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https://github.com/comfyanonymous/ComfyUI.git
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31b6b53236
- export_custom_nodes() finds all the classes that inherit from CustomNode and exports them correctly for custom node discovery to find - regular expressions - additional string formatting and parsing nodes
94 lines
2.9 KiB
Python
94 lines
2.9 KiB
Python
import torch
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from comfy_extras.nodes.nodes_strings import StringFormat
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def test_string_format_basic():
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n = StringFormat()
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# Test basic string formatting
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result, = n.execute(format="Hello, {}!", value0="World")
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assert result == "Hello, World!"
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# Test multiple values
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result, = n.execute(format="{} plus {} equals {}", value0=2, value1=2, value2=4)
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assert result == "2 plus 2 equals 4"
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def test_string_format_types():
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n = StringFormat()
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# Test with different types
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result, = n.execute(format="Float: {:.2f}, Int: {}, Bool: {}",
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value0=3.14159, value1=42, value2=True)
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assert result == "Float: 3.14, Int: 42, Bool: True"
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# Test None values
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result, = n.execute(format="{}, {}, {}", value0=None, value1="test", value2=None)
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assert result == "None, test, None"
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def test_string_format_tensors():
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n = StringFormat()
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# Test small tensor
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small_tensor = torch.tensor([1, 2, 3])
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result, = n.execute(format="Tensor: {}", value0=small_tensor)
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assert result == "Tensor: [1, 2, 3]"
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# Test large tensor
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large_tensor = torch.randn(100, 100)
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result, = n.execute(format="Large tensor: {}", value0=large_tensor)
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assert result == "Large tensor: <Tensor shape=100x100>"
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# Test mixed tensor sizes
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small_tensor = torch.tensor([1, 2])
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large_tensor = torch.randn(50, 50)
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result, = n.execute(format="{} and {}", value0=small_tensor, value1=large_tensor)
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assert "and <Tensor shape=50x50>" in result
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assert "[1, 2]" in result
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def test_string_format_edge_cases():
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n = StringFormat()
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# Test with missing values
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result, = n.execute(format="{} {} {}", value0="a", value1="b")
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assert result.startswith("Format error: ")
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# Test with empty format string
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result, = n.execute(format="", value0="ignored")
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assert result == ""
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# Test with no placeholders
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result, = n.execute(format="Hello World", value0="ignored")
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assert result == "Hello World"
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# Test with named placeholders
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result, = n.execute(format="X: {value0}, Y: {value1}", value0=10, value1=20)
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assert result == "X: 10, Y: 20"
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# Test mixing None, tensors and regular values
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tensor = torch.tensor([1, 2, 3])
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result, = n.execute(format="{}, {}, {}", value0=None, value1=tensor, value2="test")
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assert result == "None, [1, 2, 3], test"
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def test_string_format_tensor_edge_cases():
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n = StringFormat()
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# Test empty tensor
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empty_tensor = torch.tensor([])
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result, = n.execute(format="Empty tensor: {}", value0=empty_tensor)
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assert result == "Empty tensor: []"
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# Test scalar tensor
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scalar_tensor = torch.tensor(5)
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result, = n.execute(format="Scalar tensor: {}", value0=scalar_tensor)
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assert result == "Scalar tensor: 5"
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# Test multi-dimensional small tensor
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small_2d_tensor = torch.tensor([[1, 2], [3, 4]])
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result, = n.execute(format="2D tensor: {}", value0=small_2d_tensor)
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assert result == "2D tensor: [[1, 2], [3, 4]]"
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