[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

pylint_ml/checkers/tensorflow/tensor_parameter.py

@@ -16,25 +16,21 @@ class TensorFlowParameterChecker(BaseChecker):
         "W8111": (
             "Ensure that required parameters %s are explicitly specified in TensorFlow method %s.",
             "tensor-parameter",
-            "Explicitly specifying required parameters improves model performance and prevents unintended "
-            "behavior.",
+            "Explicitly specifying required parameters improves model performance and prevents unintended " "behavior.",
         ),
     }
 
     # Define required parameters for specific TensorFlow methods
     REQUIRED_PARAMS = {
         # Model Creation
-        'Sequential': ['layers'],  # Layers must be specified to build a model
-
+        "Sequential": ["layers"],  # Layers must be specified to build a model
         # Model Compilation
-        'compile': ['optimizer', 'loss'],  # Optimizer and loss function are essential for training
-
+        "compile": ["optimizer", "loss"],  # Optimizer and loss function are essential for training
         # Model Training
-        'fit': ['x', 'y'],  # Input data (x) and target data (y) are required to train the model
-
+        "fit": ["x", "y"],  # Input data (x) and target data (y) are required to train the model
         # Layers
-        'Conv2D': ['filters', 'kernel_size'],  # Filters and kernel size define the convolutional layer's structure
-        'Dense': ['units'],  # Number of units (neurons) is crucial for a Dense layer
+        "Conv2D": ["filters", "kernel_size"],  # Filters and kernel size define the convolutional layer's structure
+        "Dense": ["units"],  # Number of units (neurons) is crucial for a Dense layer
     }
 
     @only_required_for_messages("tensor-parameter")
@@ -44,15 +40,16 @@ def visit_call(self, node: nodes.Call) -> None:
             if method_name in self.REQUIRED_PARAMS:
                 required_params = self.REQUIRED_PARAMS[method_name]
                 # Check for explicit parameters
-                missing_params = [param for param in required_params if
-                                  not any(kw.arg == param for kw in node.keywords)]
+                missing_params = [
+                    param for param in required_params if not any(kw.arg == param for kw in node.keywords)
+                ]
 
                 if missing_params:
                     self.add_message(
                         "tensor-parameter",
                         node=node,
                         confidence=HIGH,
-                        args=(', '.join(missing_params), method_name),
+                        args=(", ".join(missing_params), method_name),
                     )
 
     @only_required_for_messages("tensor-parameter")
@@ -72,5 +69,5 @@ def visit_call(self, node: nodes.Call) -> None:
                         "tensor-parameter",
                         node=node,
                         confidence=HIGH,
-                        args=(', '.join(missing_params), method_name),
+                        args=(", ".join(missing_params), method_name),
                     )

pylint_ml/checkers/torch/torch_parameter.py

@@ -16,22 +16,20 @@ class PyTorchParameterChecker(BaseChecker):
         "W8111": (
             "Ensure that required parameters %s are explicitly specified in PyTorch method %s.",
             "pytorch-parameter",
-            "Explicitly specifying required parameters improves model performance and prevents unintended "
-            "behavior.",
+            "Explicitly specifying required parameters improves model performance and prevents unintended " "behavior.",
         ),
     }
 
     # Define required parameters for specific PyTorch methods
     REQUIRED_PARAMS = {
         # Optimizers
-        'SGD': ['lr'],  # Focus on the critical learning rate parameter
-        'Adam': ['lr'],  # Learning rate is typically the most important for tuning
-
+        "SGD": ["lr"],  # Focus on the critical learning rate parameter
+        "Adam": ["lr"],  # Learning rate is typically the most important for tuning
         # Layers
-        'Conv2d': ['in_channels', 'out_channels', 'kernel_size'],
+        "Conv2d": ["in_channels", "out_channels", "kernel_size"],
         # These parameters define the convolution's core operation
-        'Linear': ['in_features', 'out_features'],  # Essential to define the transformation dimensions
-        'LSTM': ['input_size', 'hidden_size'],  # Essential for defining the dimensionality of the LSTM cell
+        "Linear": ["in_features", "out_features"],  # Essential to define the transformation dimensions
+        "LSTM": ["input_size", "hidden_size"],  # Essential for defining the dimensionality of the LSTM cell
     }
 
