formatting

sae_analysis/dashboard_runner.py

@@ -18,10 +18,10 @@
 import plotly
 import plotly.express as px
 import torch
-import wandb
 from torch.nn.functional import cosine_similarity
 from tqdm import tqdm
 
+import wandb
 from sae_analysis.visualizer.data_fns import get_feature_data
 from sae_training.utils import LMSparseAutoencoderSessionloader
 

sae_training/config.py

@@ -3,6 +3,7 @@
 from typing import Any, Optional, cast
 
 import torch
+
 import wandb
 
 

sae_training/evals.py

@@ -3,11 +3,11 @@
 
 import pandas as pd
 import torch
-import wandb
 from tqdm import tqdm
 from transformer_lens import HookedTransformer
 from transformer_lens.utils import get_act_name
 
+import wandb
 from sae_training.activations_store import ActivationsStore
 from sae_training.sparse_autoencoder import SparseAutoencoder
 

sae_training/lm_runner.py

@@ -1,7 +1,6 @@
 from typing import Any, cast
 
 import wandb
-
 from sae_training.config import LanguageModelSAERunnerConfig
 
 # from sae_training.activation_store import ActivationStore

sae_training/toy_model_runner.py

@@ -3,8 +3,8 @@
 
 import einops
 import torch
-import wandb
 
+import wandb
 from sae_training.sparse_autoencoder import SparseAutoencoder
 from sae_training.toy_models import Config as ToyConfig
 from sae_training.toy_models import Model as ToyModel

sae_training/train_sae_on_language_model.py

@@ -1,11 +1,11 @@
 from typing import Any, cast
 
 import torch
-import wandb
 from torch.optim import Adam
 from tqdm import tqdm
 from transformer_lens import HookedTransformer
 
+import wandb
 from sae_training.activations_store import ActivationsStore
 from sae_training.evals import run_evals
 from sae_training.geom_median.src.geom_median.torch import compute_geometric_median

sae_training/train_sae_on_toy_model.py

@@ -1,10 +1,10 @@
 from typing import Any, cast
 
 import torch
-import wandb
 from torch.utils.data import DataLoader
 from tqdm import tqdm
 
+import wandb
 from sae_training.sparse_autoencoder import SparseAutoencoder
 
 

scripts/generate_dashboards.py

@@ -17,10 +17,10 @@
 import plotly
 import plotly.express as px
 import torch
-import wandb
 from torch.nn.functional import cosine_similarity
 from tqdm import tqdm
 
+import wandb
 from sae_analysis.visualizer.data_fns import get_feature_data
 from sae_training.utils import LMSparseAutoencoderSessionloader