Fix linting

src/basic_data_handling/tensor_nodes.py

@@ -1,6 +1,6 @@
 import torch
 from inspect import cleandoc
-from typing import Any, Union
+from typing import Any
 
 try:
     from comfy.comfy_types.node_typing import IO, ComfyNodeABC

tests/test_tensor_nodes.py

@@ -1,4 +1,3 @@
-import pytest
 import torch
 from src.basic_data_handling.tensor_nodes import (
     TensorCreate, TensorBinaryOp, TensorUnaryOp, TensorSlice,
@@ -11,11 +10,11 @@ def test_tensor_create():
     result = node.create([1, 2, 3])
     assert isinstance(result[0], torch.Tensor)
     assert torch.equal(result[0], torch.tensor([1, 2, 3]))
-    
+
     # From scalar
     result = node.create(5.0)
     assert torch.equal(result[0], torch.tensor(5.0))
-    
+
     # From existing tensor
     t = torch.tensor([1.0, 2.0])
     result = node.create(t)
@@ -25,7 +24,7 @@ def test_tensor_binary_op():
     node = TensorBinaryOp()
     a = torch.tensor([10.0, 20.0])
     b = torch.tensor([2.0, 4.0])
-    
+
     assert torch.equal(node.operate(a, b, "add")[0], a + b)
     assert torch.equal(node.operate(a, b, "subtract")[0], a - b)
     assert torch.equal(node.operate(a, b, "multiply")[0], a * b)
@@ -35,7 +34,7 @@ def test_tensor_binary_op():
 def test_tensor_unary_op():
     node = TensorUnaryOp()
     t = torch.tensor([-1.0, 0.0, 1.0])
-    
+
     assert torch.equal(node.operate(t, "abs")[0], torch.tensor([1.0, 0.0, 1.0]))
     assert torch.equal(node.operate(t, "neg")[0], torch.tensor([1.0, 0.0, -1.0]))
     assert torch.equal(node.operate(torch.tensor([0.0]), "sin")[0], torch.tensor([0.0]))
@@ -43,11 +42,11 @@ def test_tensor_unary_op():
 def test_tensor_slice():
     node = TensorSlice()
     t = torch.arange(10).reshape(2, 5) # [[0,1,2,3,4], [5,6,7,8,9]]
-    
+
     # Simple slice
     result = node.slice_tensor(t, "0, 1:3")
     assert torch.equal(result[0], t[0, 1:3])
-    
+
     # Ellipsis/Full slice
     result = node.slice_tensor(t, ":, 2")
     assert torch.equal(result[0], t[:, 2])
@@ -55,17 +54,17 @@ def test_tensor_slice():
 def test_tensor_reshape():
     node = TensorReshape()
     t = torch.arange(6)
-    
+
     result = node.reshape(t, "2, 3")
     assert result[0].shape == (2, 3)
-    
+
     result = node.reshape(t, "-1, 2")
     assert result[0].shape == (3, 2)
 
 def test_tensor_permute():
     node = TensorPermute()
     t = torch.randn(2, 3, 4)
-    
+
     result = node.permute(t, "2, 0, 1")
     assert result[0].shape == (4, 2, 3)
 
@@ -73,11 +72,11 @@ def test_tensor_join():
     node = TensorJoin()
     t1 = torch.tensor([1, 2])
     t2 = torch.tensor([3, 4])
-    
+
     # Cat
     result = node.join(t1, t2, 0, "concatenate")
     assert torch.equal(result[0], torch.tensor([1, 2, 3, 4]))
-    
+
     # Stack
     result = node.join(t1, t2, 0, "stack")
     assert result[0].shape == (2, 2)
@@ -86,7 +85,7 @@ def test_tensor_join():
 def test_tensor_info():
     node = TensorInfo()
     t = torch.zeros((2, 3), dtype=torch.float32)
-    
+
     shape, dtype, device = node.get_info(t)
     assert shape == [2, 3]
     assert "float32" in dtype