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from typing import List
from transformers import PretrainedConfig
class TimerConfig(PretrainedConfig):
model_type = "timer"
keys_to_ignore_at_inference = ["past_key_values"]
def __init__(
self,
input_token_len: int = 1,
hidden_size: int = 1024,
intermediate_size: int = 2048,
output_token_lens: List[int] = [1, 8, 32, 64],
num_hidden_layers: int = 8,
num_attention_heads: int = 8,
hidden_act: str = "silu",
use_cache: bool = True,
rope_theta: int = 10000,
attention_dropout: float = 0.0,
initializer_range: float = 0.02,
max_position_embeddings: int = 10000,
**kwargs,
):
self.input_token_len = input_token_len
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.hidden_act = hidden_act
self.output_token_lens = output_token_lens
self.use_cache = use_cache
self.rope_theta = rope_theta
self.attention_dropout = attention_dropout
self.initializer_range = initializer_range
self.max_position_embeddings = max_position_embeddings
super().__init__(
**kwargs,
)
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