Comments (7)
letting you guys know that numba
has recently opensourced their numbapro
paid library, so everyone can use 'gpu' and 'parallel' targets now! I'd be really excited to see if anyone would use any of those in tensorflow
from tensorflow.
Our team has recently released a library for python-native TensorFlow operator definition and optimization: opveclib. It is not part of the numba ecosystem, but I believe could be an alternative solution to @datnamer 's desired functionality.
from tensorflow.
So I did some digging in the documentation. It would be convenient to be able to write a new op with Numba.
from tensorflow.
👍
from tensorflow.
I think that 'close' belongs over in tensorflow/skflow #47
from tensorflow.
Oops, sorry.
from tensorflow.
Since we have py_func() you can utilize any python numpy based library, so this feature seems addressed. If you have a more targeted feature request, we'd be happy to talk about it. Thanks!
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Related Issues (20)
- problem with converted custom model at TensorFlow Lite
- 模板类 TensorContractionBlocking 的模板参数数量不正确 HOT 1
- [Error]tf-opt --tf-init-text-file-to-import --tf-saved-model-dir HOT 1
- Aborted (core dumped) in `tf.irfftnd/ifftnd/irfftnd`
- _image_ops.so not found
- Inconsistency in CPU results and GPU results in model training HOT 4
- Unable bazel build tensorflow with cuda support inside a docker HOT 1
- TFLite GPUv2: ADD(x, 1e-5) results in severely wrong output HOT 1
- Why don't you provide a standard go-lang get install?
- Protobuf does not support 4.x HOT 2
- Failed to compile on aarch64 HOT 1
- Fit function to work with adaptive step size
- Documentation for `tf.linalg.set_diag()` is missing return information HOT 3
- NumPy 2.0 support
- wrong calculations with TPU distribution strategy HOT 1
- Iterating over a symbolic `tf.Tensor` is not allowed: AutoGraph did convert this function
- Why tf.data.Dataset.choose_from_datasets() chooses only one element from dataset of size-element 5, I want to unite with other dataset of size-element 5 the same. If I want to merge dataset with all their elements and get <ChooseDataset ...> with 10 elements inside HOT 1
- tf.data filter dataset too slow HOT 2
- import tensorflow.compat.v2 could not be resolved HOT 5
- Broken ExtensionType interoperability with Keras in 2.16
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