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119 lines
4.0 KiB
Python
119 lines
4.0 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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from tokenspeed.runtime.cache.kvstore_controller import LayerDoneCounter
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from tokenspeed.runtime.cache.mamba_cache_host import MambaPoolHost
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from tokenspeed.runtime.cache.transfer.types import CacheKind
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from tokenspeed.runtime.layers.attention.backends.hybrid_linear_attn import (
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SimpleMambaPool,
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)
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class MambaCachePool:
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kind = CacheKind.MAMBA
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def __init__(
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self,
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device_pool: SimpleMambaPool,
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host_pool: MambaPoolHost,
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io_backend: str,
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):
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self.device_pool = device_pool
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self.host_pool = host_pool
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self.io_backend = io_backend
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self._counter = LayerDoneCounter(self.num_layers())
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device_pool.register_layer_transfer_counter(self._counter)
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@property
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def device(self) -> torch.device | str:
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return self.device_pool.device
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@property
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def host_layout(self) -> str:
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return self.host_pool.layout
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def page_size(self) -> int:
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return 1
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def num_layers(self) -> int:
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return int(self.device_pool.conv_state.shape[0])
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def supports_layerwise_loadback(self) -> bool:
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return True
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def get_layer_done_counter(self) -> LayerDoneCounter:
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return self._counter
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def local_layer_idx(self, global_layer_id: int) -> int:
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return self.device_pool.mamba_map[global_layer_id]
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def writeback(
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self,
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src_indices: torch.Tensor,
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dst_indices: torch.Tensor,
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block_quota: int | None = None,
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) -> None:
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self.host_pool.backup_from_device_all_layer(
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self.device_pool,
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host_indices=dst_indices,
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device_indices=src_indices,
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io_backend=self.io_backend,
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block_quota=block_quota,
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)
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def loadback(
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self, src_indices: torch.Tensor, dst_indices: torch.Tensor, layer_idx: int
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) -> None:
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self.host_pool.load_to_device_per_layer(
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self.device_pool,
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host_indices=src_indices,
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device_indices=dst_indices,
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layer_idx=layer_idx,
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io_backend=self.io_backend,
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)
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def copy_layer(
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self, src_indices: torch.Tensor, dst_indices: torch.Tensor, layer_idx: int
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) -> None:
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if src_indices.numel() == 0:
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return
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src_indices = src_indices.to(
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device=self.device, dtype=torch.int64, non_blocking=True
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)
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dst_indices = dst_indices.to(
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device=self.device, dtype=torch.int64, non_blocking=True
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)
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for cache in self.device_pool.mamba_cache:
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layer = cache[layer_idx]
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layer.index_copy_(0, dst_indices, layer.index_select(0, src_indices))
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def alloc_host(self, n: int) -> torch.Tensor | None:
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return self.host_pool.alloc(n)
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def free_host(self, indices: torch.Tensor) -> None:
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self.host_pool.free(indices)
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def host_available(self) -> int:
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return self.host_pool.available_size()
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