64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
# copied from https://huggingface.co/apple/aimv2-huge-patch14-448
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from typing import Any
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from transformers.configuration_utils import PretrainedConfig
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__all__ = ["AIMv2Config"]
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class AIMv2Config(PretrainedConfig):
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"""This is the configuration class to store the configuration of an [`AIMv2Model`].
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Instantiating a configuration with the defaults will yield a similar configuration
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to that of the [apple/aimv2-large-patch14-224](https://huggingface.co/apple/aimv2-large-patch14-224).
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Args:
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hidden_size: Dimension of the hidden representations.
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intermediate_size: Dimension of the SwiGLU representations.
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num_hidden_layers: Number of hidden layers in the Transformer.
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num_attention_heads: Number of attention heads for each attention layer
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in the Transformer.
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num_channels: Number of input channels.
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image_size: Image size.
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patch_size: Patch size.
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rms_norm_eps: Epsilon value used for the RMS normalization layer.
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attention_dropout: Dropout ratio for attention probabilities.
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projection_dropout: Dropout ratio for the projection layer after the attention.
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qkv_bias: Whether to add a bias to the queries, keys and values.
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use_bias: Whether to add a bias in the feed-forward and projection layers.
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kwargs: Keyword arguments for the [`PretrainedConfig`].
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"""
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model_type: str = "aimv2"
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def __init__(
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self,
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hidden_size: int = 1024,
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intermediate_size: int = 2816,
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num_hidden_layers: int = 24,
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num_attention_heads: int = 8,
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num_channels: int = 3,
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image_size: int = 224,
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patch_size: int = 14,
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rms_norm_eps: float = 1e-5,
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attention_dropout: float = 0.0,
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projection_dropout: float = 0.0,
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qkv_bias: bool = False,
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use_bias: bool = False,
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**kwargs: Any,
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):
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super().__init__(**kwargs)
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self.hidden_size = hidden_size
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self.intermediate_size = intermediate_size
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self.num_hidden_layers = num_hidden_layers
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self.num_attention_heads = num_attention_heads
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self.num_channels = num_channels
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self.patch_size = patch_size
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self.image_size = image_size
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self.attention_dropout = attention_dropout
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self.rms_norm_eps = rms_norm_eps
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self.projection_dropout = projection_dropout
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self.qkv_bias = qkv_bias
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self.use_bias = use_bias
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