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53 lines
2.2 KiB
Python
53 lines
2.2 KiB
Python
# Copyright (c) 2026 LightSeek Foundation
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in
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# all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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from __future__ import annotations
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import torch
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def workspace_indices_to_kv_slots(
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workspace_indices: torch.Tensor,
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kv_workspace_slots: torch.Tensor | None,
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) -> torch.Tensor:
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"""Map DSA workspace-local top-k indices to global KV cache slot ids.
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Args:
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workspace_indices: Top-k indices in the compact DSA prefill workspace.
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Negative entries are treated as invalid sentinels and preserved.
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kv_workspace_slots: Lookup table mapping workspace rows to KV cache slots.
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Returns:
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A tensor with the same shape as ``workspace_indices`` containing int32 KV
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cache slot ids, or int32 ``workspace_indices`` when no lookup is provided.
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"""
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if kv_workspace_slots is None or workspace_indices.numel() == 0:
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return workspace_indices.to(torch.int32)
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flat_indices = workspace_indices.reshape(-1)
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valid = flat_indices >= 0
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flat_slots = flat_indices.to(torch.int64)
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if valid.any():
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flat_slots[valid] = kv_workspace_slots.to(
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device=workspace_indices.device,
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dtype=torch.int64,
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).index_select(0, flat_slots[valid])
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return flat_slots.view_as(workspace_indices).to(torch.int32)
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