sushreebarsa
sushreebarsa
@shamazharikh Could you up-sample its 3D data to a higher resolution before applying regular max/avg pooling. This offers some control over the output size but adds computational overhead. Please refer...
@haraldurt Instead of relying on "SAME" padding, we could try specifying the padding values manually to control the output shape more precisely. If you still have a concern then please...
@amlinux A reference could be [golang-tensorflow](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/go/README.md) that provides Go wrappers for TensorFlow C++. If you still have a concern then please create a new ticket as you are using an...
@khatchad You're right, the official TF documentation for tf.linalg.set_diag() doesn't explicitly mention the return value in the descriptiontf.linalg.set_diag. Please refer the master [branch](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/array_ops.py) for the detailed information. Thank you!
@khatchad Could you please let us know if you have referred to the above [comment](https://github.com/tensorflow/tensorflow/issues/67255#issuecomment-2104241615) and you could see the return information ? Thank you!
@suyash-narain tflite.load_delegate directly searches for the shared library (.so file) and doesn't handle settings files like stable_delegate_settings.json. There's a workaround to achieve your goal using the Python API. Could you...
@suyash-narain If you're using a custom delegate library with its own settings, follow the TFLite delegate loading [documentation](https://www.tensorflow.org/lite/performance/delegates) to incorporate it. There isn't a well-established workaround to directly use the...
@gadagashwini I was able to replicate the issue on colab, please find the gist [here](https://colab.research.google.com/gist/sushreebarsa/f5e5d342a5e1e7e31a80d0e35a547076/16784.ipynb). Thank you!
@PolarBean Please refer to the comment above and let us know? Thank you!
@ahasselbring I tried to replicate the issue on colab and faced following error; ``` ValueError: Types are not compatible: TensorSpec(shape=(None,), dtype=tf.float32, name=None) with type of vs VariableSpec(shape=(1,), dtype=tf.float32, name='x') with...