40 lines
1.4 KiB
Python
40 lines
1.4 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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import ast
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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_argmax import PtArgmax
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class TestPtArgmax(unittest.TestCase):
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def setUp(self):
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"""Set up test instance."""
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self.node = PtArgmax()
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# Test cases: (Tensor, Dim (as string), keepdim, Expected result)
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self.test_cases = [
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(torch.tensor([[1, 3, 2], [4, 0, 5]]), "0", False, torch.tensor([1, 0, 1])),
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(torch.tensor([[1, 3, 2], [4, 0, 5]]), "1", True, torch.tensor([[1], [2]])),
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(torch.tensor([[10, 3, 2], [123, 0, 5]]), "", False, torch.tensor(3)),
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]
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def test_argmax(self):
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"""Test torch.argmax behavior."""
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for tens, dim, keepdim, expected in self.test_cases:
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with self.subTest(tens=tens, dim=dim, keepdim=keepdim):
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result, = self.node.f(tens, dim, keepdim)
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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 indices
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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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