sushreebarsa

@yousifj129 I tried to replicate the issue reported [here](https://colab.research.google.com/gist/sushreebarsa/414af12a513fd6aef5499bd97702fd47/70261.ipynb), could you please share the dependencies? Thank you!

@yousifj129 Could you refer to the above comment and let us know? Thank you!

@ian-huu One workaround could be to specify the input names during saving using the tf.saved_model.save API with the input argument. This ensures that all your model's inputs are included in...

@ian-huu Could you try to use tf.keras.models.load_model() to load the model and let us know? Please make sure that you are using the latest TF version? Thank you!

@ian-huu There are two SavedModel formats: legacy and the new high-level format. The error message indicates you're dealing with the legacy format, which isn't compatible with load_model. Please refer this...

@tilakrayal I was able to replicate the issue reported [here](https://colab.research.google.com/gist/sushreebarsa/888c6010aa9f9957f66b6503b5ee7f14/69307.ipynb). Please have a look at this issue. Thank you!

@pekaalto The GPU implementation of bucketize might not handle the rounding or boundary conditions in the same way as the CPU implementation. This could lead to differences in how values...

@tilakrayal I was able to replicate the issue reported [here](https://colab.research.google.com/gist/sushreebarsa/abcfb366665be6100ac838150531699f/70343.ipynb#scrollTo=_OiohTm0Iy4s). Thank you!

@Leo-Lifeblood I was able to replicate the output reported [here](https://colab.research.google.com/gist/sushreebarsa/c573727f8cf0f77be2dc13af243567a4/70520.ipynb), could you please share the error you are encountering ? Thank you!

@luanft Please make sure the conversion is done correctly; ``` # Convert the model to TFLite converter = tf.lite.TFLiteConverter.from_keras_model(nn_model) tflite_model = converter.convert() # Save the TFLite model with open('model.tflite', 'wb')...