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c5b071d 7ea993f c5b071d 7ea993f c5b071d 7ea993f c5b071d 7ea993f c5b071d | 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 | from typing import Any, Optional
from transformers.configuration_utils import PretrainedConfig
# Remove Qwen3Config import as it causes error on older transformers/python versions
# from transformers.models.qwen3 import Qwen3Config
#from transformers import Qwen2_5_VLProcessor, AutoProcessor
from transformers.models.auto.configuration_auto import CONFIG_MAPPING
class MonkeyOCRv2VisionConfig(PretrainedConfig):
model_type = "MonkeyOCRv2VisionTransformer"
def __init__(
self,
embed_dim: int = 1536, # vision encoder embed size
hidden_size: int = 1536, # after merger hidden size
intermediate_size: int = 4224,
num_hidden_layers: int = 42,
num_attention_heads: int = 12,
num_channels: int = 3,
patch_size: int = 14,
spatial_merge_size: int = 2,
temporal_patch_size: int = 1,
rms_norm_eps: float = 1e-5,
use_bias: bool = False,
vision_attn_implementation="flash_attention_2", # "eager","sdpa","flash_attention_2"
initializer_range=0.02,
init_merger_std=0.02,
is_causal=False, # ve causal forward
post_norm=True,
gradient_checkpointing=False,
**kwargs: Any,
):
super().__init__(**kwargs)
self.embed_dim = embed_dim
self.hidden_size = hidden_size
self.intermediate_size = intermediate_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.num_channels = num_channels
self.patch_size = patch_size
self.spatial_merge_size = spatial_merge_size
self.temporal_patch_size = temporal_patch_size
self.rms_norm_eps = rms_norm_eps
self.use_bias = use_bias
self.vision_attn_implementation = vision_attn_implementation
self.initializer_range = initializer_range
self.init_merger_std = init_merger_std
self.is_causal = is_causal
self.post_norm = post_norm
self.gradient_checkpointing = gradient_checkpointing
# Commented out Processor definition to avoid dependencies on Qwen2_5_VLProcessor
# class MonkeyOCRv2Processor(Qwen2_5_VLProcessor):
# attributes = ["image_processor", "tokenizer"]
# def __init__(self, image_processor=None, tokenizer=None, chat_template=None, **kwargs):
# super().__init__(image_processor, tokenizer, chat_template=chat_template)
# AutoProcessor.register("MonkeyOCRv2VisionTransformer", MonkeyOCRv2Processor)
CONFIG_MAPPING.register("MonkeyOCRv2VisionTransformer", MonkeyOCRv2VisionConfig)
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