72 lines
2.1 KiB
Python
72 lines
2.1 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_sum import PtSum
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class TestPtSum(unittest.TestCase):
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def setUp(self):
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"""Set up test instance."""
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self.node = PtSum()
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# Test cases: (Tensor, Dim (as string), keepdim, Expected result)
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self.test_cases = [
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(
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torch.tensor([[1, 3, 2], [2, 1, 3]]),
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"0",
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False,
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torch.tensor([3, 4, 5])
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),
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(
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torch.tensor([[1, 3, 2], [4, 0, 5]]),
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"1",
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True,
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torch.tensor([[6], [9]])
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),
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(
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torch.tensor([[1, 3, 2], [4, 5, 6]]),
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"0",
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False,
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torch.tensor([5, 8, 8])
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),
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(
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torch.tensor([[1, 3, 2], [4, 5, 6], [7, 8, 9]]),
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"1",
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False,
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torch.tensor([6, 15, 24])
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),
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(
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torch.tensor([[1, 2], [3, 4]]),
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"",
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False,
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torch.tensor(10) # Sum of all elements
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),
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(
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torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]),
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"(0, 1)",
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False,
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torch.tensor([16, 20]) # Sum over dimensions (0, 1)
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)
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]
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def test_sum(self):
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"""Test torch.sum 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 sum 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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