61 lines
2.6 KiB
Python
61 lines
2.6 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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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_bmm import PtBmm # Updated import to PtBmm
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class TestPtBmm(unittest.TestCase):
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def setUp(self):
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"""Set up test instance."""
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self.node = PtBmm()
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# Valid test cases: (Tensor A, Tensor B, Expected result)
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self.valid_test_cases = [
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# Case 1: Batch of 2 matrices (3x4) * (4x5) → (2, 3, 5)
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(torch.ones(2, 3, 4), torch.ones(2, 4, 5), torch.full((2, 3, 5), 4.0)),
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# Case 2: Batch of 3 matrices (2x3) * (3x2) → (3, 2, 2)
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(torch.tensor([[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]]),
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torch.tensor([[[7.0, 8.0], [9.0, 10.0], [11.0, 12.0]]]),
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torch.tensor([[[58.0, 64.0], [139.0, 154.0]]])),
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# Case 3: Identity matrix batch multiplication (should remain the same)
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(torch.eye(3).expand(4, -1, -1), torch.eye(3).expand(4, -1, -1), torch.eye(3).expand(4, -1, -1)),
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]
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# Invalid test cases (should raise errors)
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self.invalid_test_cases = [
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(torch.ones(3, 4), torch.ones(4, 5)), # 2D tensors (not allowed)
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(torch.ones(2, 3, 4), torch.ones(3, 4, 5)), # Mismatched batch size
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(torch.ones(2, 3, 4, 5), torch.ones(2, 5, 6)), # 4D tensors (not allowed)
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(torch.ones(2, 3, 4), torch.ones(2, 5, 6)), # Matmul shape mismatch within batch
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]
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def test_batched_matrix_multiplication(self):
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"""Test valid batched matrix multiplication cases."""
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for tens_a, tens_b, expected in self.valid_test_cases:
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with self.subTest(tens_a=tens_a, tens_b=tens_b):
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result, = self.node.f(tens_a, tens_b)
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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 batch matrix multiplication
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self.assertTrue(torch.equal(result, expected), f"Expected {expected}, got {result}")
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def test_invalid_multiplication(self):
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"""Test invalid cases where dimensions do not match."""
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for tens_a, tens_b in self.invalid_test_cases:
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with self.subTest(tens_a=tens_a, tens_b=tens_b):
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with self.assertRaises(Exception, msg=f"torch.bmm() should fail for shapes {tens_a.shape} and {tens_b.shape}"):
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self.node.f(tens_a, tens_b)
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if __name__ == "__main__":
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unittest.main()
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