experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Update TFLite converter issue template

Browse Source 
PiperOrigin-RevId: 353929808
Change-Id: Id68c6eb9f215d72b4fe57b899e061c5d76dcd5a5
This commit is contained in:
Meghna Natraj 2021-01-26 12:54:46 -08:00 committed by TensorFlower Gardener
parent 8f595c9558
commit 75c3c9e16e
1 changed files with 24 additions and 23 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

47
.github/ISSUE_TEMPLATE/60-tflite-converter-issue.md vendored
View File

@ -1,46 +1,47 @@
--- ---
name: TensorFlow Lite New Converter Issue name: TensorFlow Lite Converter Issue
about: Use this template for reporting issues during model conversion to TFLite about: Use this template for reporting issues during model conversion to TFLite
labels: 'TFLiteConverter' labels: 'TFLiteConverter'
--- ---
### 1. System information
**System information**
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): - OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installed from (source or binary): - TensorFlow installation (pip package or built from source):
- TensorFlow version (or github SHA if from source): - TensorFlow library (version, if pip package or github SHA, if built from source):
### 2. Code
**Command used to run the converter or code if you’re using the Python API** Provide code to help us reproduce your issues using one of the following options:
If possible, please share a link to Colab/Jupyter/any notebook.
#### Option A: Reference colab notebooks
1) Reference [TensorFlow Model Colab](https://colab.research.google.com/gist/ymodak/e96a4270b953201d5362c61c1e8b78aa/tensorflow-datasets.ipynb?authuser=1): Demonstrate how to build your TF model.
2) Reference [TensorFlow Lite Model Colab](https://colab.research.google.com/gist/ymodak/0dfeb28255e189c5c48d9093f296e9a8/tensorflow-lite-debugger-colab.ipynb): Demonstrate how to convert your TF model to a TF Lite model (with quantization, if used) and run TFLite Inference (if possible).
``` ```
# Copy and paste here the exact command (You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
``` ```
**The output from the converter invocation** #### Option B: Paste your code here or provide a link to a custom end-to-end colab
``` ```
# Copy and paste the output here. (You can paste links or attach files by dragging & dropping them below)
- Include code to invoke the TFLite Converter Python API and the errors.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
``` ```
**Also, please include a link to the saved model or GraphDef** ### 3. Failure after conversion
If the conversion is successful, but the generated model is wrong, then state what is wrong:
``` - Model produces wrong results and/or has lesser accuracy.
# Put link here or attach to the issue. - Model produces correct results, but it is slower than expected.
```
**Failure details** ### 4. (optional) RNN conversion support
If the conversion is successful, but the generated model is wrong,
state what is wrong:
- Producing wrong results and/or decrease in accuracy
- Producing correct results, but the model is slower than expected (model generated from old converter)
**RNN conversion support**
If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title. If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title.
**Any other info / logs** ### 5. (optional) Any other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.