Phil 9.3.19 (including install directions for Tensorflow 2.0rc1 on Windows 10)

7:00 – 4:30ASRC GOES

  • Dissertation – Working on the Orientation section, where I compare Moby Dick to Dieselgate
  • Uninstalling all previous versions of CUDA, which should hopefully allow 10 to be installed
  • Still flailing on getting TF 2.0 working. Grrrrr. Success! Added guide below
  • Spent some time discussing mapping the GPT-2 with Aaron

Installing Tensorflow 2.0rc1 to Windows 10, a temporary accurate guide

  • Uninstall any previous version of Tensorflow (e.g. “pip uninstall tensorflow”)
  • Uninstall all your NVIDIA crap
  • Install JUST THE CUDA LIBRARIES for version 9.0 and 10.0. You don’t need anything else

NVIDIA1

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  • Then install the latest Nvidia graphics drivers. When you’re done, your install should look something like this (this worked on 9.3.19):

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Edit your system variables so that the CUDA 9 and CUDA 10 directories are on your path:

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One more part is needed from NVIDIA: cudnn64_7.dll

In order to download cuDNN, ensure you are registered for the NVIDIA Developer Program.

    1. Go to: NVIDIA cuDNN home page
    2. Click “Download”.
  1. Remember to accept the Terms and Conditions.
  2. Select the cuDNN version to want to install from the list. This opens up a second list of target OS installs. Select cuDNN Library for Windows 10.
  3. Extract the cuDNN archive to a directory of your choice. The important part (cudnn64_7.dll) is in the cuda\bin directory. Either add that directory to your path, or copy the dll and put it in the Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10\bin directory

NVIDIA6

Then open up a console window (cmd) as admin, and install tensorflow:

  • pip install tensorflow-gpu==2.0.0-rc1
  • verify that it works by opening the python console and typing the following:

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if that works, you should be able to have the following work:

import tensorflow as tf
print("tf version = {}".format(tf.__version__))
mnist = tf.keras.datasets.mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

model = tf.keras.models.Sequential([
    tf.keras.layers.Flatten(input_shape=(28, 28)),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(10, activation='softmax')
])

model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

model.fit(x_train, y_train, epochs=5)

model.evaluate(x_test, y_test)

The results should looks something like:

"D:\Program Files\Python37\python.exe" D:/Development/Sandboxes/PyBullet/src/TensorFlow/HelloWorld.py
2019-09-03 15:09:56.685476: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
tf version = 2.0.0-rc0
2019-09-03 15:09:59.272748: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2019-09-03 15:09:59.372341: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: 
name: TITAN X (Pascal) major: 6 minor: 1 memoryClockRate(GHz): 1.531
pciBusID: 0000:01:00.0
2019-09-03 15:09:59.372616: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-09-03 15:09:59.373339: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-09-03 15:09:59.373671: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2019-09-03 15:09:59.376010: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: 
name: TITAN X (Pascal) major: 6 minor: 1 memoryClockRate(GHz): 1.531
pciBusID: 0000:01:00.0
2019-09-03 15:09:59.376291: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-09-03 15:09:59.376996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-09-03 15:09:59.951116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-09-03 15:09:59.951317: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 
2019-09-03 15:09:59.951433: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N 
2019-09-03 15:09:59.952189: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9607 MB memory) -> physical GPU (device: 0, name: TITAN X (Pascal), pci bus id: 0000:01:00.0, compute capability: 6.1)
Train on 60000 samples
Epoch 1/5
2019-09-03 15:10:00.818650: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_100.dll

