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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]",
],
)
],
)
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