Comments (2)
We can use Alpa to parallelize LLaMa with jax/jaxlib==0.3.22
, but it fails with jax/jaxlib==0.4.6
.
The reason why we want to switch to jax/jaxlib==0.4.6
is because we want to use the new features pf jax.
We also found jax/jaxlib==0.4.6
failed with built-int workload example/gpt2
from alpa.
A lot of changes have been made in version 0.4 and version 0.3 of jax
from alpa.
Related Issues (20)
- Will alpa support jax 0.4.x and cuda 12.x?
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- Problem in building Alpa-modified Jaxlib. HOT 5
- IndexError: `InlinedVector::at(size_type) const` failed bounds check
- Check failed: operand_dim < ins->operand(0)->shape().rank() (2 vs. 2)Does not support this kind of Gather. HOT 2
- How to build debug-version Alpa-modified jaxlib HOT 3
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- Unsupported parallel mode in shard-only auto perf test: load_solution
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- A question about file /alpa/benchmark/gen_serving_database.py
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- Why did you choose ray instead of using torch distributed? HOT 2
- Ray spill out of disk error when using alpa to auto-parallelize llama HOT 2
- How to profile Alpa models and get the trace HOT 1
- Check Installation failled HOT 1
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