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| import copy |
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| from transformers import LlamaConfig, Qwen2Config |
| from transformers.configuration_utils import PretrainedConfig |
| from transformers.utils import logging |
|
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| from .configuration_intern_vit import InternVisionConfig |
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| logger = logging.get_logger(__name__) |
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|
|
| class InternVLChatConfig(PretrainedConfig): |
| model_type = "internvl_chat" |
| is_composition = True |
|
|
| def __init__( |
| self, |
| vision_config=None, |
| llm_config=None, |
| use_backbone_lora=0, |
| use_llm_lora=0, |
| select_layer=-1, |
| force_image_size=None, |
| downsample_ratio=0.5, |
| template=None, |
| dynamic_image_size=False, |
| use_thumbnail=False, |
| ps_version="v1", |
| min_dynamic_patch=1, |
| max_dynamic_patch=6, |
| **kwargs, |
| ): |
| super().__init__(**kwargs) |
|
|
| if vision_config is None: |
| vision_config = {} |
| logger.info("vision_config is None. Initializing the InternVisionConfig with default values.") |
|
|
| if llm_config is None: |
| llm_config = {"architectures": ["Qwen2ForCausalLM"]} |
| logger.info("llm_config is None. Initializing the LlamaConfig config with default values (`LlamaConfig`).") |
|
|
| self.vision_config = InternVisionConfig(**vision_config) |
| if llm_config["architectures"][0] == "LlamaForCausalLM": |
| self.llm_config = LlamaConfig(**llm_config) |
| elif llm_config["architectures"][0] == "Qwen2ForCausalLM": |
| self.llm_config = Qwen2Config(**llm_config) |
| else: |
| raise ValueError("Unsupported architecture: {}".format(llm_config["architectures"][0])) |
| self.use_backbone_lora = use_backbone_lora |
| self.use_llm_lora = use_llm_lora |
| self.select_layer = select_layer |
| self.force_image_size = force_image_size |
| self.downsample_ratio = downsample_ratio |
| self.template = template |
| self.dynamic_image_size = dynamic_image_size |
| self.use_thumbnail = use_thumbnail |
| self.ps_version = ps_version |
| self.min_dynamic_patch = min_dynamic_patch |
| self.max_dynamic_patch = max_dynamic_patch |
|
|
| logger.info(f"vision_select_layer: {self.select_layer}") |
| logger.info(f"ps_version: {self.ps_version}") |
| logger.info(f"min_dynamic_patch: {self.min_dynamic_patch}") |
| logger.info(f"max_dynamic_patch: {self.max_dynamic_patch}") |
|
|
| def to_dict(self): |
| """ |
| Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. |
| |
| Returns: |
| `Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance, |
| """ |
| output = copy.deepcopy(self.__dict__) |
| output["vision_config"] = self.vision_config.to_dict() |
| output["llm_config"] = self.llm_config.to_dict() |
| output["model_type"] = self.__class__.model_type |
| output["use_backbone_lora"] = self.use_backbone_lora |
| output["use_llm_lora"] = self.use_llm_lora |
| output["select_layer"] = self.select_layer |
| output["force_image_size"] = self.force_image_size |
| output["downsample_ratio"] = self.downsample_ratio |
| output["template"] = self.template |
| output["dynamic_image_size"] = self.dynamic_image_size |
| output["use_thumbnail"] = self.use_thumbnail |
| output["ps_version"] = self.ps_version |
| output["min_dynamic_patch"] = self.min_dynamic_patch |
| output["max_dynamic_patch"] = self.max_dynamic_patch |
|
|
| return output |
|
|
