37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
import os
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import sys
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import unittest
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import torch
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PROJECT_ROOT = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", ".."))
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MODULE_ROOT = os.path.join(PROJECT_ROOT, "modules")
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sys.path.append(MODULE_ROOT)
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from pytorch_wrapper.pt_stack import PtStack
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class TestPtStack(unittest.TestCase):
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def setUp(self):
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"""Set up test instance."""
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self.node = PtStack()
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# Test cases: (Tensor A, Tensor B, Dim, Expected result)
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self.test_cases = [
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(torch.tensor([1, 2]), torch.tensor([5, 6]), 0, torch.tensor([[1, 2], [5, 6]])),
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(torch.tensor([1, 2]), torch.tensor([5, 6]), 1, torch.tensor([[1, 5], [2, 6]]))
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]
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def test_stacking(self):
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"""Test tensor stacking along different dimensions."""
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for tens_a, tens_b, dim, expected in self.test_cases:
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with self.subTest(tens_a=tens_a, tens_b=tens_b, dim=dim):
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result, = self.node.f(tens_a, tens_b, dim)
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# Ensure return value is a tensor
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self.assertTrue(isinstance(result, torch.Tensor), "Output is not a tensor")
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# Ensure result matches expected stacking
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self.assertTrue(torch.equal(result, expected), f"Expected {expected}, got {result}")
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if __name__ == "__main__":
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unittest.main() |