diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index 99e60ca..c53f15e 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -66,7 +66,7 @@ jobs:
           commit_message: 'docs: deploy documentation from ${{ github.sha }}'
 
       - name: Upload build artifacts
-        if: github.event_name == 'pull_request'
+        if: (github.event_name == 'push' || github.event_name == 'workflow_dispatch') && github.ref == 'refs/heads/main'
         uses: actions/upload-artifact@v4
         with:
           name: documentation
diff --git a/dynvision/base/__init__.py b/dynvision/base/__init__.py
index c3c05c7..226595b 100644
--- a/dynvision/base/__init__.py
+++ b/dynvision/base/__init__.py
@@ -183,10 +183,6 @@ def setup(self, stage=None) -> None:
 class CoreModel(TemporalBase, DtypeDeviceCoordinatorMixin):
     """Core neural network functionality with device coordination only."""
 
-    pass
-
 
 class MonitoredModel(TemporalBase, MonitoringMixin, DtypeDeviceCoordinatorMixin):
     """Core neural network with monitoring, but no Lightning integration."""
-
-    pass
diff --git a/dynvision/base/coordination.py b/dynvision/base/coordination.py
index 701e79a..4b1ea4f 100644
--- a/dynvision/base/coordination.py
+++ b/dynvision/base/coordination.py
@@ -144,7 +144,6 @@ def _determine_dtype_from_parameters(self) -> torch.dtype:
                 logger.warning(
                     f"Error determining dtype from parameters: {e}. Defaulting to torch.float16."
                 )
-                pass
         return torch.float16
 
     def create_aligned_tensor(self, *args, **kwargs) -> torch.Tensor:
diff --git a/dynvision/base/storage.py b/dynvision/base/storage.py
index f4e41cc..df7ee20 100644
--- a/dynvision/base/storage.py
+++ b/dynvision/base/storage.py
@@ -37,7 +37,6 @@ def get_storage_index(
 
     def reset(self, input_shape: Optional[Tuple[int, ...]] = None) -> None:
         """Reset strategy state."""
-        pass
 
 
 class CyclicStrategy(SamplingStrategy):
diff --git a/dynvision/base/temporal.py b/dynvision/base/temporal.py
index 047e54a..35cebfc 100644
--- a/dynvision/base/temporal.py
+++ b/dynvision/base/temporal.py
@@ -218,7 +218,6 @@ def verify_initialization(self) -> None:
 
     def reset(self, input_shape: Optional[Tuple[int, ...]] = None) -> None:
         """Reset the model state, in particular hidden states."""
-        pass
 
     def compute_idle_initial_states(
         self, batch_size: int, device: torch.device, dtype: torch.dtype
@@ -400,7 +399,6 @@ def _forward(
 
                 else:
                     logger.debug(f"No {operation} defined for {layer_name}. Skipping.")
-                    pass
 
                 # if isinstance(x, torch.Tensor) and (~torch.isfinite(x)).any():
                 #     logger.warning(
diff --git a/dynvision/data/dataloader.py b/dynvision/data/dataloader.py
index 8f37700..ddf002d 100644
--- a/dynvision/data/dataloader.py
+++ b/dynvision/data/dataloader.py
@@ -13,7 +13,7 @@
 """
 
 import logging
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Optional, Tuple
 from collections import OrderedDict
 import torch
 import torch.jit
diff --git a/dynvision/data/datasets.py b/dynvision/data/datasets.py
index c1c4aa0..771ce8b 100644
--- a/dynvision/data/datasets.py
+++ b/dynvision/data/datasets.py
@@ -22,7 +22,7 @@
 from concurrent.futures import ThreadPoolExecutor
 from functools import lru_cache
 from pathlib import Path
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union, cast
+from typing import Any, Callable, List, Optional, Tuple
 import torchvision as tv
 import torch
 from torch.utils.data import Dataset
diff --git a/dynvision/data/ffcv_dataloader.py b/dynvision/data/ffcv_dataloader.py
index 3c40ee4..bc24eec 100644
--- a/dynvision/data/ffcv_dataloader.py
+++ b/dynvision/data/ffcv_dataloader.py
@@ -1,6 +1,6 @@
 import logging
 from pathlib import Path
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Callable, List, Optional, Tuple, Union
 from .ffcv_operations import ExtendDataTimeFFCV, ExtendLabelTimeFFCV
 import torch
 import torch.distributed
@@ -10,7 +10,6 @@
     IntDecoder,
     NDArrayDecoder,
     RandomResizedCropRGBImageDecoder,
-    SimpleRGBImageDecoder,
 )
 from ffcv.loader import Loader, OrderOption
 from ffcv.pipeline.operation import Operation
@@ -20,7 +19,6 @@
     ToTensor,
     ToTorchImage,
     NormalizeImage,
-    RandomResizedCrop,
 )
 
 from dynvision.data.transforms import get_data_transform, get_target_transform
diff --git a/dynvision/data/ffcv_datasets.py b/dynvision/data/ffcv_datasets.py
index a829d68..42bd237 100644
--- a/dynvision/data/ffcv_datasets.py
+++ b/dynvision/data/ffcv_datasets.py
@@ -78,7 +78,7 @@ def main() -> None:
     )
 
