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[model] fix: qwen2vl for transformers 4.52.* #3524

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Merged
vermouth1992 merged 1 commit into from
Sep 18, 2025
Merged

[model] fix: qwen2vl for transformers 4.52.* #3524

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73 changes: 32 additions & 41 deletions verl/models/transformers/monkey_patch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
"""

import sys
from types import SimpleNamespace
from typing import Optional

import torch
Expand Down Expand Up @@ -239,70 +240,60 @@ def state_dict(self, *args, **kwargs):
print("Monkey patch state_dict in AutoModelForCausalLMWithValueHead. ")

# TODO: VLM models only, unify monkey patch to LLM models.
if model.config.model_type == "qwen2_5_vl":
if model.config.model_type in ["qwen2_5_vl", "qwen2_vl"]:
# Step 1: patch model to support image-text mixed data
if is_transformers_version_in_range(min_version="4.52.0"):
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import (
Qwen2_5_VLAttention,
Qwen2_5_VLForConditionalGeneration,
Qwen2_5_VLModel,
Qwen2_5_VLTextModel,
)

from verl.models.transformers.qwen2_vl import forward_with_normal_backend, qwen2_vl_base_forward

Qwen2_5_VLModel.forward = qwen2_vl_base_forward
Qwen2_5_VLForConditionalGeneration.forward = forward_with_normal_backend
else:
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import (
Qwen2_5_VLFlashAttention2 as Qwen2_5_VLAttention,
)
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import (
Qwen2_5_VLForConditionalGeneration,
)
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLModel as Qwen2_5_VLTextModel

from verl.models.transformers.qwen2_vl import forward_with_normal_backend

Qwen2_5_VLForConditionalGeneration.forward = forward_with_normal_backend

if use_remove_padding or ulysses_sp_size > 1:
from verl.models.transformers.qwen2_vl import qwen2_vl_attn_forward

Qwen2_5_VLAttention.forward = qwen2_vl_attn_forward
print("Monkey patch Qwen2.5VL attention layer")

if ulysses_sp_size > 1:
patch_vlm_for_ulysses_input_slicing(Qwen2_5_VLTextModel)

elif model.config.model_type == "qwen2_vl":
if is_transformers_version_in_range(min_version="4.52.0"):
from transformers.models.qwen2_vl.modeling_qwen2_vl import (
Qwen2VLAttention,
Qwen2VLForConditionalGeneration,
Qwen2VLModel,
Qwen2VLTextModel,
)

from verl.models.transformers.qwen2_vl import forward_with_normal_backend, qwen2_vl_base_forward

Qwen2VLModel.forward = qwen2_vl_base_forward
Qwen2VLForConditionalGeneration.forward = forward_with_normal_backend
else:
from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLFlashAttention2 as Qwen2VLAttention
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLForConditionalGeneration
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLModel as Qwen2_5_VLTextModel
from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLForConditionalGeneration
from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLModel as Qwen2VLTextModel

from verl.models.transformers.qwen2_vl import forward_with_normal_backend
Qwen2_5_VLModel = SimpleNamespace(forward=None)
Qwen2VLModel = SimpleNamespace(forward=None)

from verl.models.transformers.qwen2_vl import forward_with_normal_backend, qwen2_vl_base_forward

Qwen2VLForConditionalGeneration.forward = forward_with_normal_backend
Qwen2_5_VLModel.forward = qwen2_vl_base_forward
Qwen2VLModel.forward = qwen2_vl_base_forward
Qwen2_5_VLForConditionalGeneration.forward = forward_with_normal_backend
Qwen2VLForConditionalGeneration.forward = forward_with_normal_backend
print(f"Monkey patch {model.__class__.__name__} model forward")

# Step 2: patch attention to support ulysses parallelism
if is_transformers_version_in_range(min_version="4.54.0"):
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import Qwen2_5_VLAttention
from transformers.models.qwen2_vl.modeling_qwen2_vl import Qwen2VLAttention
elif is_transformers_version_in_range(min_version="4.53.0"):
raise RuntimeError("Transformers 4.53.* is bugged. Use transformers 4.54.0 or later.")
else:
from transformers.models.qwen2_5_vl.modeling_qwen2_5_vl import (
Qwen2_5_VLFlashAttention2 as Qwen2_5_VLAttention,
)
from transformers.models.qwen2_vl.modeling_qwen2_vl import (
Qwen2VLFlashAttention2 as Qwen2VLAttention,
)

if use_remove_padding or ulysses_sp_size > 1:
from verl.models.transformers.qwen2_vl import qwen2_vl_attn_forward

Qwen2_5_VLAttention.forward = qwen2_vl_attn_forward
Qwen2VLAttention.forward = qwen2_vl_attn_forward
print("Monkey patch Qwen2VL attention layer")
print(f"Monkey patch {model.__class__.__name__} attention layer")

# Step 3: patch input for multimodal sequence parallelism
if ulysses_sp_size > 1:
patch_vlm_for_ulysses_input_slicing(Qwen2_5_VLTextModel)
patch_vlm_for_ulysses_input_slicing(Qwen2VLTextModel)

elif model.config.model_type == "kimi_vl":
Expand Down
14 changes: 6 additions & 8 deletions verl/models/transformers/qwen2_vl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -216,19 +216,17 @@ def _custom_flash_attention_forward(

if position_ids is not None and query_length != 1 and not (torch.diff(position_ids, dim=-1) >= 0).all():
batch_size = query_states.size(0)
query_states, key_states, value_states, cu_seq_lens, max_seq_lens = prepare_fa2_from_position_ids(
q, k, v, (cu_seqlens_q, cu_seqlens_k), (max_seqlen_q, max_seqlen_k) = prepare_fa2_from_position_ids(
query_states, key_states, value_states, position_ids
)
cu_seqlens_q, cu_seqlens_k = cu_seq_lens
max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens
attn_output = flash_attn_varlen_func(
query_states,
key_states,
value_states,
q=q,
k=k,
v=v,
cu_seqlens_q=cu_seqlens_q,
cu_seqlens_k=cu_seqlens_k,
max_seqlen_q=max_seqlen_in_batch_q,
max_seqlen_k=max_seqlen_in_batch_k,
max_seqlen_q=max_seqlen_q,
max_seqlen_k=max_seqlen_k,
dropout_p=kwargs.pop("dropout", 0.0),
softmax_scale=kwargs.pop("softmax_scale", None),
causal=is_causal,
Expand Down
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