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Summary: Closes pytorch#9199 The input shapes are not logged correctly in production because `PerfNetObserver::Stop()` only gets called after the inference is done for the net and in the mobile models, it's common practice to reuse the blobs as much as possible to save memory. And the shapes of the blobs keep changing during inference. By the time you you query `InputTensorShapes()` in `PerfNetObserver::Stop()`, you only get the final shape of the blobs. To fix this bug, I moved the 'InputTensorShapes()' query from `PerfNetObserver::Stop()` to `PerfOperatorObserver::Stop()`. The latter gets called at the end of operator->run() whereas `PerfNetObserver::Stop()` gets called at the end of net->run(). Also remove `PerfOperatorObserver::getAnalyticalCost()` since it's now done on the server side and no longer needed on mobile Differential Revision: D8743346 fbshipit-source-id: cf28493bbb3d1b48903353dc3a1d86f96f4a699d
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Summary: Closes pytorch#9199 The input shapes are not logged correctly in production because `PerfNetObserver::Stop()` only gets called after the inference is done for the net and in the mobile models, it's common practice to reuse the blobs as much as possible to save memory. And the shapes of the blobs keep changing during inference. By the time you you query `InputTensorShapes()` in `PerfNetObserver::Stop()`, you only get the final shape of the blobs. To fix this bug, I moved the 'InputTensorShapes()' query from `PerfNetObserver::Stop()` to `PerfOperatorObserver::Stop()`. The latter gets called at the end of operator->run() whereas `PerfNetObserver::Stop()` gets called at the end of net->run(). Also remove `PerfOperatorObserver::getAnalyticalCost()` since it's now done on the server side and no longer needed on mobile Reviewed By: Maratyszcza Differential Revision: D8743346 fbshipit-source-id: 5d2d0132e3f5e084be7d0173863e695e62a6b4a0
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Summary:
The input shapes are not logged correctly in production because
PerfNetObserver::Stop()only gets called after the inference is done for the net and in the mobile models, it's common practice to reuse the blobs as much as possible to save memory. And the shapes of the blobs keep changing during inference. By the time you you queryInputTensorShapes()inPerfNetObserver::Stop(), you only get the final shape of the blobs.To fix this bug, I moved the 'InputTensorShapes()' query from
PerfNetObserver::Stop()toPerfOperatorObserver::Stop(). The latter gets called at the end of operator->run() whereasPerfNetObserver::Stop()gets called at the end of net->run().Also remove
PerfOperatorObserver::getAnalyticalCost()since it's now done on the server side and no longer needed on mobileDifferential Revision: D8743346