52 lines
1.6 KiB
Python
52 lines
1.6 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_scatter import PtScatter
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class TestPtScatter(unittest.TestCase):
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def setUp(self):
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"""Set up test instance."""
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self.node = PtScatter()
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# Test cases: (Target Tensor, Dim, Index Tensor (as string), Source Tensor (as string), Expected Output)
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self.test_cases = [
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(
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torch.tensor([
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[10, 11, 12],
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[21, 22, 23],
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[31, 32, 33],
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]),
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0,
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"[[0, 1, 0], [1, 1, 2]]",
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"[[2, 4, 6], [4, 4, 2]]",
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torch.tensor([
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[2, 11, 6],
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[4, 4, 23],
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[31, 32, 2],
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])
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)
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]
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def test_scatter(self):
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"""Test torch.scatter behavior."""
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for tens, dim, index, src, expected in self.test_cases:
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with self.subTest(tens=tens, dim=dim, index=index, src=src):
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result, = self.node.f(tens, dim, index, src)
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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 values
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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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