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import copy |
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from .configuration_mmMamba import mmMambaConfig |
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from transformers.configuration_utils import PretrainedConfig |
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from transformers.utils import logging |
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from .configuration_mmMamba_embedding import mmMambaEmbeddingConfig |
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logger = logging.get_logger(__name__) |
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class mmMambaChatConfig(PretrainedConfig): |
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model_type = 'mmMamba_chat' |
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is_composition = True |
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def __init__( |
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self, |
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embedding_config=None, |
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llm_config=None, |
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use_backbone_lora=0, |
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use_llm_lora=0, |
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pad2square=False, |
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select_layer=-1, |
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force_image_size=None, |
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downsample_ratio=0.5, |
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template=None, |
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dynamic_image_size=False, |
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use_thumbnail=False, |
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ps_version='v1', |
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min_dynamic_patch=1, |
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max_dynamic_patch=6, |
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normalize_encoder_output=False, |
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**kwargs): |
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super().__init__(**kwargs) |
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if embedding_config is None: |
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embedding_config = {} |
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logger.info('embedding_config is None. Initializing the VisionConfig with default values.') |
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if llm_config is None: |
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llm_config = {} |
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logger.info('llm_config is None. Initializing the Config config with default values (`Config`).') |
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self.embedding_config = mmMambaEmbeddingConfig(**embedding_config) |
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self.llm_config = mmMambaConfig(**llm_config) |
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self.use_backbone_lora = use_backbone_lora |
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self.use_llm_lora = use_llm_lora |
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self.pad2square = pad2square |
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self.select_layer = select_layer |
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self.force_image_size = force_image_size |
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self.downsample_ratio = downsample_ratio |
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self.template = template |
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self.dynamic_image_size = dynamic_image_size |
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self.use_thumbnail = use_thumbnail |
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self.ps_version = ps_version |
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self.min_dynamic_patch = min_dynamic_patch |
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self.max_dynamic_patch = max_dynamic_patch |
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self.normalize_encoder_output = normalize_encoder_output |
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logger.info(f'vision_select_layer: {self.select_layer}') |
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logger.info(f'ps_version: {self.ps_version}') |
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logger.info(f'min_dynamic_patch: {self.min_dynamic_patch}') |
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logger.info(f'max_dynamic_patch: {self.max_dynamic_patch}') |
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def to_dict(self): |
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""" |
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Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. |
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Returns: |
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`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance, |
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""" |
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output = copy.deepcopy(self.__dict__) |
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output['embedding_config'] = self.embedding_config.to_dict() |
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output['llm_config'] = self.llm_config.to_dict() |
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output['model_type'] = self.__class__.model_type |
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output['use_backbone_lora'] = self.use_backbone_lora |
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output['use_llm_lora'] = self.use_llm_lora |
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output['pad2square'] = self.pad2square |
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output['select_layer'] = self.select_layer |
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output['force_image_size'] = self.force_image_size |
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output['downsample_ratio'] = self.downsample_ratio |
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output['template'] = self.template |
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output['dynamic_image_size'] = self.dynamic_image_size |
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output['use_thumbnail'] = self.use_thumbnail |
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output['ps_version'] = self.ps_version |
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output['min_dynamic_patch'] = self.min_dynamic_patch |
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output['max_dynamic_patch'] = self.max_dynamic_patch |
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output['normalize_encoder_output'] = self.normalize_encoder_output |
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return output |
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