     # Get writer configuration
-    data_sample = dataset[0][0]
+    dataset[0][0]
 
     image_writer = RGBImageField(
         write_mode=config.writer_mode,
diff --git a/dynvision/data/noise.py b/dynvision/data/noise.py
index 93e5c89..045dc2b 100644
--- a/dynvision/data/noise.py
+++ b/dynvision/data/noise.py
@@ -26,9 +26,8 @@ def __getitem__(self, idx):
 import torch.nn.functional as F
 import numpy as np
 from typing import Optional, Union, Tuple, Callable
-import warnings
 import logging
-from dynvision.utils import str_to_bool, alias_kwargs, filter_kwargs
+from dynvision.utils import str_to_bool, alias_kwargs
 
 logger = logging.getLogger(__name__)
 
diff --git a/dynvision/model_components/layer_connections.py b/dynvision/model_components/layer_connections.py
index 47d16f6..67350da 100644
--- a/dynvision/model_components/layer_connections.py
+++ b/dynvision/model_components/layer_connections.py
@@ -251,16 +251,12 @@ class Skip(ConnectionBase):
     The skip connection module adds the input tensor (x) of an earlier layer to the output tensor (h) of a deeper layer.
     """
 
-    pass
-
 
 class Feedback(ConnectionBase):
     """
     The feedback connection module adds a hidden state (h) of a deeper layer to the input tensor (x) of an earlier layer.
     """
 
-    pass
-
 
 if __name__ == "__main__":
     input_shape = (3, 32, 32)
diff --git a/dynvision/model_components/recurrence.py b/dynvision/model_components/recurrence.py
index a28a273..9a7f620 100644
--- a/dynvision/model_components/recurrence.py
+++ b/dynvision/model_components/recurrence.py
@@ -405,8 +405,6 @@ class DepthPointwiseConnection(DepthwiseSeparableConnection):
     Implements a depth-pointwise convolution connection.
     """
 
-    pass
-
 
 class PointDepthwiseConnection(DepthwiseSeparableConnection):
     """
diff --git a/dynvision/models/__init__.py b/dynvision/models/__init__.py
index 94ba560..e69de29 100644
--- a/dynvision/models/__init__.py
+++ b/dynvision/models/__init__.py
@@ -1,6 +0,0 @@
-from .alexnet import *
-from .cordsnet import *
-from .cornet_rt import *
-from .dyrcnn import *
-from .resnet import *
-from .resnetx3 import *
diff --git a/dynvision/models/alexnet.py b/dynvision/models/alexnet.py
index a34af15..eb80a4b 100644
--- a/dynvision/models/alexnet.py
+++ b/dynvision/models/alexnet.py
@@ -6,7 +6,6 @@
 from dynvision.base import BaseModel
 from typing import Optional, Tuple
 from dynvision.model_components import (
-    InputAdaption,
     RecurrentConnectedConv2d,
 )
 
diff --git a/dynvision/models/cordsnet.py b/dynvision/models/cordsnet.py
index 1656372..286b2e2 100644
--- a/dynvision/models/cordsnet.py
+++ b/dynvision/models/cordsnet.py
@@ -282,7 +282,6 @@ def _define_architecture(self) -> None:
 
         # Configuration arrays
         channels = [64, 64, 64, 128, 128, 256, 256, 512, 512]
-        sizes = [56, 56, 28, 28, 14, 14, 7, 7]
         strides = [1, 1, 2, 1, 2, 1, 2, 1]
 
         # Layer 0: Input processing (no recurrence, no bias)
diff --git a/dynvision/models/cornet_rt.py b/dynvision/models/cornet_rt.py
index a204b2d..9b92e63 100644
--- a/dynvision/models/cornet_rt.py
+++ b/dynvision/models/cornet_rt.py
@@ -9,18 +9,15 @@
 """
 
 import logging
-from typing import Optional, Dict, Any, Tuple, Union, List
+from typing import Optional, Any, Tuple
 
 import torch
 import torch.nn as nn
-from torch.utils import model_zoo
 
 from dynvision.models.dyrcnn import DyRCNN
 from dynvision.utils import alias_kwargs, str_to_bool
 from dynvision.model_components import (
-    InputAdaption,
     RConv2d,
-    Skip,
 )
 
 
@@ -31,8 +28,6 @@ class ZeroStateSentinel:
     Operations check isinstance and treat it as additive identity.
     """
 
-    pass
-
 
 __all__ = ["CorNetRT"]
 
diff --git a/dynvision/models/dyrcnn.py b/dynvision/models/dyrcnn.py
index 3b961d9..4c3c510 100644
--- a/dynvision/models/dyrcnn.py
+++ b/dynvision/models/dyrcnn.py
@@ -15,7 +15,7 @@
 """
 
 import logging
-from typing import Optional, Union, Dict, Any, List, Tuple
+from typing import Optional, Union, Any, List, Tuple
 
 import torch
 import torch.nn as nn
diff --git a/dynvision/models/resnet.py b/dynvision/models/resnet.py
index 43c9683..c70afca 100644
--- a/dynvision/models/resnet.py
+++ b/dynvision/models/resnet.py
@@ -207,7 +207,6 @@ def forward(
 
     def reset(self, input_shape: Optional[Tuple[int, ...]] = None) -> None:
         """Reset model state."""
-        pass
 
     def _determine_residual_timesteps(self, **kwargs) -> int:
         """Determine residual timesteps (none for ResNet)."""