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Diffstat (limited to 'tensorflow/docs_src/guide/debugger.md')
| -rw-r--r-- | tensorflow/docs_src/guide/debugger.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/docs_src/guide/debugger.md b/tensorflow/docs_src/guide/debugger.md index 0b4a063c10..4c4a04a88a 100644 --- a/tensorflow/docs_src/guide/debugger.md +++ b/tensorflow/docs_src/guide/debugger.md @@ -627,7 +627,7 @@ hooks = [tf_debug.DumpingDebugHook("/shared/storage/location/tfdbg_dumps_1")] Then this `hook` can be used in the same way as the `LocalCLIDebugHook` examples described earlier in this document. -As the training, evalution or prediction happens with `Estimator`, +As the training, evaluation or prediction happens with `Estimator`, tfdbg creates directories having the following name pattern: `/shared/storage/location/tfdbg_dumps_1/run_<epoch_timestamp_microsec>_<uuid>`. Each directory corresponds to a `Session.run()` call that underlies @@ -768,7 +768,7 @@ sess.run(b) **A**: The reason why you see no data dumped is because every node in the executed TensorFlow graph is constant-folded by the TensorFlow runtime. - In this exapmle, `a` is a constant tensor; therefore, the fetched + In this example, `a` is a constant tensor; therefore, the fetched tensor `b` is effectively also a constant tensor. TensorFlow's graph optimization folds the graph that contains `a` and `b` into a single node to speed up future runs of the graph, which is why `tfdbg` does |