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[Feature] Split cross-entropy computation in SP (#5959)
* halfway * fix cross-PP-stage position id length diff bug * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * unified cross entropy func for all shardformer models * remove redundant lines * add basic ring attn; debug cross entropy * fwd bwd logic complete * fwd bwd logic complete; add experimental triton rescale * precision tests passed * precision tests passed * fix typos and remove misc files * update softmax_lse shape by new interface * change tester name * remove buffer clone; support packed seq layout * add varlen tests * fix typo * all tests passed * add dkv_group; fix mask * remove debug statements * adapt chatglm, command-R, qwen * debug * halfway * fix cross-PP-stage position id length diff bug * fix typo * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * unified cross entropy func for all shardformer models * remove redundant lines * add basic ring attn; debug cross entropy * fwd bwd logic complete * fwd bwd logic complete; add experimental triton rescale * precision tests passed * precision tests passed * fix typos and remove misc files * add sp_mode to benchmark; fix varlen interface * update softmax_lse shape by new interface * add varlen tests * fix typo * all tests passed * add dkv_group; fix mask * remove debug statements * add comments * q1 index only once * remove events to simplify stream sync * simplify forward/backward logic * 2d ring forward passed * 2d ring backward passed * fixes * fix ring attn loss * 2D ring backward + llama passed * merge * update logger * fix typo * rebase * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix typo * remove typos * fixes * support GPT --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@@ -157,7 +157,6 @@ def build_model_from_hybrid_plugin(
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sharded_optimizer = sharded_optim_class(sharded_model.parameters(), lr=1e-3)
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criterion = loss_fn
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plugin = pluggin_cls(**test_config)
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booster = Booster(plugin=plugin)
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@@ -323,7 +322,6 @@ def check_output_hidden_state(
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sp_size = shard_config.sequence_parallel_size
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if org_hidden_state.shape[seq_dim] == sharded_hidden_state.shape[seq_dim] * sp_size:
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org_hidden_state = org_hidden_state.chunk(sp_size, dim=seq_dim)[dist.get_rank(sp_group)]
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assert_close(org_hidden_state.float(), sharded_hidden_state.float(), atol=atol, rtol=rtol)
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