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scale_attn_by_inverse_layer_idx (`bool`, *optional*, defaults to `False`):
    Whether to additionally scale attention weights by `1 / layer_idx + 1`.
reorder_and_upcast_attn (`bool`, *optional*, defaults to `False`):
    Whether to scale keys (K) prior to computing attention (dot-product) and upcast attention
    dot-product/softmax to float() when training with mixed precision.

Example:

```python
>>> from transformers import ImageGPTConfig, ImageGPTModel

>>> # Initializing a ImageGPT configuration
>>> configuration = ImageGPTConfig()

>>> # Initializing a model (with random weights) from the configuration
>>> model = ImageGPTModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```imagegptpast_key_valuesn_embdn_positionsn_headn_layer)hidden_sizemax_position_embeddingsnum_attention_headsnum_hidden_layersi  
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