style: apply consistent whitespace and formatting across codebase

tinytorch/tests/test_utils.py

@@ -13,29 +13,29 @@ from pathlib import Path
 def setup_integration_test():
     """
     Set up the environment for integration testing.
-    
+
     This function ensures:
     1. The TinyTorch package is importable
     2. NumPy random seed is set for reproducibility
     3. Warning filters are set appropriately
-    
+
     Call this at the top of integration test files before importing TinyTorch.
     """
     import warnings
     import numpy as np
-    
+
     # Ensure tinytorch is on the path (from project root)
     project_root = Path(__file__).parent.parent
     if str(project_root) not in sys.path:
         sys.path.insert(0, str(project_root))
-    
+
     # Set random seed for reproducibility
     np.random.seed(42)
-    
+
     # Suppress certain warnings during tests
     warnings.filterwarnings('ignore', category=DeprecationWarning)
     warnings.filterwarnings('ignore', category=FutureWarning)
-    
+
     # Set quiet mode for tinytorch imports during tests
     os.environ['TINYTORCH_QUIET'] = '1'
 
@@ -53,21 +53,21 @@ def get_test_data_path() -> Path:
 def create_test_tensor(shape, requires_grad=True, seed=None):
     """
     Create a test tensor with random data.
-    
+
     Args:
         shape: Tuple specifying tensor shape
         requires_grad: Whether tensor should track gradients
         seed: Optional random seed for reproducibility
-    
+
     Returns:
         Tensor with random data
     """
     import numpy as np
     from tinytorch.core.tensor import Tensor
-    
+
     if seed is not None:
         np.random.seed(seed)
-    
+
     data = np.random.randn(*shape).astype(np.float32)
     return Tensor(data, requires_grad=requires_grad)
 
@@ -75,7 +75,7 @@ def create_test_tensor(shape, requires_grad=True, seed=None):
 def assert_tensors_close(t1, t2, rtol=1e-5, atol=1e-8, msg=""):
     """
     Assert that two tensors are element-wise close.
-    
+
     Args:
         t1: First tensor
         t2: Second tensor
@@ -84,11 +84,11 @@ def assert_tensors_close(t1, t2, rtol=1e-5, atol=1e-8, msg=""):
         msg: Optional message for assertion error
     """
     import numpy as np
-    
+
     # Extract data from tensors if needed
     data1 = t1.data if hasattr(t1, 'data') else t1
     data2 = t2.data if hasattr(t2, 'data') else t2
-    
+
     if not np.allclose(data1, data2, rtol=rtol, atol=atol):
         diff = np.abs(data1 - data2)
         max_diff = np.max(diff)
@@ -111,4 +111,3 @@ def skip_if_no_tinytorch():
         return pytest.mark.skipif(False, reason="TinyTorch available")
     except ImportError:
         return pytest.mark.skip(reason="TinyTorch not installed")
-