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2025-03-20 21:40:01 -07:00

40 lines
1.6 KiB
Python

import os
import sys
import unittest
import torch
PROJECT_ROOT = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", ".."))
MODULE_ROOT = os.path.join(PROJECT_ROOT, "modules")
sys.path.append(MODULE_ROOT)
from pytorch_wrapper.pt_exp import PtExp
class TestPtExp(unittest.TestCase):
def setUp(self):
"""Set up test instance."""
self.node = PtExp()
# Test cases: (Tensor A, Expected result)
self.test_cases = [
(torch.tensor([0.0, 1.0, 2.0], dtype=torch.float32), torch.exp(torch.tensor([0.0, 1.0, 2.0], dtype=torch.float32))), # Edge cases
(torch.tensor([-1.0, -2.0, 0.5], dtype=torch.float32), torch.exp(torch.tensor([-1.0, -2.0, 0.5], dtype=torch.float32))), # Common values
(torch.tensor([[0.1, -0.3], [0.7, -0.9]], dtype=torch.float32), torch.exp(torch.tensor([[0.1, -0.3], [0.7, -0.9]], dtype=torch.float32))), # 2D case
(torch.full((2, 2), 0.6, dtype=torch.float32), torch.exp(torch.full((2, 2), 0.6, dtype=torch.float32))), # Constant matrix
]
def test_exp(self):
"""Test tensor element-wise exponential function using torch.exp()."""
for tens_a, expected in self.test_cases:
with self.subTest(tens_a=tens_a):
result, = self.node.f(tens_a)
# Ensure return value is a tensor
self.assertTrue(isinstance(result, torch.Tensor), "Output is not a tensor")
# Ensure result matches expected exp values
self.assertTrue(torch.allclose(result, expected, atol=1e-6), f"Expected {expected}, got {result}")
if __name__ == "__main__":
unittest.main()