist, create it. This is executed everytime you open a terminal window)

    4. Downloading and installing cuDNN (cudnn-8.0-osx-x64-v5.1) Need to register before downloading it
    5. Copy cuDNN files to CUDA
    ```
  2. awwong1 revised this gist Apr 12, 2018. 1 changed file with 26 additions and 22 deletions.
    48 changes: 26 additions & 22 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -1,4 +1,6 @@
    **This configuration worked for me, hope it helps**
    **MacBook Pro 13-inch, Early 2015**

    Configuration worked as of April 11, 2018.

    It is based on:
    https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b
    @@ -16,23 +18,25 @@ https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support

    # Software versions
    - macOS Sierra Version 10.12.6
    - GPU Driver Version: 10.18.5 (378.05.05.25f01)
    - CUDA Driver Version: 8.0.61
    - cuDNN v5.1 (Jan 20, 2017), for CUDA 8.0: Need to register and download
    - Nvidia Web Driver Version: [378.05.05.25f07](http://www.nvidia.com/download/driverResults.aspx/133513/en-us)
    - CUDA Driver Version: [8.0.90](http://www.nvidia.com/object/macosx-cuda-8.0.90-driver.html)
    - cuDNN v6.0 (April 27, 2017), for CUDA 8.0: [downloads](https://developer.nvidia.com/rdp/cudnn-download#a-collapse6-8) (requires registration)
    - CUDA Toolkit 8.0 GA2: [download](https://developer.nvidia.com/cuda-80-ga2-download-archive)
    - tensorflow-gpu 1.0.0
    - Keras 2.0.8

    # Procedure:
    ## Install GPU driver

    1. ShutDown your system, power it up again with pressing (⌘ and R) keys until you see , this will let you in Recovery Mode.
    2. From the Menu Bar click Utilities > Terminal and write ‘csrutil disable; reboot’ press enter to execute this command.
    2. From the Menu Bar click Utilities > Terminal and write `csrutil disable; reboot` press enter to execute this command.
    3. When your mac restarted, run this command in Terminal:
    ~~~~
    ```
    cd ~/Desktop; git clone https://github.com/goalque/automate-eGPU.git; chmod +x ~/Desktop/automate-eGPU/automate-eGPU.sh; sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh
    ~~~~
    4. Unplug your eGPU from your Mac, and restart. This is important if you did not unplug your eGPU you may end up with black screen after restarting.
    5. When your Mac restarted, Open up Terminal and execute this command:
    sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh -a
    ```
    4. Turn off your Macbook. Unplug your eGPU. (This is important if you did not unplug your eGPU you may end up with black screen after power on.) Power on your Macbook.
    5. After your Mac powers on, Open up Terminal and execute this command:
    `sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh -a`
    6. Plug your eGPU to your mac via TH2.
    7. Restart your Mac.
    8. Got to About this Mac / Sytem Report / Graphics/Displays and you should see the Nvidia Card with the correct model.
    @@ -43,30 +47,30 @@ At this moment, Keras 2.08 needs tensorflow 1.0.0. Tensorflow-gpu 1.0.0 needs CU
    1. [Download and installing CUDA 8.0](https://developer.nvidia.com/cuda-toolkit-archive) CUDA Toolkit 8.0 GA2 (Feb 2017)
    2. Install it and follow the instructions
    3. Set env variables
    ~~~~
    ```
    vim ~/.bash_profile
    export CUDA_HOME=/usr/local/cuda
    export DYLD_LIBRARY_PATH="$CUDA_HOME/lib:$CUDA_HOME:$CUDA_HOME/extras/CUPTI/lib"
    export LD_LIBRARY_PATH=$DYLD_LIBRARY_PATH
    ~~~~
    ```
    (If your bash_profile does not exist, create it. This is executed everytime you open a terminal window)
    4. Downloading and installing cuDNN (cudnn-8.0-osx-x64-v5.1) Need to register before downloading it
    5. Copy cuDNN files to CUDA
    ~~~~
    ```
    cd ~/Downloads/cuda
    sudo cp include/* /usr/local/cuda/include/
    sudo cp lib/* /usr/local/cuda/lib/
    ~~~~
    ```
    6. Create envirenment and install tensorflow
    ~~~~
    ```
    conda create -n egpu python=3
    source activate egpu
    pip install tensorflow-gpu==1.0.0
    ~~~~
    ```
    7. Verify it works

