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import torch
from transformers import PretrainedConfig
class FlashSTUConfig(PretrainedConfig):
model_type = "FlashSTU"
def __init__(
self,
bsz: int = 4,
n_embd: int = 2304,
n_heads: int = 9,
n_layers: int = 7,
seq_len: int = 8192,
window_size: int = 1024,
vocab_size: int = 200064,
mlp_scale: int = 12,
bias: bool = False,
dropout: float = 0.0,
num_eigh: int = 24,
use_hankel_L: bool = False,
use_flash_fft: bool = True,
use_approx: bool = True,
softcap: float = 50.0,
torch_dtype: torch.dtype = torch.bfloat16,
**kwargs,
):
super().__init__(**kwargs)
self.bsz = bsz
self.n_embd = n_embd
self.n_heads = n_heads
self.n_layers = n_layers
self.seq_len = seq_len
self.window_size = window_size
self.vocab_size = vocab_size
self.mlp_scale = mlp_scale
self.bias = bias
self.dropout = dropout
self.num_eigh = num_eigh
self.use_hankel_L = use_hankel_L
self.use_flash_fft = use_flash_fft
self.use_approx = use_approx
self.softcap = softcap
self.torch_dtype = torch_dtype
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