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| # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. | |
| # SPDX-License-Identifier: Apache-2.0 | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| def get_fa_ca_qv_lora_config(first_nblocks=28, rank=8, scale=1): | |
| """ | |
| Get a LoRA configuration for the Self-Attention (FA) and Cross-Attention (CA) blocks in the model. | |
| This LoRA configuration is used to inject LoRA parameters into the model. | |
| Args: | |
| first_nblocks (int): The number of blocks to apply LoRA to. | |
| rank (int): The rank of the LoRA matrices. | |
| """ | |
| blocks_regex = r"\b(" + "|".join([str(i) for i in range(first_nblocks)]) + r")\b" | |
| return dict( | |
| enabled=True, | |
| customization_type="LoRA", | |
| rank=rank, | |
| scale=scale, | |
| edits=[ | |
| dict( | |
| blocks=blocks_regex, | |
| customization_type="LoRA", | |
| rank=rank, | |
| scale=scale, | |
| block_edit=[ | |
| "FA[to_q, to_v]", | |
| "CA[to_q, to_v]", | |
| ], | |
| ) | |
| ], | |
| ) | |