     @only_required_for_messages("pytorch-parameter")
@@ -41,13 +39,14 @@ def visit_call(self, node: nodes.Call) -> None:
             if method_name in self.REQUIRED_PARAMS:
                 required_params = self.REQUIRED_PARAMS[method_name]
                 # Check for explicit parameters
-                missing_params = [param for param in required_params if
-                                  not any(kw.arg == param for kw in node.keywords)]
+                missing_params = [
+                    param for param in required_params if not any(kw.arg == param for kw in node.keywords)
+                ]
 
                 if missing_params:
                     self.add_message(
                         "pytorch-parameter",
                         node=node,
                         confidence=HIGH,
-                        args=(', '.join(missing_params), method_name),
+                        args=(", ".join(missing_params), method_name),
                     )

tests/checkers/test_tensorflow/test_tensor_parameter.py

@@ -19,13 +19,13 @@ def test_sequential_params(self):
         sequential_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="tensor-parameter",
-                    confidence=HIGH,
-                    node=sequential_call,
-                    args=("layers", "Sequential"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="tensor-parameter",
+                confidence=HIGH,
+                node=sequential_call,
+                args=("layers", "Sequential"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(sequential_call)
 
@@ -55,13 +55,13 @@ def test_compile_params(self):
         )
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="tensor-parameter",
-                    confidence=HIGH,
-                    node=node,
-                    args=("optimizer, loss", "compile"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="tensor-parameter",
+                confidence=HIGH,
+                node=node,
+                args=("optimizer, loss", "compile"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(node)
 
@@ -92,13 +92,13 @@ def test_fit_params(self):
         fit_call = node
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="tensor-parameter",
-                    confidence=HIGH,
-                    node=fit_call,
-                    args=("x, y", "fit"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="tensor-parameter",
+                confidence=HIGH,
+                node=fit_call,
+                args=("x, y", "fit"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(fit_call)
 
@@ -128,13 +128,13 @@ def test_conv2d_params(self):
         conv2d_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="tensor-parameter",
-                    confidence=HIGH,
-                    node=conv2d_call,
-                    args=("filters", "Conv2D"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="tensor-parameter",
+                confidence=HIGH,
+                node=conv2d_call,
+                args=("filters", "Conv2D"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(conv2d_call)
 
@@ -162,13 +162,13 @@ def test_dense_params(self):
         dense_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="tensor-parameter",
-                    confidence=HIGH,
-                    node=dense_call,
-                    args=("units", "Dense"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="tensor-parameter",
+                confidence=HIGH,
+                node=dense_call,
+                args=("units", "Dense"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(dense_call)
 
@@ -184,4 +184,3 @@ def test_dense_with_all_params(self):
 
         with self.assertNoMessages():
             self.checker.visit_call(dense_call)
-

tests/checkers/test_torch/test_torch_parameter.py

@@ -19,13 +19,13 @@ def test_sgd_params(self):
         sgd_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="pytorch-parameter",
-                    confidence=HIGH,
-                    node=sgd_call,
-                    args=("lr", "SGD"),  # Specify the expected missing parameters and method name
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="pytorch-parameter",
+                confidence=HIGH,
+                node=sgd_call,
+                args=("lr", "SGD"),  # Specify the expected missing parameters and method name
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(sgd_call)
 
@@ -53,13 +53,13 @@ def test_adam_params(self):
         adam_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="pytorch-parameter",
-                    confidence=HIGH,
-                    node=adam_call,
-                    args=("lr", "Adam"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="pytorch-parameter",
+                confidence=HIGH,
+                node=adam_call,
+                args=("lr", "Adam"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(adam_call)
 
@@ -87,13 +87,13 @@ def test_conv2d_params(self):
         conv2d_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="pytorch-parameter",
-                    confidence=HIGH,
-                    node=conv2d_call,
-                    args=("out_channels", "Conv2d"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="pytorch-parameter",
+                confidence=HIGH,
+                node=conv2d_call,
+                args=("out_channels", "Conv2d"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(conv2d_call)
 
@@ -121,13 +121,13 @@ def test_linear_params(self):
         linear_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="pytorch-parameter",
-                    confidence=HIGH,
-                    node=linear_call,
-                    args=("out_features", "Linear"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="pytorch-parameter",
+                confidence=HIGH,
+                node=linear_call,
+                args=("out_features", "Linear"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(linear_call)
 
@@ -155,13 +155,13 @@ def test_lstm_params(self):
         lstm_call = node.value
 
         with self.assertAddsMessages(
-                pylint.testutils.MessageTest(
-                    msg_id="pytorch-parameter",
-                    confidence=HIGH,
-                    node=lstm_call,
-                    args=("hidden_size", "LSTM"),
-                ),
-                ignore_position=True,
+            pylint.testutils.MessageTest(
+                msg_id="pytorch-parameter",
+                confidence=HIGH,
+                node=lstm_call,
+                args=("hidden_size", "LSTM"),
+            ),
+            ignore_position=True,
         ):
             self.checker.visit_call(lstm_call)