chore: rename use_gpu to disable_gpu in TorchAlgo

Signed-off-by: ThibaultFy <[email protected]>

substrafl/algorithms/pytorch/torch_base_algo.py

@@ -46,7 +46,7 @@ def __init__(
         optimizer: Optional[torch.optim.Optimizer] = None,
         scheduler: Optional[torch.optim.lr_scheduler._LRScheduler] = None,
         seed: Optional[int] = None,
-        disable_gpu: bool = True,
+        disable_gpu: bool = False,
         *args,
         **kwargs,
     ):

substrafl/algorithms/pytorch/torch_fed_avg_algo.py

@@ -92,7 +92,7 @@ def __init__(
         scheduler: Optional[torch.optim.lr_scheduler._LRScheduler] = None,
         with_batch_norm_parameters: bool = False,
         seed: Optional[int] = None,
-        disable_gpu: bool = True,
+        disable_gpu: bool = False,
         *args,
         **kwargs,
     ):
@@ -125,7 +125,7 @@ def __init__(
             with_batch_norm_parameters (bool): Whether to include the batch norm layer parameters in the fed avg
                 strategy. Defaults to False.
             seed (typing.Optional[int]): Seed set at the algo initialization on each organization. Defaults to None.
-            disable_gpu (bool): Whether to use the GPUs if they are available. Defaults to True.
+            disable_gpu (bool): Force to disable GPUs usage. Defaults to False.
         """
         super().__init__(
             *args,

substrafl/algorithms/pytorch/torch_fed_pca_algo.py

@@ -87,7 +87,7 @@ def __init__(
         out_features: int,
         batch_size: Optional[int] = None,
         seed: int = 1,
-        disable_gpu: bool = True,
+        disable_gpu: bool = False,
         *args,
         **kwargs,
     ):
@@ -101,7 +101,7 @@ def __init__(
             out_features (int): dimension to keep after PCA
             batch_size (Optional[int]): mini-batch size
             seed (int): random generator seed. The seed is mandatory. Default to 1.
-            disable_gpu (bool): whether to use GPU or not. Default to True.
+            disable_gpu (bool): force to disable GPUs usage. Defaults to False.
         """
         self.in_features = in_features
         self.out_features = out_features

substrafl/algorithms/pytorch/torch_newton_raphson_algo.py

@@ -48,7 +48,7 @@ def __init__(
         l2_coeff: float = 0,
         with_batch_norm_parameters: bool = False,
         seed: Optional[int] = None,
-        disable_gpu: bool = True,
+        disable_gpu: bool = False,
         *args,
         **kwargs,
     ):
@@ -80,7 +80,7 @@ def __init__(
             with_batch_norm_parameters (bool): Whether to include the batch norm layer parameters in the Newton-Raphson
                 strategy. Defaults to False.
             seed (typing.Optional[int]): Seed set at the algo initialization on each organization. Defaults to None.
-            disable_gpu (bool): Whether to use the GPUs if they are available. Defaults to True.
+            disable_gpu (bool): Force to disable GPUs usage. Defaults to False.
         """
         assert "optimizer" not in kwargs, "Newton Raphson strategy does not uses optimizers"
 

substrafl/algorithms/pytorch/torch_scaffold_algo.py

@@ -118,7 +118,7 @@ def __init__(
         with_batch_norm_parameters: bool = False,
         c_update_rule: CUpdateRule = CUpdateRule.FAST,
         seed: Optional[int] = None,
-        disable_gpu: bool = True,
+        disable_gpu: bool = False,
         *args,
         **kwargs,
     ):
@@ -153,7 +153,7 @@ def __init__(
                 client control variate.
                 Defaults to CUpdateRule.FAST.
             seed (typing.Optional[int]): Seed set at the algo initialization on each organization. Defaults to None.
-            disable_gpu (bool): Whether to use the GPUs if they are available. Defaults to True.
+            disable_gpu (bool): Force to disable GPUs usage. Defaults to False.
         Raises:
             :ref:`~substrafl.exceptions.NumUpdatesValueError`: If `num_updates` is inferior or equal to zero.
         """

substrafl/algorithms/pytorch/torch_single_organization_algo.py

@@ -90,7 +90,7 @@ def __init__(
         dataset: torch.utils.data.Dataset,
         scheduler: Optional[torch.optim.lr_scheduler._LRScheduler] = None,
         seed: Optional[int] = None,
-        disable_gpu: bool = True,
+        disable_gpu: bool = False,
         *args,
         **kwargs,
     ):
@@ -121,7 +121,7 @@ def __init__(
             scheduler (torch.optim.lr_scheduler._LRScheduler, Optional): A torch scheduler that will be called at every
                 batch. If None, no scheduler will be used. Defaults to None.
             seed (typing.Optional[int]): Seed set at the algo initialization on each organization. Defaults to None.
-            disable_gpu (bool): Whether to use the GPUs if they are available. Defaults to True.
+            disable_gpu (bool): Force to disable GPUs usage. Defaults to False.
         """
         super().__init__(
             *args,

tests/algorithms/pytorch/test_base_algo.py

@@ -201,9 +201,9 @@ def __init__(self):
                     disable_gpu=disable_gpu,
                 )
             if disable_gpu:
-                assert self._device == torch.device("cuda")
-            else:
                 assert self._device == torch.device("cpu")
+            else:
+                assert self._device == torch.device("cuda")
 
         @property
         def strategies(self):