fix rendering part 2

pina/solver/physic_informed_solver/competitive_pinn.py

@@ -46,8 +46,8 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
     .. seealso::
 
         **Original reference**: Zeng, Qi, et al.
-        "Competitive physics informed networks." International Conference on
-        Learning Representations, ICLR 2022
+        *Competitive physics informed networks.*
+        International Conference on Learning Representations, ICLR 2022
         `OpenReview Preprint <https://openreview.net/forum?id=z9SIj-IM7tn>`_.
     """
 
@@ -72,21 +72,23 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
             If `None`, the discriminator is a deepcopy of the ``model``.
             Default is ``None``.
         :param torch.optim.Optimizer optimizer_model: The optimizer of the
-            ``model``. If `None`, the Adam optimizer is used.
-            Default is ``None``.
+            ``model``. If `None`, the :class:`torch.optim.Adam` optimizer is
+            used. Default is ``None``.
         :param torch.optim.Optimizer optimizer_discriminator: The optimizer of
-            the ``discriminator``. If `None`, the Adam optimizer is used.
-            Default is ``None``.
-        :param torch.optim.LRScheduler scheduler_model: Learning rate scheduler
-            for the ``model``. If `None`, the constant learning rate scheduler
-            is used. Default is ``None``.
-        :param torch.optim.LRScheduler scheduler_discriminator: Learning rate
-            scheduler for the ``discriminator``. If `None`, the constant
-            learning rate scheduler is used. Default is ``None``.
+            the ``discriminator``. If `None`, the :class:`torch.optim.Adam`
+            optimizer is used. Default is ``None``.
+        :param Scheduler scheduler_model: Learning rate scheduler for the
+            ``model``.
+            If `None`, the :class:`torch.optim.lr_scheduler.ConstantLR`
+            scheduler is used. Default is ``None``.
+        :param Scheduler scheduler_discriminator: Learning rate scheduler for
+            the ``discriminator``.
+            If `None`, the :class:`torch.optim.lr_scheduler.ConstantLR`
+            scheduler is used. Default is ``None``.
         :param WeightingInterface weighting: The weighting schema to be used.
             If `None`, no weighting schema is used. Default is ``None``.
         :param torch.nn.Module loss: The loss function to be minimized.
-            If `None`, the Mean Squared Error (MSE) loss is used.
+            If `None`, the :class:`torch.nn.MSELoss` loss is used.
             Default is `None`.
         """
         if discriminator is None:
@@ -118,7 +120,8 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
         """
         Solver training step, overridden to perform manual optimization.
 
-        :param dict batch: The batch element in the dataloader.
+        :param list[tuple[str, dict]] batch: A batch of data. Each element is a
+            tuple containing a condition name and a dictionary of points.
         :return: The aggregated loss.
         :rtype: LabelTensor
         """
@@ -163,7 +166,7 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
         Optimizer configuration.
 
         :return: The optimizers and the schedulers
-        :rtype: tuple(list, list)
+        :rtype: tuple[list[Optimizer], list[Scheduler]]
         """
         # If the problem is an InverseProblem, add the unknown parameters
         # to the parameters to be optimized
@@ -198,7 +201,8 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
 
         :param torch.Tensor outputs: The ``model``'s output for the current
             batch.
-        :param dict batch: The current batch of data.
+        :param list[tuple[str, dict]] batch: A batch of data. Each element is a
+            tuple containing a condition name and a dictionary of points.
         :param int batch_idx: The index of the current batch.
         """
         # increase by one the counter of optimization to save loggers
@@ -234,7 +238,7 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
         The optimizer associated to the model.
 
         :return: The optimizer for the model.
-        :rtype: torch.optim.Optimizer
+        :rtype: Optimizer
         """
         return self.optimizers[0]
 
@@ -244,7 +248,7 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
         The optimizer associated to the discriminator.
 
         :return: The optimizer for the discriminator.
-        :rtype: torch.optim.Optimizer
+        :rtype: Optimizer
         """
         return self.optimizers[1]
 
@@ -254,7 +258,7 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
         The scheduler associated to the model.
 
         :return: The scheduler for the model.
-        :rtype: torch.optim.lr_scheduler._LRScheduler
+        :rtype: Scheduler
         """
         return self.schedulers[0]
 
@@ -264,6 +268,6 @@ class CompetitivePINN(PINNInterface, MultiSolverInterface):
         The scheduler associated to the discriminator.
 
         :return: The scheduler for the discriminator.
-        :rtype: torch.optim.lr_scheduler._LRScheduler
+        :rtype: Scheduler
         """
         return self.schedulers[1]