    Run the following script:
    ~~~~
    ```
    import tensorflow as tf
    with tf.device('/gpu:0'):
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
    @@ -75,9 +79,9 @@ with tf.device('/gpu:0'):
    with tf.Session() as sess:
    print (sess.run(c))
    ~~~~
    ```
    8. Install Keras in the envirenment and set tensorflow as backend:
    ~~~~
    ```
    pip install --upgrade --no-deps keras # Need no-deps flag to prevent from installing tensorflow dependency
    KERAS_BACKEND=tensorflow python -c "from keras import backend"
    Output:
    @@ -88,10 +92,10 @@ I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library
    I tensorflow/stream_executor/dso_loader.cc:126] Couldn't open CUDA library libcuda.1.dylib. LD_LIBRARY_PATH: /usr/local/cuda/lib:/usr/local/cuda:/usr/local/cuda/extras/CUPTI/lib
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.8.0.dylib locally
    ~~~~
    ```

    9. Log after importing keras in Jupyter Notebook:
    ~~~~
    ```
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.8.0.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.5.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.8.0.dylib locally
    @@ -113,4 +117,4 @@ Free memory: 11.79GiB
    I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0
    I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y
    I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: TITAN Xp, pci bus id: 0000:c3:00.0)
    ~~~~
    ```
  3. @jganzabal jganzabal revised this gist Oct 7, 2017. 1 changed file with 1 addition and 1 deletion.
    2 changes: 1 addition & 1 deletion Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -90,7 +90,7 @@ I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.8.0.dylib locally
    ~~~~

    9. Log after imported keras in tensorflow:
    9. Log after importing keras in Jupyter Notebook:
    ~~~~
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.8.0.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.5.dylib locally
  4. @jganzabal jganzabal revised this gist Oct 7, 2017. 1 changed file with 24 additions and 0 deletions.
    24 changes: 24 additions & 0 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -90,3 +90,27 @@ I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.8.0.dylib locally
    ~~~~

    9. Log after imported keras in tensorflow:
    ~~~~
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.8.0.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.5.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.8.0.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:126] Couldn't open CUDA library libcuda.1.dylib. LD_LIBRARY_PATH: /usr/local/cuda/lib:/usr/local/cuda:/usr/local/cuda/extras/CUPTI/lib
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.8.0.dylib locally
    W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
    W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
    W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
    W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
    W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
    I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:874] OS X does not support NUMA - returning NUMA node zero
    I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties:
    name: TITAN Xp
    major: 6 minor: 1 memoryClockRate (GHz) 1.582
    pciBusID 0000:c3:00.0
    Total memory: 12.00GiB
    Free memory: 11.79GiB
    I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0
    I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y
    I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: TITAN Xp, pci bus id: 0000:c3:00.0)
    ~~~~
  5. @jganzabal jganzabal revised this gist Oct 4, 2017. 1 changed file with 1 addition and 0 deletions.
    1 change: 1 addition & 0 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -35,6 +35,7 @@ cd ~/Desktop; git clone https://github.com/goalque/automate-eGPU.git; chmod +x ~
    sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh -a
    6. Plug your eGPU to your mac via TH2.
    7. Restart your Mac.
    8. Got to About this Mac / Sytem Report / Graphics/Displays and you should see the Nvidia Card with the correct model.

    ## Install CUDA, cuDNN, Tensorflow and Keras
    At this moment, Keras 2.08 needs tensorflow 1.0.0. Tensorflow-gpu 1.0.0 needs CUDA 8.0 and cuDNN v5.1 is the one that worked for me. I tried other combinations but doesn't seem to work
  6. @jganzabal jganzabal revised this gist Oct 3, 2017. 1 changed file with 1 addition and 1 deletion.
    2 changes: 1 addition & 1 deletion Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -12,7 +12,7 @@ https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support
    - EGPU: [Akitio Node](https://www.akitio.com/expansion/node)
    - MacBook Pro (Retina, 13-inch, Early 2015)
    - [Apple Thunderbolt3 to Thunderbolt2 Adapter](https://www.apple.com/shop/product/MMEL2AM/A/thunderbolt-3-usb-c-to-thunderbolt-2-adapter)
    - [https://www.apple.com/shop/product/MD861LL/A/apple-thunderbolt-cable-20-m](Apple Thunderbolt2 Cable)
    - [Apple Thunderbolt2 Cable](https://www.apple.com/shop/product/MD861LL/A/apple-thunderbolt-cable-20-m)

    # Software versions
    - macOS Sierra Version 10.12.6
  7. @jganzabal jganzabal revised this gist Oct 3, 2017. 1 changed file with 11 additions and 4 deletions.
    15 changes: 11 additions & 4 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -4,7 +4,6 @@ It is based on:
    https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

    and on:

    https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support


    @@ -20,8 +19,8 @@ https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support
    - GPU Driver Version: 10.18.5 (378.05.05.25f01)
    - CUDA Driver Version: 8.0.61
    - cuDNN v5.1 (Jan 20, 2017), for CUDA 8.0: Need to register and download
    - tensorflow-gpu 1.0.0: pip install tensorflow-gpu==1.0.0 # Install tensorflow-gpu manually
    - Keras 2.0.8: pip install --upgrade --no-deps keras # Need no-deps flag to prevent from installing tensorflow dependency
    - tensorflow-gpu 1.0.0
    - Keras 2.0.8

    # Procedure:
    ## Install GPU driver
    @@ -78,7 +77,15 @@ with tf.Session() as sess:
    ~~~~
    8. Install Keras in the envirenment and set tensorflow as backend:
    ~~~~
    pip install --upgrade --no-deps keras
    pip install --upgrade --no-deps keras # Need no-deps flag to prevent from installing tensorflow dependency
    KERAS_BACKEND=tensorflow python -c "from keras import backend"
    Output:
    Using TensorFlow backend.
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.8.0.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.5.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.8.0.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:126] Couldn't open CUDA library libcuda.1.dylib. LD_LIBRARY_PATH: /usr/local/cuda/lib:/usr/local/cuda:/usr/local/cuda/extras/CUPTI/lib
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.dylib locally
    I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.8.0.dylib locally
    ~~~~

  8. @jganzabal jganzabal revised this gist Oct 3, 2017. 1 changed file with 13 additions and 1 deletion.
    14 changes: 13 additions & 1 deletion Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -28,7 +28,9 @@ https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support
    1. ShutDown your system, power it up again with pressing (⌘ and R) keys until you see , this will let you in Recovery Mode.
    2. From the Menu Bar click Utilities > Terminal and write ‘csrutil disable; reboot’ press enter to execute this command.
    3. When your mac restarted, run this command in Terminal:
    ~~~~
    cd ~/Desktop; git clone https://github.com/goalque/automate-eGPU.git; chmod +x ~/Desktop/automate-eGPU/automate-eGPU.sh; sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh
    ~~~~
    4. Unplug your eGPU from your Mac, and restart. This is important if you did not unplug your eGPU you may end up with black screen after restarting.
    5. When your Mac restarted, Open up Terminal and execute this command:
    sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh -a
    @@ -41,20 +43,26 @@ At this moment, Keras 2.08 needs tensorflow 1.0.0. Tensorflow-gpu 1.0.0 needs CU
    1. [Download and installing CUDA 8.0](https://developer.nvidia.com/cuda-toolkit-archive) CUDA Toolkit 8.0 GA2 (Feb 2017)
    2. Install it and follow the instructions
    3. Set env variables
    ~~~~
    vim ~/.bash_profile
    export CUDA_HOME=/usr/local/cuda
    export DYLD_LIBRARY_PATH="$CUDA_HOME/lib:$CUDA_HOME:$CUDA_HOME/extras/CUPTI/lib"
    export LD_LIBRARY_PATH=$DYLD_LIBRARY_PATH
    ~~~~
    (If your bash_profile does not exist, create it. This is executed everytime you open a terminal window)
    4. Downloading and installing cuDNN (cudnn-8.0-osx-x64-v5.1) Need to register before downloading it
    5. Copy cuDNN files to CUDA
    ~~~~
    cd ~/Downloads/cuda
    sudo cp include/* /usr/local/cuda/include/
    sudo cp lib/* /usr/local/cuda/lib/
    ~~~~
    6. Create envirenment and install tensorflow
    ~~~~
    conda create -n egpu python=3
    source activate egpu
    pip install tensorflow-gpu==1.0.0
    ~~~~
    7. Verify it works

