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Add optional path parameter to PyTorchNetwork #170

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Merged
henba1 merged 2 commits into from
Jan 13, 2026
Merged

Add optional path parameter to PyTorchNetwork #170

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0c5ed06
Add optional path parameter to PyTorchNetwork
henba1 Dec 8, 2025
5d466e3
Merge branch 'main' into henba1-patch-pytorch-network-path
henba1 Jan 12, 2026
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19 changes: 9 additions & 10 deletions ada_verona/database/machine_learning_model/pytorch_network.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

from pathlib import Path

import numpy as np
Expand All @@ -33,7 +32,7 @@ class PyTorchNetwork(Network):
input_shape (tuple[int]): Input shape of the model.
"""

def __init__(self, model: torch.nn.Module, input_shape: tuple[int], name: str) -> None:
def __init__(self, model: torch.nn.Module, input_shape: tuple[int], name: str, path: Path | None = None) -> None:
"""
Initialize the PyTorchNetwork with architecture and weights paths.

Expand All @@ -46,6 +45,7 @@ def __init__(self, model: torch.nn.Module, input_shape: tuple[int], name: str) -
self.model = model
self.input_shape = input_shape
self._name = name
self._path = path
self.torch_model_wrapper = None

@property
Expand All @@ -57,7 +57,7 @@ def name(self) -> str:
str: The name of the network.
"""
return self._name

@property
def path(self) -> Path:
"""
Expand All @@ -66,8 +66,8 @@ def path(self) -> Path:
Returns:
Path: The path of the network.
"""
return None
return self._path

def get_input_shape(self) -> np.ndarray:
"""
Get the input shape of the PyTorch model.
Expand All @@ -89,14 +89,13 @@ def load_pytorch_model(self) -> torch.nn.Module:
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = self.model.to(device)
model.eval()

self.torch_model_wrapper = TorchModelWrapper(model, self.get_input_shape())

return self.torch_model_wrapper


def to_dict(self):
raise NotImplementedError("PytorchNetwork does not support to_dict() function currently.")

def from_dict(cls, data: dict):
raise NotImplementedError("PytorchNetwork does not support from_dict() function currently.")
raise NotImplementedError("PytorchNetwork does not support from_dict() function currently.")