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# # Set up Cuda-related environment settings
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while [ " $TF_NEED_CUDA " == " " ]; do
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- read -p " Do you wish to bulid TensorFlow with GPU support? [y/n] " INPUT
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+ read -p " Do you wish to build TensorFlow with GPU support? [y/n] " INPUT
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case $INPUT in
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[Yy]* ) echo -e " GPU support will be enabled for TensorFlow\n" ; TF_NEED_CUDA=1;;
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[Nn]* ) echo -e " No GPU support will be enabled for TensorFlow\n" ; TF_NEED_CUDA=0;;
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Additional details about the TensorFlow programming model and the underlying
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implementation can be found in out white paper:
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- * [ TensorFlow: Large-scale machine learning on heterogeneous systems] ( http://www .tensorflow.org/whitepaper2015.pdf )
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+ * [ TensorFlow: Large-scale machine learning on heterogeneous systems] ( http://download .tensorflow.org/paper /whitepaper2015.pdf )
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### Citation <a class =" md-anchor " id =" AUTOGENERATED-citation " ></a >
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Original file line number Diff line number Diff line change @@ -179,14 +179,13 @@ bazel build -c opt tensorflow/models/rnn/ptb:ptb_word_lm
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And if you have a fast GPU, run the following:
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```
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- bazel build -c opt tensorflow --config=cuda \
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- tensorflow/models/rnn/ptb:ptb_word_lm
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+ bazel build -c opt --config=cuda tensorflow/models/rnn/ptb:ptb_word_lm
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```
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Now we can run the model:
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```
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- bazel-bin/... /ptb_word_lm \
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+ bazel-bin/tensorflow/models/rnn/ptb /ptb_word_lm \
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--data_path=/tmp/simple-examples/data/ --alsologtostderr --model small
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```
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