Update configuration_super_linear.py

configuration_super_linear.py

@@ -30,11 +30,31 @@ class SuperLinearConfig(PretrainedConfig):
         pred_len=96,
         inf_pred_len=96,
         max_horizon=96,
-        auto_regressive=1,
         moe_n_experts=8,
         top_k_experts=3,
         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,                          # any extra CLI args
     ):
         self.seq_len         = seq_len
@@ -46,10 +66,10 @@ class SuperLinearConfig(PretrainedConfig):
         self.moe_n_experts   = moe_n_experts
         self.top_k_experts   = top_k_experts
         self.freq_experts    = freq_experts
-        self.freeze_experts  = 1
-        self.layer_type      = "RLinear"
-        self.linear_checkpoints_path  = '/cs/azencot_fsas/MoE/'
-        self.linear_checkpoints_dir   = "checkpoints5"
+        self.freeze_experts  = freeze_experts
+        self.layer_type      = layer_type
+        self.linear_checkpoints_path  = linear_checkpoints_dir
+        self.linear_checkpoints_dir   = linear_checkpoints_dir
         self.load_linear              = load_linear 
         self.manual_moe              = manual_moe
         self.misc_moe                = misc_moe