42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from vllm.lora.layers.base import BaseLayerWithLoRA
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from vllm.lora.layers.column_parallel_linear import (
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ColumnParallelLinearWithLoRA,
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ColumnParallelLinearWithShardedLoRA,
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MergedColumnParallelLinearWithLoRA,
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MergedColumnParallelLinearWithShardedLoRA,
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MergedQKVParallelLinearWithLoRA,
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MergedQKVParallelLinearWithShardedLoRA,
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QKVParallelLinearWithLoRA,
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QKVParallelLinearWithShardedLoRA,
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)
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from vllm.lora.layers.fused_moe import FusedMoEWithLoRA
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from vllm.lora.layers.logits_processor import LogitsProcessorWithLoRA
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from vllm.lora.layers.replicated_linear import ReplicatedLinearWithLoRA
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from vllm.lora.layers.row_parallel_linear import (
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RowParallelLinearWithLoRA,
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RowParallelLinearWithShardedLoRA,
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)
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from vllm.lora.layers.utils import LoRAMapping
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from vllm.lora.layers.vocal_parallel_embedding import VocabParallelEmbeddingWithLoRA
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__all__ = [
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"BaseLayerWithLoRA",
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"VocabParallelEmbeddingWithLoRA",
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"LogitsProcessorWithLoRA",
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"ColumnParallelLinearWithLoRA",
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"ColumnParallelLinearWithShardedLoRA",
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"MergedColumnParallelLinearWithLoRA",
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"MergedColumnParallelLinearWithShardedLoRA",
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"MergedQKVParallelLinearWithLoRA",
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"MergedQKVParallelLinearWithShardedLoRA",
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"QKVParallelLinearWithLoRA",
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"QKVParallelLinearWithShardedLoRA",
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"RowParallelLinearWithLoRA",
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"RowParallelLinearWithShardedLoRA",
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"ReplicatedLinearWithLoRA",
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"LoRAMapping",
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"FusedMoEWithLoRA",
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]
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