[Pallas] Integrate FlashAttention with SPMD#6935
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alanwaketan merged 9 commits intomasterfrom Apr 18, 2024
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JackCaoG
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Apr 17, 2024
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| if xr.device_type() == 'TPU': | ||
| from torch_xla.experimental.custom_kernel import jax_import_guard | ||
| jax_import_guard() | ||
| import jax | ||
| import jax.numpy as jnp | ||
| from jax.experimental import pallas as pl |
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nit, you can put this part in the setup class similar to https://github.com/pytorch/xla/blob/master/test/spmd/test_xla_sharding_base.py#L31-L35
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Is python import global?
| jax.config.update('jax_default_matmul_precision', jax.lax.Precision.HIGHEST) | ||
| from torch_xla.experimental.custom_kernel import flash_attention | ||
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| xr.use_spmd() |
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nit, this should be called in the setup class since it is a one time global config.
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I probably can call this in main as well. The setup class seems overkilled for this.
jonb377
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Apr 17, 2024
| @unittest.skipIf(xr.device_type() != 'TPU' or tpu.version() < 3, | ||
| "This test only works on TPUv3+.") | ||
| def test_flash_attention_spmd_data_parallel(self): | ||
| jax.config.update('jax_default_matmul_precision', jax.lax.Precision.HIGHEST) |
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Does this impact the resulting kernel?
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| @staticmethod | ||
| def forward(ctx, q, k, v, causal=False): | ||
| def forward(ctx, q, k, v, causal=False, sharding_spec=None, mesh=None): |
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nit: sharding_spec -> partition_spec?
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Thanks Jon and Jack for the reviews. |
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Summary:
This pull request integrating FlashAttention with SPMD. The way it works is to create a manual sharding region for the kernel which means we wraps all the inputs with enable_manual_sharding and all the outputs with disable_manual_sharding.
Added a new test file because the original test file is not SPMD aware.
Test Plan:
PJRT_DEVICE=TPU python test/test_pallas_spmd.py