    Run the following script:
    @@ -68,5 +76,9 @@ with tf.device('/gpu:0'):
    with tf.Session() as sess:
    print (sess.run(c))
    ~~~~

    8. Install Keras in the envirenment and set tensorflow as backend:
    ~~~~
    pip install --upgrade --no-deps keras
    KERAS_BACKEND=tensorflow python -c "from keras import backend"
    ~~~~

  9. @jganzabal jganzabal revised this gist Oct 3, 2017. 1 changed file with 42 additions and 1 deletion.
    43 changes: 42 additions & 1 deletion Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -1,7 +1,13 @@
    **This configuration worked for me, hope it helps**
    based on:

    It is based on:
    https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

    and on:

    https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support


    # Hardware
    - Nvidia Video Card: [Titan Xp](https://www.nvidia.com/en-us/geforce/products/10series/titan-xp/)
    - EGPU: [Akitio Node](https://www.akitio.com/expansion/node)
    @@ -29,3 +35,38 @@ sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh -a
    6. Plug your eGPU to your mac via TH2.
    7. Restart your Mac.

    ## Install CUDA, cuDNN, Tensorflow and Keras
    At this moment, Keras 2.08 needs tensorflow 1.0.0. Tensorflow-gpu 1.0.0 needs CUDA 8.0 and cuDNN v5.1 is the one that worked for me. I tried other combinations but doesn't seem to work

    1. [Download and installing CUDA 8.0](https://developer.nvidia.com/cuda-toolkit-archive) CUDA Toolkit 8.0 GA2 (Feb 2017)
    2. Install it and follow the instructions
    3. Set env variables
    vim ~/.bash_profile
    export CUDA_HOME=/usr/local/cuda
    export DYLD_LIBRARY_PATH="$CUDA_HOME/lib:$CUDA_HOME:$CUDA_HOME/extras/CUPTI/lib"
    export LD_LIBRARY_PATH=$DYLD_LIBRARY_PATH
    (If your bash_profile does not exist, create it. This is executed everytime you open a terminal window)
    4. Downloading and installing cuDNN (cudnn-8.0-osx-x64-v5.1) Need to register before downloading it
    5. Copy cuDNN files to CUDA
    cd ~/Downloads/cuda
    sudo cp include/* /usr/local/cuda/include/
    sudo cp lib/* /usr/local/cuda/lib/
    6. Create envirenment and install tensorflow
    conda create -n egpu python=3
    source activate egpu
    pip install tensorflow-gpu==1.0.0
    7. Verify it works

    Run the following script:
    ~~~~
    import tensorflow as tf
    with tf.device('/gpu:0'):
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
    b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
    c = tf.matmul(a, b)
    with tf.Session() as sess:
    print (sess.run(c))
    ~~~~


  10. @jganzabal jganzabal revised this gist Oct 3, 2017. 1 changed file with 7 additions and 7 deletions.
    14 changes: 7 additions & 7 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -19,13 +19,13 @@ https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-mac

    # Procedure:
    ## Install GPU driver
    1- ShutDown your system, power it up again with pressing (⌘ and R) keys until you see , this will let you in Recovery Mode.
    2- From the Menu Bar click Utilities > Terminal and write ‘csrutil disable; reboot’ press enter to execute this command.
    3- When your mac restarted, run this command in Terminal:
    1. ShutDown your system, power it up again with pressing (⌘ and R) keys until you see , this will let you in Recovery Mode.
    2. From the Menu Bar click Utilities > Terminal and write ‘csrutil disable; reboot’ press enter to execute this command.
    3. When your mac restarted, run this command in Terminal:
    cd ~/Desktop; git clone https://github.com/goalque/automate-eGPU.git; chmod +x ~/Desktop/automate-eGPU/automate-eGPU.sh; sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh
    4- Unplug your eGPU from your Mac, and restart. This is important if you did not unplug your eGPU you may end up with black screen after restarting.
    5- When your Mac restarted, Open up Terminal and execute this command:
    4. Unplug your eGPU from your Mac, and restart. This is important if you did not unplug your eGPU you may end up with black screen after restarting.
    5. When your Mac restarted, Open up Terminal and execute this command:
    sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh -a
    5- Plug your eGPU to your mac via TH2.
    6- Restart your Mac.
    6. Plug your eGPU to your mac via TH2.
    7. Restart your Mac.

