40 lines
1.5 KiB
Python
40 lines
1.5 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_pow import PtPow
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class TestPtPow(unittest.TestCase):
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def setUp(self):
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"""Set up test instance."""
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self.node = PtPow()
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# Test cases: (Tensor A, Tensor B, Expected result)
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self.test_cases = [
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(torch.tensor([2.0, 3.0, 4.0]), torch.tensor([3.0, 2.0, 1.0]), torch.tensor([8.0, 9.0, 4.0])), # 2^3, 3^2, 4^1
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(torch.ones(3, 3) * 4, torch.ones(3, 3) * 2, torch.ones(3, 3) * 16), # 4^2 = 16
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(torch.full((2, 2), 5.0), torch.full((2, 2), 3.0), torch.full((2, 2), 125.0)), # 5^3 = 125
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(torch.tensor([[2.0], [3.0]]), torch.tensor([[4.0], [5.0]]), torch.tensor([[16.0], [243.0]])), # 2^4 = 16, 3^5 = 243
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]
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def test_power(self):
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"""Test tensor exponentiation."""
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for tens_a, tens_b, expected in self.test_cases:
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with self.subTest(tens_a=tens_a, tens_b=tens_b):
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result, = self.node.f(tens_a, tens_b)
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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 power computation
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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()
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