56 lines
2.0 KiB
Python
56 lines
2.0 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 torch.nn.functional
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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.ptf_softmax import PtfSoftmax
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def compute_softmax(x, dim=-1):
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return torch.nn.functional.softmax(x, dim=dim)
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class TestPtfSoftmax(unittest.TestCase):
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def setUp(self):
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"""Set up test instance."""
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self.node = PtfSoftmax()
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# Test cases: (Input Tensor, Expected Softmax Output)
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self.test_cases = [
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# Rank-1 tensor
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(torch.tensor([0.0, -100.0, 100.0]), compute_softmax(torch.tensor([0.0, -100.0, 100.0]))),
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# # Rank-2 tensor
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(torch.tensor([[-1.0, 2.0, 3.0], [0.0, 1.0, -1.0]]), compute_softmax(torch.tensor([[-1.0, 2.0, 3.0], [0.0, 1.0, -1.0]]))),
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# # Rank-2 tensor. Check dim=-1 maps to 1.
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(torch.tensor([[-1.0, 2.0, 3.0], [0.0, 1.0, -1.0]]), compute_softmax(torch.tensor([[-1.0, 2.0, 3.0], [0.0, 1.0, -1.0]]), dim=1)),
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# # Rank-3 tensor
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(torch.tensor([[[1.0, 2.0], [3.0, 4.0]], [[0.0, -1.0], [-2.0, -3.0]]]), compute_softmax(torch.tensor([[[1.0, 2.0], [3.0, 4.0]], [[0.0, -1.0], [-2.0, -3.0]]]))),
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]
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def test_softmax_function(self):
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"""Test the returned Softmax function."""
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softmax_function, = self.node.f()
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# Ensure return value is callable
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self.assertTrue(callable(softmax_function), "Returned value is not callable")
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for input_tensor, expected in self.test_cases:
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with self.subTest(input_tensor=input_tensor):
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result = softmax_function(input_tensor)
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# Ensure output 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 output
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self.assertTrue(torch.allclose(result, expected, atol=1e-6), f"Expected {expected}, got {result}")
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if __name__ == "__main__":
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unittest.main()
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