Revert .pylintrc and remove pylint disable

Author: FilippoOlivo

.pylintrc

@@ -250,9 +250,7 @@ single-line-if-stmt=no
 
 [BASIC]
 # Allow redefinition of input builtins
-# input needed in conditions and in solver
-# compile needed in Trainer
-allowed-redefined-builtins=input,compile
+allowed-redefined-builtins=input
 
 # Naming hint for argument names
 argument-name-hint=(([a-z][a-z0-9_]{2,30})|(_[a-z0-9_]*))$
@@ -377,10 +375,7 @@ known-third-party=enchant
 [DESIGN]
 
 # Maximum number of arguments for function / method
-max-args=15
-
-# Maximum nmber of positional arguments (R0917)
-max-positional-arguments=15
+max-args=10
 
 # Maximum number of attributes for a class (see R0902).
 max-attributes=15
@@ -395,7 +390,7 @@ max-branches=12
 max-locals=15
 
 # Maximum number of parents for a class (see R0901).
-max-parents=12
+max-parents=7
 
 # Maximum number of public methods for a class (see R0904).
 max-public-methods=20

pina/data/data_module.py

@@ -423,9 +423,6 @@ def test_dataloader(self):
         return self._create_dataloader("test", self.test_dataset)
 
     @staticmethod
-    # Unavoidable pylint error (we need to keep the same signature as the
-    # parent)
-    # pylint: disable=W0613
     def _transfer_batch_to_device_dummy(batch, device, dataloader_idx):
         return batch
 

pina/domain/ellipsoid.py

@@ -190,7 +190,6 @@ def _sample_range(self, n, mode, variables):
 
             # step 1.
             pts = torch.randn(size=(n, dim))
-            # pylint: disable=E1102
             pts = pts / torch.linalg.norm(pts, axis=-1).view((n, 1))
             if not self._sample_surface:  # step 2.
                 scale = torch.rand((n, 1))

pina/domain/simplex.py

@@ -135,7 +135,7 @@ def is_inside(self, point, check_border=False):
 
         # compute barycentric coordinates
 
-        lambda_ = torch.linalg.solve(  # pylint: disable=E1102
+        lambda_ = torch.linalg.solve(
             self._vectors_shifted * 1.0, point_shift * 1.0
         )
         lambda_1 = 1.0 - torch.sum(lambda_)

pina/equation/equation_factory.py

@@ -23,9 +23,6 @@ def __init__(self, value, components=None):
             Default is ``None``.
         """
 
-        # input_ is not used but it is necessary to keep the signature for
-        # consistency
-        # pylint: disable=W0613
         def equation(input_, output_):
             if components is None:
                 return output_ - value

pina/graph.py

@@ -242,10 +242,6 @@ def _build_edge_attr(pos, edge_index):
         )
 
 
-# Avoid signature-differs error. This is a wanted behavior of the overriden
-# classes since KNNGraph and RadiusGraph creates edge_index based on radius
-# and k-nearest neighbors respectively.
-# pylint: disable=signature-differs
 class RadiusGraph(GraphBuilder):
     """
     A class to build a radius graph.

pina/label_tensor.py

@@ -5,9 +5,6 @@
 from torch import Tensor
 
 
-# Avoid protected-access. We need to access the protected members of the
-# LabelTensor class to avoid repeated checking.
-# pylint: disable=protected-access
 class LabelTensor(torch.Tensor):
     """Torch tensor with a label for any column."""
 
@@ -39,9 +36,6 @@ def __init__(self, x, labels):
                     {1: {"name": "space"['a', 'b', 'c'])
 
         """
-        # Avoid unused argument warning. x is not used in the constructor
-        # of the parent class.
-        # pylint: disable=unused-argument
         super().__init__()
         if labels is not None:
             self.labels = labels

pina/loss/lp_loss.py

@@ -6,8 +6,6 @@
 from .loss_interface import LossInterface
 
 
-# Avoid pylint warning for torch.linalg.norm (it is callable)
-# pylint: disable=not-callable
 class LpLoss(LossInterface):
     r"""
     The Lp loss implementation class. Creates a criterion that measures

pina/model/block/convolution_2d.py

@@ -379,8 +379,6 @@ def forward(self, X):
             ).sum(1)
         return conv
 
-    # Avoid too many arguments warning
-    # pylint: disable=R0914
     def transpose_no_overlap(self, integrals, X):
         """
         Transpose pass in the layer for no-overlapping filters

pina/model/block/gno_block.py

@@ -28,9 +28,7 @@ def __init__(
         :param edges_features: Number of edge features.
         :param n_layers: Number of layers in edge transformation MLP.
         """
-        # Avoid circular import. I need to import FeedForward here
-        # to avoid circular import with FeedForward itself.
-        # pylint: disable=import-outside-toplevel
+
         from ...model.feed_forward import FeedForward
 
         super().__init__(aggr="mean")  # Uses PyG's default aggregation