KeshavAnandCode
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
30 lines
610 B
Python
30 lines
610 B
Python
"""Evaluate model performance"""
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import time
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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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def benchmark(model: LinearEval, samples: int = 1000) -> dict:
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"""
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Benchmark inference speed.
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Returns:
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dict with speed metrics
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"""
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model.eval()
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x = torch.randn(samples, 61072)
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start = time.time()
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with torch.no_grad():
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for _ in range(samples):
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_ = model(x)
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end = time.time()
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return {
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"samples": samples,
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"time_seconds": end - start,
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"ms_per_sample": (end - start) / samples * 1000,
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}
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