Comments (2)
hawkinsp
commented on June 30, 2024
Currently the XLA Python bindings are something of an internal detail of JAX and they aren't exposed at all as part of TensorFlow. It's not clear whether they will remain part of XLA itself or move into JAX; that is to be determined.
Can you say more about the use case? That might help answer the question about public APIs.
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vinayburugu
commented on June 30, 2024
Understood.
Here is the usecase :
We would like to handle exceptions arising from XLA with custom messages in the framework. But XlaRuntimeError is not visible in tensorflow python layer. What are the steps needed to make it visible in tensorflow?
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Related Issues (20)
- [XLA:CPU] oneDNN Softmax gives inaccurate results HOT 1
- call ptxas become defunct, cause xla hung HOT 2
- gpu_hlo_cost_analysis NumOfDevices always return 0 HOT 2
- [Feature Request]Add more comm op support on gpu_hlo_cost_analysis HOT 4
- gpu f16 cast to fp32 calculation, and then converted back? HOT 1
- "Could not find executable `nvidia-smi`" for `./configure.py --backend=CUDA` HOT 6
- Build from source fails HOT 7
- XLA documentation for Windows HOT 1
- Implement GitHub Presubmit Checks for Windows Environment HOT 1
- Support builds with cuDNN 9
- gpu_fused_mha_test fails at HEAD on H100 HOT 1
- Workable example on normal DNN model
- [xla:auto_sharding] Question about resharding costs of Reshape strategies
- OpenCL Support. HOT 2
- BF16 matmul slower than F32 matmul on T4 GPU HOT 3
- PJRT `CopyCpuBufferToLiteral` of JAX buffer taking too long HOT 9
- Porting XLA to different backends. HOT 4
- Compiling xla/mlir/tools/mlir_interpreter/dialects/util.cc failed HOT 3
- MHLO Extraction from XLA Compiler HOT 4
- Controlling a single compiler pass in XLA for CPU target HOT 2
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