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Eager: CPU Performance/Operation Overheads #14130

asimshankar opened this Issue Oct 31, 2017 · 2 comments


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asimshankar commented Oct 31, 2017

(This applies only when eager execution has been enabled via tfe.enable_eager_execution())

Eager execution re-uses most of the same Python code used for constructing TensorFlow graphs. Many of these paths have not been optimized for part of the critical path of computation. As a result, the CPU overheads of executing Python code for every operation are higher than we’d like.

Consequently, the performance of eager execution on models with many small computations, or models executed on CPU may be dominated by these overheads.

Overheads are measured using microbenchmarks such as in and model-level benchmarks such as those used for ResNet50 and the PTB RNN


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tensorflowbutler commented Oct 23, 2018

Nagging Assignee @akshaym: It has been 195 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.


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asimshankar commented Oct 23, 2018

Closing this out as many many improvements have been made and others are coming too.
Not sure about the value of this issue since it isn't very specific (yes, I know I filed this :))

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