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| from transformers import PretrainedConfig |
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| class InternImageConfig(PretrainedConfig): |
| r""" |
| This is the configuration class to store the configuration of a [`~InternImageModel`]. |
| It is used to instantiate an internimage model according to the specified arguments, defining the model |
| architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of |
| the internimage [OpenGVLab/internimage](https://huggingface.co/OpenGVLab/internimage) architecture. |
| |
| Configuration objects inherit from [`PretrainedConfig`] and can be used |
| to control the model outputs. Read the documentation from [`PretrainedConfig`] |
| for more information. |
| |
| Args: |
| core_op (`str`, *optional*, defaults to `"DCNv3"`): |
| Core operation used in the InternImageModel. |
| depths (`tuple`, *optional*, defaults to `(4, 4, 18, 4)`): |
| Tuple specifying the depth of layers in the InternImageModel. |
| groups (`tuple`, *optional*, defaults to `(4, 8, 16, 32)`): |
| Tuple specifying the group of layers in the InternImageModel. |
| channels (`int`, *optional*, defaults to `64`): |
| Number of channels in the InternImageModel. |
| dw_kernel_size (`int`, *optional*, defaults to `None`): |
| Kernel size for depthwise convolutions. |
| layer_scale (`float`, *optional*, defaults to `None`): |
| Scale of the layers in the model. |
| offset_scale (`float`, *optional*, defaults to `1.0`): |
| Offset scale in the model. |
| mlp_ratio (`float`, *optional*, defaults to `4.0`): |
| Ratio of mlp layers in the InternImageModel. |
| post_norm (`bool`, *optional*, defaults to `False`): |
| Whether to use post normalization in the model. |
| level2_post_norm (`bool`, *optional*, defaults to `False`): |
| Whether to use level 2 post normalization. |
| level2_post_norm_block_ids (`list`, *optional*, defaults to `None`): |
| Specific block IDs for level 2 post normalization. |
| center_feature_scale (`bool`, *optional*, defaults to `False`): |
| Whether to apply center feature scaling. |
| use_clip_projector (`bool`, *optional*, defaults to `False`): |
| Whether to use CLIP projector. |
| remove_center (`bool`, *optional*, defaults to `False`): |
| Whether to remove center pixels in some operations. |
| num_classes (`int`, *optional*, defaults to `1000`): |
| Number of classes for the model output. |
| drop_rate (`float`, *optional*, defaults to `0.0`): |
| Dropout rate in the model. |
| drop_path_rate (`float`, *optional*, defaults to `0.0`): |
| Dropout path rate in the model. |
| drop_path_type (`str`, *optional*, defaults to `"linear"`): |
| Type of dropout path used in the model. |
| act_layer (`str`, *optional*, defaults to `"GELU"`): |
| Activation function used in the model. |
| norm_layer (`str`, *optional*, defaults to `"LN"`): |
| Normalization layer used in the model. |
| cls_scale (`float`, *optional*, defaults to `1.5`): |
| Scale of the classification layer in the model. |
| with_cp (`bool`, *optional*, defaults to `False`): |
| Whether to use checkpointing in the model. |
| """ |
| model_type = 'internimage' |
|
|
| def __init__( |
| self, |
| core_op='DCNv3', |
| depths=(4, 4, 18, 4), |
| groups=(4, 8, 16, 32), |
| channels=64, |
| dw_kernel_size=None, |
| layer_scale=None, |
| offset_scale=1.0, |
| mlp_ratio=4.0, |
| post_norm=False, |
| res_post_norm=False, |
| level2_post_norm=False, |
| level2_post_norm_block_ids=None, |
| center_feature_scale=False, |
| use_clip_projector=False, |
| remove_center=False, |
| num_classes=1000, |
| drop_rate=0.0, |
| drop_path_rate=0.0, |
| drop_path_type='linear', |
| act_layer='GELU', |
| norm_layer='LN', |
| cls_scale=1.5, |
| with_cp=False, |
| **kwargs, |
| ): |
| super().__init__(**kwargs) |
|
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| |
| self.core_op = core_op |
| self.depths = depths |
| self.groups = groups |
| self.channels = channels |
| self.dw_kernel_size = dw_kernel_size |
| self.layer_scale = layer_scale |
| self.offset_scale = offset_scale |
| self.mlp_ratio = mlp_ratio |
| self.post_norm = post_norm |
| self.res_post_norm = res_post_norm |
| self.level2_post_norm = level2_post_norm |
| self.level2_post_norm_block_ids = level2_post_norm_block_ids |
| self.center_feature_scale = center_feature_scale |
| self.use_clip_projector = use_clip_projector |
| self.remove_center = remove_center |
| self.num_classes = num_classes |
| self.drop_rate = drop_rate |
| self.drop_path_rate = drop_path_rate |
| self.drop_path_type = drop_path_type |
| self.act_layer = act_layer |
| self.norm_layer = norm_layer |
| self.cls_scale = cls_scale |
| self.with_cp = with_cp |
|
|
