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Performance and functional parity of C and Python API for the graph mode #46763

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deadeyegoodwin opened this issue Jan 28, 2021 · 3 comments
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Performance and functional parity of C and Python API for the graph mode #46763

deadeyegoodwin opened this issue Jan 28, 2021 · 3 comments
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@rohan100jain
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comp:apis Highlevel API related issues stale This label marks the issue/pr stale - to be closed automatically if no activity stat:awaiting response Status - Awaiting response from author stat:awaiting tensorflower Status - Awaiting response from tensorflower type:feature Feature requests

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@deadeyegoodwin
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System information

  • TF 2.3
  • Are you willing to contribute it (Yes/No): No

Describe the feature and the current behavior/state.
Currently the TF C/C++ API is incomplete (e.g. does not have API to save savedmodel, does not expose all optimization and configuration options) compared to the Python API. It also seems that the Python API enables or performs additional optimization passes that are not available when using the C/C++ API.

Will this change the current api? How?
Yes. The C/C++ API will likely need to be enhanced significantly. Ideally this complete functionality will be implemented in a C API to ensure maximum ABI compatibility and portability.

Who will benefit with this feature?
Applications that want a more portable, high-performance solution that does not require using python. We are particularly interested in applications like model servers. A C API would be the most portable and performant and is relatively easy to integrate and wrap into other languages. Conceptually the python API (and any other language binding) should be a wrapper over the C API that presents the API in a language appropriate way but that does otherwise add (or remove) functionality.
@deadeyegoodwin deadeyegoodwin added the type:feature Feature requests label Jan 28, 2021
@Saduf2019 Saduf2019 added the comp:apis Highlevel API related issues label Jan 29, 2021
@Saduf2019 Saduf2019 assigned ymodak and unassigned Saduf2019 Jan 29, 2021
@ymodak ymodak assigned saxenasaurabh and unassigned ymodak Feb 1, 2021
@ymodak ymodak added the stat:awaiting tensorflower Status - Awaiting response from tensorflower label Feb 1, 2021
@tilakrayal
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Hi,

Thank you for opening this issue. Since this issue has been open for a long time, the code/debug information for this issue may not be relevant with the current state of the code base.

The Tensorflow team is constantly improving the framework by fixing bugs and adding new features. We suggest you try the latest TensorFlow version with the latest compatible hardware configuration which could potentially resolve the issue. If you are still facing the issue, please create a new GitHub issue with your latest findings, with all the debugging information which could help us investigate.

Please follow the release notes to stay up to date with the latest developments which are happening in the Tensorflow space.

@tilakrayal tilakrayal added the stat:awaiting response Status - Awaiting response from author label Sep 11, 2024
@github-actions GitHub Actions
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This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.

@github-actions github-actions bot added the stale This label marks the issue/pr stale - to be closed automatically if no activity label Sep 19, 2024
@github-actions GitHub Actions
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This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further.

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@rohan100jain rohan100jain

Labels
comp:apis Highlevel API related issues stale This label marks the issue/pr stale - to be closed automatically if no activity stat:awaiting response Status - Awaiting response from author stat:awaiting tensorflower Status - Awaiting response from tensorflower type:feature Feature requests
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@rohan100jain @saxenasaurabh @deadeyegoodwin @ymodak @Saduf2019 @tilakrayal