Use attention ops from Tokamax#4465
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Pallas Triton is heading towards deprecation, so these ops will eventually be removed from JAX. Closes #4384. PiperOrigin-RevId: 945567777
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| out = gpu_pallas_attention.mha(query, key, value, decoder_segment_ids, sm_scale=1.0, causal=True) | ||
| mask = tokamax_attention_base.Mask(is_causal=True) | ||
| if decoder_segment_ids is not None: | ||
| seg_mask = decoder_segment_ids[:, :, None] == decoder_segment_ids[:, None, :] |
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I needed to add the following to make it work:
seg_mask = seg_mask[:, None, :, :]
Tokamax infers batch dims by rank, so a rank-3 (B, T, t) mask matches its rank-3 (#heads, T, t) annotation exactly and the batch dim gets misread as the head dim — adding an explicit singleton head dim ((B, 1, T, t)) lets it vmap over batch and broadcast across heads.
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Use attention ops from Tokamax
Pallas Triton is heading towards deprecation, so these ops will eventually be
removed from JAX.
Closes #4384.