9e2fe0cae6
- Create python directory with data/, model/ subdirectories - Implement LinearEval(61072->1) model - Add config, constants, feature_extractor - Add tests with 4 passing test cases
46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
"""Tests for NNUE implementation"""
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import pytest
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import torch
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import numpy as np
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from python.model.nnue_linear import LinearEval
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from python.constants import TOTAL_FEATURES
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class TestLinearEval:
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"""Tests for the linear NNUE model"""
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def test_model_initialization(self):
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"""Test model creates correct shape"""
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model = LinearEval()
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assert model.linear.in_features == TOTAL_FEATURES
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assert model.linear.out_features == 1
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def test_model_output_shape(self):
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"""Test model outputs correct shape"""
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model = LinearEval()
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x = torch.randn(10, TOTAL_FEATURES)
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y = model(x)
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assert y.shape == (10, 1)
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def test_model_zero_output(self):
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"""Test model with zero input"""
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model = LinearEval()
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x = torch.zeros(1, TOTAL_FEATURES)
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with torch.no_grad():
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y = model(x)
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assert y.item() == 0.0
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def test_gradient_flow(self):
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"""Test gradients flow through model"""
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model = LinearEval()
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x = torch.randn(10, TOTAL_FEATURES, requires_grad=True)
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y = model(x)
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loss = y.sum()
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loss.backward()
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assert x.grad is not None
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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