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7ae83df | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | # Copyright 2024 Bytedance Ltd. and/or its affiliates
#
# 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.
from transformers.modeling_utils import ALL_ATTENTION_FUNCTIONS
from ..utils.py_functional import is_transformers_version_greater_than
from .transformers.flash_attention_utils import flash_attention_forward
SUPPORTED_MODEL_TYPE = (
"llama",
"gemma",
"gemma2",
"mistral",
"qwen2",
"qwen2_moe",
"qwen3",
"qwen3_moe",
"qwen2_vl",
"qwen2_5_vl",
"qwen3_vl",
"qwen3_vl_moe",
)
QWEN2_VL_MODELS = ("qwen2_vl", "qwen2_5_vl")
QWEN3_VL_MODELS = ("qwen3_vl", "qwen3_vl_moe")
def apply_ulysses_patch(model_type: str) -> None:
if not is_transformers_version_greater_than("4.54.0"):
raise RuntimeError("Only support transformers >= 4.54.0.")
if model_type in SUPPORTED_MODEL_TYPE:
ALL_ATTENTION_FUNCTIONS["flash_attention_2"] = flash_attention_forward
else:
#model_type = "qwen2_5_vl"
raise NotImplementedError(f"Model architecture {model_type} is not supported yet.")
if model_type in QWEN2_VL_MODELS:
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import (
Qwen2_5_VLForConditionalGeneration,
Qwen2_5_VLModel,
)
from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLForConditionalGeneration, Qwen2VLModel
from .transformers.qwen2_vl import qwen2_vl_base_forward, qwen2_vl_model_forward
# fix text-image mixed data
Qwen2VLModel.forward = qwen2_vl_base_forward
Qwen2_5_VLModel.forward = qwen2_vl_base_forward
# TODO: add linear cross entropy kernels
Qwen2VLForConditionalGeneration.forward = qwen2_vl_model_forward
Qwen2_5_VLForConditionalGeneration.forward = qwen2_vl_model_forward
elif model_type in QWEN3_VL_MODELS:
from transformers.models.qwen3_vl.modeling_qwen3_vl import Qwen3VLForConditionalGeneration, Qwen3VLModel
from transformers.models.qwen3_vl_moe.modeling_qwen3_vl_moe import (
Qwen3VLMoeForConditionalGeneration,
Qwen3VLMoeModel,
)
from .transformers.qwen3_vl import qwen3_vl_base_forward, qwen3_vl_model_forward
# fix text-image mixed data
Qwen3VLModel.forward = qwen3_vl_base_forward
Qwen3VLMoeModel.forward = qwen3_vl_base_forward
# TODO: add linear cross entropy kernels
Qwen3VLForConditionalGeneration.forward = qwen3_vl_model_forward
Qwen3VLMoeForConditionalGeneration.forward = qwen3_vl_model_forward
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