Add an example that train the torchtitan version of llama. #8400
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tengyifei
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| tpu_args = "--xla_tpu_enable_async_collective_fusion_fuse_all_gather=true --xla_tpu_megacore_fusion_allow_ags=false --xla_enable_async_collective_permute=true --xla_tpu_enable_ag_backward_pipelining=true --xla_tpu_enable_data_parallel_all_reduce_opt=true --xla_tpu_data_parallel_opt_different_sized_ops=true --xla_tpu_enable_async_collective_fusion=true --xla_tpu_enable_async_collective_fusion_multiple_steps=true --xla_tpu_overlap_compute_collective_tc=true --xla_enable_async_all_gather=true" | ||
| os.environ.setdefault('LIBTPU_INIT_ARGS', tpu_args) | ||
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| _setup_default_env() |
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Did you test that changing the environ here actually gets picked up by XLA? For example I was wondering if import jax or some other import will cause the TPU backend to get initialized and ignore future changes to XLA flags.
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hmmm... moving to the top to be safe.
tengyifei
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experimental/torch_xla2/examples/train_llama_torchtitan/train_llama.py
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experimental/torch_xla2/examples/train_llama_torchtitan/train_llama.py
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experimental/torch_xla2/examples/train_llama_torchtitan/train_llama.py
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experimental/torch_xla2/examples/train_llama_torchtitan/train_llama.py
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Few bugs fixed along the way: