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THE CONSCIOUSNESS ATLAS
Read. Experiment. Follow the evidence.

ConsciousnessLearn · Explore · Joseph Anady

DeepSeek FlashAttention2._upad_input: cu seqlens q

In DeepseekV3FlashAttention2._upad_input, this statement defines or updates cu_seqlens_q. The addition or subtraction updates the named state or combines residual contributions. The input shapes and the order in the surrounding forward path must be preserved.

Donor model implementationhistorical source recovered; expression not executed in this website audit
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donor-eq-56f5eeeb2dd70dsource-code mathematical expression
cuseqlensq=torch.arange(batchsize+1,dtype=torch.int32,device=querylayer.device)cu_seqlens_q = torch.arange( batch_size + 1, dtype=torch.int32, device=query_layer.device )

Read the equation

In DeepseekV3FlashAttention2._upad_input, this statement defines or updates cu_seqlens_q. The addition or subtraction updates the named state or combines residual contributions. The input shapes and the order in the surrounding forward path must be preserved.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

  1. Read cu_seqlens_q as the quantity being defined or updated by this relation.

  2. Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.

  3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

Source recovery establishes that the expression appears in this record. Its mathematical validity, implementation behavior, and interpretation must be assessed separately. See the linked source and research notes for the checks available for this version.

Original context

Read the surrounding source passage
indices_q = indices_k
        elif query_length == 1:
            max_seqlen_in_batch_q = 1
            cu_seqlens_q = torch.arange(
                batch_size + 1, dtype=torch.int32, device=query_layer.device
            )  # There is a memcpy here, that is very bad.
            indices_q = cu_seqlens_q[:-1]
            query_layer = query_layer.squeeze(1)
        else:
Exact original notation
cu_seqlens_q = torch.arange(
                batch_size + 1, dtype=torch.int32, device=query_layer.device
            )

Related builds

Sources & provenance

01
kimi source tree.txt
lines 3433–3435 · Aug 5, 2026
cu_seqlens_q = torch.arange( batch_size + 1, dtype=torch.int32, device=query_layer.device )
02
DEEPSEEK_R1_COMPLETE.txt
lines 3224–3226 · Aug 5, 2026
cu_seqlens_q = torch.arange( batch_size + 1, dtype=torch.int32, device=query_layer.device )

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