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with tf.device('/cpu:0'):
one_hot_y = tf.one_hot(y, 10)
As it can be a frustrating error, and jupyter gives no useful feedback, suggest offering this fix in the readme comments, or even updating the code until CUDA/tensorflow fix it properly.
Anthony
The text was updated successfully, but these errors were encountered:
Hello,
The code provided in the solution file will not run on a windows GPU enabled machine. Jupyter notebook crashes and gives non-useful error message. Running in normal python build yields the error: CUDA_ERROR_ILLEGAL_ADDRESS. This can be solved as suggested here: https://carnd-forums.udacity.com/questions/32717096/tensorflow-gpu-error-cudaerrorillegaladdress
For this instance, in[7] this works:
As it can be a frustrating error, and jupyter gives no useful feedback, suggest offering this fix in the readme comments, or even updating the code until CUDA/tensorflow fix it properly.
Anthony
The text was updated successfully, but these errors were encountered: