Datasets:

zzhowe1207
/

tet-rl

# 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
from .transformers.qwen2_vl import (
    qwen2_vl_attn_forward,
    qwen2_vl_base_forward_new,
    qwen2_vl_forward_new,
    qwen2_vl_forward_old,
)


def apply_ulysses_patch(model_type: str) -> None:
    if model_type in ("llama", "gemma", "gemma2", "mistral", "qwen2", "qwen3", "qwen3_moe"):
        ALL_ATTENTION_FUNCTIONS["flash_attention_2"] = flash_attention_forward
    elif model_type in ("qwen2_vl", "qwen2_5_vl"):
        if is_transformers_version_greater_than("4.53.0"):
            from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLAttention
            from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLAttention

            Qwen2VLAttention.forward = qwen2_vl_attn_forward
            Qwen2_5_VLAttention.forward = qwen2_vl_attn_forward
            raise NotImplementedError("Transformers 4.53.* is not compatible with Qwen2-VL models.")
        else:
            from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLFlashAttention2
            from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLFlashAttention2

            Qwen2VLFlashAttention2.forward = qwen2_vl_attn_forward
            Qwen2_5_VLFlashAttention2.forward = qwen2_vl_attn_forward

        if is_transformers_version_greater_than("4.52.0"):
            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

            Qwen2VLModel.forward = qwen2_vl_base_forward_new
            Qwen2_5_VLModel.forward = qwen2_vl_base_forward_new
            Qwen2VLForConditionalGeneration.forward = qwen2_vl_forward_new
            Qwen2_5_VLForConditionalGeneration.forward = qwen2_vl_forward_new
        else:
            from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLForConditionalGeneration
            from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLForConditionalGeneration

            Qwen2VLForConditionalGeneration.forward = qwen2_vl_forward_old
            Qwen2_5_VLForConditionalGeneration.forward = qwen2_vl_forward_old
    else:
        raise NotImplementedError(f"Model architecture {model_type} is not supported yet.")

	# 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
	from .transformers.qwen2_vl import (
	qwen2_vl_attn_forward,
	qwen2_vl_base_forward_new,
	qwen2_vl_forward_new,
	qwen2_vl_forward_old,
	)


	def apply_ulysses_patch(model_type: str) -> None:
	if model_type in ("llama", "gemma", "gemma2", "mistral", "qwen2", "qwen3", "qwen3_moe"):
	ALL_ATTENTION_FUNCTIONS["flash_attention_2"] = flash_attention_forward
	elif model_type in ("qwen2_vl", "qwen2_5_vl"):
	if is_transformers_version_greater_than("4.53.0"):
	from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLAttention
	from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLAttention

	Qwen2VLAttention.forward = qwen2_vl_attn_forward
	Qwen2_5_VLAttention.forward = qwen2_vl_attn_forward
	raise NotImplementedError("Transformers 4.53.* is not compatible with Qwen2-VL models.")
	else:
	from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLFlashAttention2
	from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLFlashAttention2

	Qwen2VLFlashAttention2.forward = qwen2_vl_attn_forward
	Qwen2_5_VLFlashAttention2.forward = qwen2_vl_attn_forward

	if is_transformers_version_greater_than("4.52.0"):
	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

	Qwen2VLModel.forward = qwen2_vl_base_forward_new
	Qwen2_5_VLModel.forward = qwen2_vl_base_forward_new
	Qwen2VLForConditionalGeneration.forward = qwen2_vl_forward_new
	Qwen2_5_VLForConditionalGeneration.forward = qwen2_vl_forward_new
	else:
	from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLForConditionalGeneration
	from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLForConditionalGeneration

	Qwen2VLForConditionalGeneration.forward = qwen2_vl_forward_old
	Qwen2_5_VLForConditionalGeneration.forward = qwen2_vl_forward_old
	else:
	raise NotImplementedError(f"Model architecture {model_type} is not supported yet.")