  11. @jganzabal jganzabal revised this gist Oct 3, 2017. 1 changed file with 19 additions and 2 deletions.
    21 changes: 19 additions & 2 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
    View file
    Original file line number Diff line number Diff line change
    @@ -1,3 +1,7 @@
    **This configuration worked for me, hope it helps**
    based on:
    https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

    # Hardware
    - Nvidia Video Card: [Titan Xp](https://www.nvidia.com/en-us/geforce/products/10series/titan-xp/)
    - EGPU: [Akitio Node](https://www.akitio.com/expansion/node)
    @@ -10,5 +14,18 @@
    - GPU Driver Version: 10.18.5 (378.05.05.25f01)
    - CUDA Driver Version: 8.0.61
    - cuDNN v5.1 (Jan 20, 2017), for CUDA 8.0: Need to register and download
    - tensorflow-gpu 1.0.0: pip install tensorflow-gpu==1.0.0
    - Keras
    - tensorflow-gpu 1.0.0: pip install tensorflow-gpu==1.0.0 # Install tensorflow-gpu manually
    - Keras 2.0.8: pip install --upgrade --no-deps keras # Need no-deps flag to prevent from installing tensorflow dependency

    # Procedure:
    ## Install GPU driver
    1- ShutDown your system, power it up again with pressing (⌘ and R) keys until you see , this will let you in Recovery Mode.
    2- From the Menu Bar click Utilities > Terminal and write ‘csrutil disable; reboot’ press enter to execute this command.
    3- When your mac restarted, run this command in Terminal:
    cd ~/Desktop; git clone https://github.com/goalque/automate-eGPU.git; chmod +x ~/Desktop/automate-eGPU/automate-eGPU.sh; sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh
    4- Unplug your eGPU from your Mac, and restart. This is important if you did not unplug your eGPU you may end up with black screen after restarting.
    5- When your Mac restarted, Open up Terminal and execute this command:
    sudo ~/Desktop/automate-eGPU/./automate-eGPU.sh -a
    5- Plug your eGPU to your mac via TH2.
    6- Restart your Mac.

  12. @jganzabal jganzabal revised this gist Oct 3, 2017. 1 changed file with 13 additions and 3 deletions.
    16 changes: 13 additions & 3 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
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    # Hardware
    - Nvidia Video Card: Titan XP https://www.nvidia.com/en-us/geforce/products/10series/titan-xp/
    - EGPU: Akitio Node
    - MacBook Pro 13-inch (Early 2015)
    - Nvidia Video Card: [Titan Xp](https://www.nvidia.com/en-us/geforce/products/10series/titan-xp/)
    - EGPU: [Akitio Node](https://www.akitio.com/expansion/node)
    - MacBook Pro (Retina, 13-inch, Early 2015)
    - [Apple Thunderbolt3 to Thunderbolt2 Adapter](https://www.apple.com/shop/product/MMEL2AM/A/thunderbolt-3-usb-c-to-thunderbolt-2-adapter)
    - [https://www.apple.com/shop/product/MD861LL/A/apple-thunderbolt-cable-20-m](Apple Thunderbolt2 Cable)

    # Software versions
    - macOS Sierra Version 10.12.6
    - GPU Driver Version: 10.18.5 (378.05.05.25f01)
    - CUDA Driver Version: 8.0.61
    - cuDNN v5.1 (Jan 20, 2017), for CUDA 8.0: Need to register and download
    - tensorflow-gpu 1.0.0: pip install tensorflow-gpu==1.0.0
    - Keras
  13. @jganzabal jganzabal created this gist Oct 3, 2017.
    4 changes: 4 additions & 0 deletions Nvidia Titan XP + MacBook Pro + Akitio Node + Tensorflow + Keras.md
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    # Hardware
    - Nvidia Video Card: Titan XP https://www.nvidia.com/en-us/geforce/products/10series/titan-xp/
    - EGPU: Akitio Node
    - MacBook Pro 13-inch (Early 2015)