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Diffstat (limited to 'tensorflow/docs_src/performance/performance_guide.md')
| -rw-r--r-- | tensorflow/docs_src/performance/performance_guide.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/tensorflow/docs_src/performance/performance_guide.md b/tensorflow/docs_src/performance/performance_guide.md index a5508ac23e..9ac60024a1 100644 --- a/tensorflow/docs_src/performance/performance_guide.md +++ b/tensorflow/docs_src/performance/performance_guide.md @@ -104,7 +104,7 @@ with tf.device('/cpu:0'): Under some circumstances, both the CPU and GPU can be starved for data by the I/O system. If you are using many small files to form your input data set, you may be limited by the speed of your filesystem. If your training loop runs -faster when using SSDs vs HDDs for storing your input data, you could could be +faster when using SSDs vs HDDs for storing your input data, you could be I/O bottlenecked. If this is the case, you should pre-process your input data, creating a few |