feat: add mamba and dynamic chunking related code and test code

scripts/long_term_forecast/xPatch_SparseChannel_all.sh

@@ -0,0 +1,77 @@
+#!/bin/bash
+
+model_name=xPatch_SparseChannel
+
+# ECL dataset
+for pred_len in 96 192 336 720
+do
+python -u run.py \
+  --task_name long_term_forecast \
+  --is_training 1 \
+  --root_path ./dataset/electricity/ \
+  --data_path electricity.csv \
+  --model_id ECL_$pred_len'_'$pred_len \
+  --model $model_name \
+  --data custom \
+  --features M \
+  --seq_len 96 \
+  --label_len 48 \
+  --pred_len $pred_len \
+  --e_layers 2 \
+  --d_layers 1 \
+  --enc_in 321 \
+  --batch_size 512 \
+  --learning_rate 0.001 \
+  --use_multi_gpu True \
+  --lradj 'sigmoid' \
+  --train_epochs 50 \
+  --patience 5 \
+  --c_out 321 \
+  --d_model 128 \
+  --d_ff 256 \
+  --n_heads 16 \
+  --patch_len 16 \
+  --stride 8 \
+  --k_graph 8 \
+  --dropout 0.1 \
+  --revin 1 \
+  --des 'Exp' \
+  --itr 1
+done
+
+# Traffic dataset
+for pred_len in 96 192 336 720
+do
+python -u run.py \
+  --task_name long_term_forecast \
+  --is_training 1 \
+  --root_path ./dataset/traffic/ \
+  --data_path traffic.csv \
+  --model_id traffic_$pred_len'_'$pred_len \
+  --model $model_name \
+  --data custom \
+  --features M \
+  --seq_len 96 \
+  --label_len 48 \
+  --pred_len $pred_len \
+  --e_layers 2 \
+  --d_layers 1 \
+  --enc_in 862 \
+  --batch_size 256 \
+  --learning_rate 0.0005 \
+  --use_multi_gpu True \
+  --lradj 'sigmoid' \
+  --train_epochs 50 \
+  --patience 5 \
+  --c_out 862 \
+  --d_model 128 \
+  --d_ff 256 \
+  --n_heads 16 \
+  --patch_len 16 \
+  --stride 8 \
+  --k_graph 8 \
+  --dropout 0.1 \
+  --revin 1 \
+  --des 'Exp' \
+  --itr 1
+done