| from typing import Optional, Tuple |
| import torch, torch.nn as nn, torch.nn.functional as F |
|
|
| from transformers import ( |
| PretrainedConfig, |
| PreTrainedModel, |
| GenerationMixin, |
| AutoConfig, |
| AutoModelForCausalLM, |
| ) |
| from transformers.modeling_outputs import CausalLMOutputWithCrossAttentions |
|
|
| |
| |
| |
|
|
|
|
| class SuperLinearConfig(PretrainedConfig): |
| """ |
| Configuration for the SuperLinear MoE time–series foundation model. |
| Only *model_type* must be unique inside transformers; the rest mirrors |
| the __init__ arguments of your original Config object. |
| """ |
|
|
| model_type = "super_linear" |
|
|
| def __init__( |
| self, |
| seq_len=512, |
| pred_len=96, |
| inf_pred_len=96, |
| max_horizon=96, |
| moe_n_experts=8, |
| top_k_experts=5, |
| moe =1, |
| freq_experts='mean_naive_1/6_1/7_1/8_1/12_1/14_1/16_1/21_1/24_1/28_1/30_1/32_1/36_1/42_1/48_1/52_1/56_1/60_1/72_1/84_1/96_1/120_1/144_1/168_1/180_1/224_1/252_1/288_1/336_1/365_1/504_1/672_1/1008_1/1440_1/2016_1/3600', |
| auto_regressive= 1, |
| con= 0, |
| d_model= 128, |
| dropout= 0.0, |
| fft_len= 10000, |
| freeze_experts= 1, |
| ker_len= 50, |
| layer_type= "RLinear", |
| linear_checkpoints_dir= "checkpoints5", |
| linear_checkpoints_path= "/cs/azencot_fsas/MoE/", |
| load_linear = 1, |
| manual_moe = 0, |
| misc_moe = 1, |
| mlp_gating = 1, |
| model_type= "super_linear", |
| moe_temp = 1, |
| noisy_gating_std = 0.1, |
| noisy_gating_std_decay = 1, |
| torch_dtype = "float32", |
| transformers_version = "4.40.1", |
| use_fft = 1, |
| **kwargs, |
| ): |
| self.seq_len = seq_len |
| self.moe = moe |
| self.pred_len = pred_len |
| self.inf_pred_len = inf_pred_len |
| self.max_horizon = max_horizon |
| self.auto_regressive = auto_regressive |
| self.moe_n_experts = moe_n_experts |
| self.top_k_experts = top_k_experts |
| self.freq_experts = freq_experts |
| self.freeze_experts = freeze_experts |
| self.layer_type = layer_type |
| self.linear_checkpoints_path = linear_checkpoints_path |
| self.linear_checkpoints_dir = linear_checkpoints_dir |
| self.load_linear = load_linear |
| self.manual_moe = manual_moe |
| self.misc_moe = misc_moe |
| self.noisy_gating_std = noisy_gating_std |
| self.noisy_gating_std_decay = noisy_gating_std_decay |
| self.ker_len = ker_len |
| self.con = con |
| self.d_model = d_model |
| self.mlp_gating = mlp_gating |
| self.moe_temp = moe_temp |
| self.use_fft = use_fft |
| self.fft_len = fft_len |
| self.dropout = dropout |
| super().__init__(**kwargs) |
|
|
