Normalisation fix

.gitignore

@@ -1,4 +1,30 @@
+# macOS
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
 
+# Windows
+Thumbs.db
+ehthumbs.db
+Desktop.ini
+
+# IDE files
+.vscode/
+.idea/
+*.swp
+*.swo
+
+# Temporary files
+*.tmp
+*.temp
+*~
+
+# Logs
+*.log
 __pycache__/
 .ipynb_checkpoints/
 .pytest_cache/
@@ -13,3 +39,42 @@ runs/
 checkpoints/
 tutorials/saved_models/
 
+venv/
+venv/
+cap/venv
+.DS_Store
+.vscode/
+
+saved_models/*.pth# ignore locally built venv
+venv/
+# ignore raw data dumps
+dataset/electricity/*.csv
+dataset/traffic/*.csv
+
+# ignore local venv
+venv/
+
+# ignore raw data dumps
+dataset/electricity/*.csv
+dataset/traffic/*.csv
+
+# local Python env
+venv/
+
+# raw data (too big for GitHub)
+dataset/electricity/*.csv
+dataset/traffic/*.csv
+
+# local Python env
+venv/
+
+# raw data (too big)
+dataset/electricity/*.csv
+dataset/traffic/*.csv
+
+# local Python env
+venv/
+
+# raw data (too big)
+dataset/electricity/*.csv
+dataset/traffic/*.csv

cap/__main__.py

@@ -58,7 +58,7 @@ def main():
 
             # Get model dimensions from data
             sample_batch = next(iter(train_loader))
-            if args.model in ['lstm', 'transformer']:
+            if args.model in ['lstm', 'transformer', 'timesnet']:
                 input_dim = sample_batch[0].shape[-1]
                 output_dim = sample_batch[1].shape[-1]
                 seq_len = sample_batch[0].shape[1]

cap/configs/autoformer.yaml

@@ -0,0 +1,21 @@
+dataset:
+  path: "dataset/ETT-small/ETTm2.csv"
+  batch_size: 32
+  train_size: 0.8
+  valid_size: 0.1
+  test_size: 0.1
+  normalization: true
+
+model:
+  type: "autoformer"
+  hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
+  num_layers: 2
+  dropout: 0.1
+
+training:
+  epochs: 30
+  learning_rate: 0.0001
+  patience: 5
+  device: "cuda"

cap/configs/autoformer_copy.yaml

@@ -0,0 +1,21 @@
+dataset:
+  path: "dataset/exchange_rate/exchange_rate.csv"
+  batch_size: 32
+  train_size: 0.8
+  valid_size: 0.1
+  test_size: 0.1
+  normalization: true
+
+model:
+  type: "autoformer"
+  hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
+  num_layers: 2
+  dropout: 0.1
+
+training:
+  epochs: 30
+  learning_rate: 0.0001
+  patience: 5
+  device: "cuda"

cap/configs/fedformer.yaml

@@ -0,0 +1,21 @@
+dataset:
+  path: "dataset/ETT-small/ETTm1.csv"
+  batch_size: 32
+  train_size: 0.8
+  valid_size: 0.1
+  test_size: 0.1
+  normalization: true
+
+model:
+  type: "fedformer"
+  hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
+  num_layers: 2
+  dropout: 0.1
+
+training:
+  epochs: 30
+  learning_rate: 0.0001
+  patience: 5
+  device: "cuda"

cap/configs/informer.yaml

@@ -0,0 +1,21 @@
+dataset:
+  path: "dataset/ETT-small/ETTm2.csv"
+  batch_size: 32
+  train_size: 0.8
+  valid_size: 0.1
+  test_size: 0.1
+  normalization: true
+
+model:
+  type: "informer"
+  hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
+  num_layers: 2
+  dropout: 0.1
+
+training:
+  epochs: 30
+  learning_rate: 0.0001
+  patience: 5
+  device: "cuda"

cap/configs/informer_copy.yaml

@@ -0,0 +1,21 @@
+dataset:
+  path: "dataset/exchange_rate/exchange_rate.csv"
+  batch_size: 32
+  train_size: 0.8
+  valid_size: 0.1
+  test_size: 0.1
+  normalization: true
+
+model:
+  type: "informer"
+  hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
+  num_layers: 2
+  dropout: 0.1
+
+training:
+  epochs: 30
+  learning_rate: 0.0001
+  patience: 5
+  device: "cuda"

cap/configs/config_bird1.yaml → cap/configs/lstm.yaml

@@ -1,18 +1,21 @@
 dataset:
-  path: "/home/yeqchen/cap/CAP/dataset/BirdMigration/bird_2.txt"
+  path: "dataset/ETT-small/ETTm1.csv"
   batch_size: 32
   train_size: 0.8
   valid_size: 0.1
   test_size: 0.1
+  normalization: true
 
 model:
   type: "lstm"
   hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
   num_layers: 2
   dropout: 0.1
 
 training:
-  epochs: 50
+  epochs: 30
   learning_rate: 0.5
   patience: 5
   device: "cuda"

cap/configs/config_et.yaml → cap/configs/timesnet.yaml

@@ -1,18 +1,21 @@
 dataset:
-  path: "cap/dataset/ElectricityTransformer/et_data.txt"
+  path: "dataset/ETT-small/ETTm1.csv"
   batch_size: 32
   train_size: 0.8
   valid_size: 0.1
   test_size: 0.1
+  normalization: true
 
 model:
-  type: "lstm"
+  type: "timesnet"
   hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
   num_layers: 2
   dropout: 0.1
 
 training:
-  epochs: 50
-  learning_rate: 0.001
+  epochs: 30
+  learning_rate: 0.1
   patience: 5
   device: "cuda"

cap/configs/config_bird2.yaml → cap/configs/transformer.yaml

@@ -1,18 +1,21 @@
 dataset:
-  path: "/home/yeqchen/cap/CAP/dataset/BirdMigration/bird_2.txt"
+  path: "dataset/ETT-small/ETTm1.csv"
   batch_size: 32
   train_size: 0.8
   valid_size: 0.1
   test_size: 0.1
+  normalization: true
 
 model:
   type: "transformer"
   hidden_dim: 128
+  seq_len: 96
+  pred_len: 96
   num_layers: 2
   dropout: 0.1
 
 training:
-  epochs: 50
+  epochs: 30
   learning_rate: 0.5
   patience: 5
   device: "cuda"