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

64 lines
2.7 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_matmul import PtMatMul
class TestPtMatMul(unittest.TestCase):
def setUp(self):
"""Set up test instance."""
self.node = PtMatMul()
# Valid test cases: (Tensor A, Tensor B, Expected result)
self.valid_test_cases = [
# Case 1: 1D x 1D (dot product)
(torch.tensor([1.0, 2.0, 3.0]), torch.tensor([4.0, 5.0, 6.0]), torch.tensor(32.0)),
# Case 2: 1D x 2D (vector-matrix multiplication)
(torch.tensor([1.0, 2.0]), torch.tensor([[3.0, 4.0], [5.0, 6.0]]), torch.tensor([13.0, 16.0])),
# Case 3: 2D x 2D (matrix-matrix multiplication)
(torch.tensor([[1.0, 2.0], [3.0, 4.0]]), torch.tensor([[5.0, 6.0], [7.0, 8.0]]), torch.tensor([[19.0, 22.0], [43.0, 50.0]])),
# Case 4: 3D x 2D (batched matrix-matrix multiplication)
(torch.ones(2, 3, 4), torch.ones(4, 5), torch.full((2, 3, 5), 4.0)), # (2,3,4) * (4,5) → (2,3,5)
# Case 5: 3D x 3D (batched matrix multiplication with broadcasting)
(torch.ones(2, 3, 4), torch.ones(2, 4, 5), torch.full((2, 3, 5), 4.0)), # (2,3,4) * (2,4,5) → (2,3,5)
]
# Invalid test cases (should raise errors)
self.invalid_test_cases = [
(torch.ones(2, 3), torch.ones(4, 2)), # (2,3) * (4,2) is invalid
(torch.tensor([1.0, 2.0, 3.0]), torch.tensor([4.0, 5.0])), # Vector size mismatch
(torch.ones(2, 3, 4), torch.ones(3, 5)), # (2,3,4) * (3,5) should fail due to misalignment
]
def test_matrix_multiplication(self):
"""Test valid matrix multiplication cases."""
for tens_a, tens_b, expected in self.valid_test_cases:
with self.subTest(tens_a=tens_a, tens_b=tens_b):
result, = self.node.f(tens_a, tens_b)
# Ensure return value is a tensor
self.assertTrue(isinstance(result, torch.Tensor), "Output is not a tensor")
# Ensure result matches expected matrix multiplication
self.assertTrue(torch.equal(result, expected), f"Expected {expected}, got {result}")
def test_invalid_multiplication(self):
"""Test invalid cases where dimensions do not match."""
for tens_a, tens_b in self.invalid_test_cases:
with self.subTest(tens_a=tens_a, tens_b=tens_b):
with self.assertRaises(RuntimeError, msg=f"MatMul should fail for shapes {tens_a.shape} and {tens_b.shape}"):
self.node.f(tens_a, tens_b)
if __name__ == "__main__":
unittest.main()