| from typing import Any | |
| from transformers.configuration_utils import PretrainedConfig | |
| __all__ = ["AIMv2Config"] | |
| class AIMv2Config(PretrainedConfig): | |
| """This is the configuration class to store the configuration of an [`AIMv2Model`]. | |
| Instantiating a configuration with the defaults will yield a similar configuration | |
| to that of the [apple/aimv2-large-patch14-224](https://huggingface.co/apple/aimv2-large-patch14-224). | |
| Args: | |
| hidden_size: Dimension of the hidden representations. | |
| intermediate_size: Dimension of the SwiGLU representations. | |
| num_hidden_layers: Number of hidden layers in the Transformer. | |
| num_attention_heads: Number of attention heads for each attention layer | |
| in the Transformer. | |
| num_channels: Number of input channels. | |
| image_size: Image size. | |
| patch_size: Patch size. | |
| rms_norm_eps: Epsilon value used for the RMS normalization layer. | |
| attention_dropout: Dropout ratio for attention probabilities. | |
| projection_dropout: Dropout ratio for the projection layer after the attention. | |
| qkv_bias: Whether to add a bias to the queries, keys and values. | |
| use_bias: Whether to add a bias in the feed-forward and projection layers. | |
| kwargs: Keyword arguments for the [`PretrainedConfig`]. | |
| """ | |
| model_type: str = "aimv2" | |
| def __init__( | |
| self, | |
| hidden_size: int = 1024, | |
| intermediate_size: int = 2816, | |
| num_hidden_layers: int = 24, | |
| num_attention_heads: int = 8, | |
| num_channels: int = 3, | |
| image_size: int = 224, | |
| patch_size: int = 14, | |
| rms_norm_eps: float = 1e-5, | |
| attention_dropout: float = 0.0, | |
| projection_dropout: float = 0.0, | |
| qkv_bias: bool = False, | |
| use_bias: bool = False, | |
| **kwargs: Any, | |
| ): | |
| super().__init__(**kwargs) | |
| 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.image_size = image_size | |
| self.attention_dropout = attention_dropout | |
| self.rms_norm_eps = rms_norm_eps | |
| self.projection_dropout = projection_dropout | |
| self.qkv_bias = qkv_bias | |
| self.use_bias = use_bias | |