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3 years ago the rule of thumb was: About 15 times faster Your CPU does 113 GFlops on float operations (source) and your GPU does 3 Tflops (source). My bet: somewhere between 15 and 30 times faster


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I invite you to look at the Horovod project on github. It's the most efficient way to currently execute distributed training with tensorflow. They have tutorials and benchmarks resource available


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Solution: Finally I found the solution myself. I just used another docker image with an older version of tensorflow (2.0.0), and the error disappeared.


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