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from typing import List
from transformers import PretrainedConfig
class SundialConfig(PretrainedConfig):
model_type = "sundial"
keys_to_ignore_at_inference = ["past_key_values"]
def __init__(
self,
input_token_len: int = 16,
hidden_size: int = 768,
intermediate_size: int = 3072,
output_token_lens: List[int] = [720],
num_hidden_layers: int = 12,
num_attention_heads: int = 12,
hidden_act: str = "silu",
use_cache: bool = True,
rope_theta: int = 10000,
dropout_rate: float = 0.1,
initializer_range: float = 0.02,
max_position_embeddings: int = 10000,
flow_loss_depth: int = 3,
num_sampling_steps: int = 50,
diffusion_batch_mul: int = 4,
**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.dropout_rate = dropout_rate
self.initializer_range = initializer_range
self.max_position_embeddings = max_position_embeddings
self.flow_loss_depth = flow_loss_depth
self.num_sampling_steps = num_sampling_steps
self.diffusion_batch_mul = diffusion_batch_mul
super().__init__(
**kwargs,
)
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