   32/60000 [..............................] - ETA: 17:07 - loss: 2.4198 - accuracy: 0.0938
  736/60000 [..............................] - ETA: 48s - loss: 1.7535 - accuracy: 0.4891  
 1696/60000 [..............................] - ETA: 22s - loss: 1.2584 - accuracy: 0.6515
 2560/60000 [>.............................] - ETA: 16s - loss: 1.0503 - accuracy: 0.7145
 3552/60000 [>.............................] - ETA: 12s - loss: 0.9017 - accuracy: 0.7531
 4352/60000 [=>............................] - ETA: 10s - loss: 0.8156 - accuracy: 0.7744
 5344/60000 [=>............................] - ETA: 9s - loss: 0.7407 - accuracy: 0.7962 
 6176/60000 [==>...........................] - ETA: 8s - loss: 0.7069 - accuracy: 0.8039
 7040/60000 [==>...........................] - ETA: 7s - loss: 0.6669 - accuracy: 0.8134
 8032/60000 [===>..........................] - ETA: 6s - loss: 0.6285 - accuracy: 0.8236
 8832/60000 [===>..........................] - ETA: 6s - loss: 0.6037 - accuracy: 0.8291
 9792/60000 [===>..........................] - ETA: 6s - loss: 0.5823 - accuracy: 0.8356
10656/60000 [====>.........................] - ETA: 5s - loss: 0.5621 - accuracy: 0.8410
11680/60000 [====>.........................] - ETA: 5s - loss: 0.5434 - accuracy: 0.8453
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14496/60000 [======>.......................] - ETA: 4s - loss: 0.4997 - accuracy: 0.8580
15296/60000 [======>.......................] - ETA: 4s - loss: 0.4894 - accuracy: 0.8609
16224/60000 [=======>......................] - ETA: 4s - loss: 0.4792 - accuracy: 0.8634
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20800/60000 [=========>....................] - ETA: 3s - loss: 0.4356 - accuracy: 0.8756
21792/60000 [=========>....................] - ETA: 3s - loss: 0.4293 - accuracy: 0.8776
22752/60000 [==========>...................] - ETA: 3s - loss: 0.4226 - accuracy: 0.8794
23712/60000 [==========>...................] - ETA: 3s - loss: 0.4179 - accuracy: 0.8808
24800/60000 [===========>..................] - ETA: 2s - loss: 0.4111 - accuracy: 0.8827
26080/60000 [============>.................] - ETA: 2s - loss: 0.4029 - accuracy: 0.8849
27264/60000 [============>.................] - ETA: 2s - loss: 0.3981 - accuracy: 0.8864
28160/60000 [=============>................] - ETA: 2s - loss: 0.3921 - accuracy: 0.8882
29408/60000 [=============>................] - ETA: 2s - loss: 0.3852 - accuracy: 0.8902
30432/60000 [==============>...............] - ETA: 2s - loss: 0.3809 - accuracy: 0.8916
31456/60000 [==============>...............] - ETA: 2s - loss: 0.3751 - accuracy: 0.8932
32704/60000 [===============>..............] - ETA: 2s - loss: 0.3707 - accuracy: 0.8946
33760/60000 [===============>..............] - ETA: 1s - loss: 0.3652 - accuracy: 0.8959
34976/60000 [================>.............] - ETA: 1s - loss: 0.3594 - accuracy: 0.8975
35968/60000 [================>.............] - ETA: 1s - loss: 0.3555 - accuracy: 0.8984
37152/60000 [=================>............] - ETA: 1s - loss: 0.3509 - accuracy: 0.8998
38240/60000 [==================>...........] - ETA: 1s - loss: 0.3477 - accuracy: 0.9006
39232/60000 [==================>...........] - ETA: 1s - loss: 0.3442 - accuracy: 0.9015
40448/60000 [===================>..........] - ETA: 1s - loss: 0.3393 - accuracy: 0.9030
41536/60000 [===================>..........] - ETA: 1s - loss: 0.3348 - accuracy: 0.9042
42752/60000 [====================>.........] - ETA: 1s - loss: 0.3317 - accuracy: 0.9049
43840/60000 [====================>.........] - ETA: 1s - loss: 0.3288 - accuracy: 0.9059
44992/60000 [=====================>........] - ETA: 1s - loss: 0.3255 - accuracy: 0.9069
46016/60000 [======================>.......] - ETA: 0s - loss: 0.3230 - accuracy: 0.9077
47104/60000 [======================>.......] - ETA: 0s - loss: 0.3203 - accuracy: 0.9085
48288/60000 [=======================>......] - ETA: 0s - loss: 0.3174 - accuracy: 0.9091
49248/60000 [=======================>......] - ETA: 0s - loss: 0.3155 - accuracy: 0.9098
50208/60000 [========================>.....] - ETA: 0s - loss: 0.3131 - accuracy: 0.9105
51104/60000 [========================>.....] - ETA: 0s - loss: 0.3111 - accuracy: 0.9111
52288/60000 [=========================>....] - ETA: 0s - loss: 0.3085 - accuracy: 0.9117
53216/60000 [=========================>....] - ETA: 0s - loss: 0.3066 - accuracy: 0.9121
54176/60000 [==========================>...] - ETA: 0s - loss: 0.3043 - accuracy: 0.9128
55328/60000 [==========================>...] - ETA: 0s - loss: 0.3018 - accuracy: 0.9135
56320/60000 [===========================>..] - ETA: 0s - loss: 0.2995 - accuracy: 0.9141
57440/60000 [===========================>..] - ETA: 0s - loss: 0.2980 - accuracy: 0.9143
58400/60000 [============================>.] - ETA: 0s - loss: 0.2961 - accuracy: 0.9148
59552/60000 [============================>.] - ETA: 0s - loss: 0.2941 - accuracy: 0.9154
60000/60000 [==============================] - 4s 65us/sample - loss: 0.2930 - accuracy: 0.9158
... epochs pass ...
10000/1 [==========] - 1s 61us/sample - loss: 0.0394 - accuracy: 0.9778

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