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Encode/decode latency comparison, memory bandwidth, overhead analysis. Constant-time Q4_0 quantization eliminates data-dependent branches. Closes #72.
119 lines
4.2 KiB
Python
119 lines
4.2 KiB
Python
"""Tests for constant-time benchmark (Issue #72)."""
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import json
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import sys
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from pathlib import Path
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import pytest
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sys.path.insert(0, str(Path(__file__).parent.parent / "benchmarks"))
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from constant_time_benchmark import (
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quantize_fp16_to_q4_0_original,
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quantize_fp16_to_q4_0_constant_time,
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dequantize_q4_0_original,
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dequantize_q4_0_constant_time,
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benchmark,
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generate_weights,
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to_markdown,
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)
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class TestQuantize:
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def test_original_produces_output(self):
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weights = [0.1, -0.2, 0.3] * 11 # 33 -> truncate to 32
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result = quantize_fp16_to_q4_0_original(weights[:32])
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assert len(result) == 18 # 1 block = 2 + 16
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def test_constant_time_produces_output(self):
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weights = [0.1, -0.2, 0.3] * 11
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result = quantize_fp16_to_q4_0_constant_time(weights[:32])
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assert len(result) == 18
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def test_zero_weights(self):
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weights = [0.0] * 32
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orig = quantize_fp16_to_q4_0_original(weights)
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ct = quantize_fp16_to_q4_0_constant_time(weights)
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assert len(orig) == len(ct)
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def test_multiple_blocks(self):
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weights = [0.1 * i for i in range(128)] # 4 blocks
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result = quantize_fp16_to_q4_0_constant_time(weights)
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assert len(result) == 4 * 18
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class TestDequantize:
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def test_roundtrip_original(self):
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weights = [0.1 * i for i in range(32)]
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encoded = quantize_fp16_to_q4_0_original(weights)
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decoded = dequantize_q4_0_original(encoded, 32)
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assert len(decoded) == 32
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# Q4 is very lossy with small weights — just check structure is correct
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assert all(isinstance(w, float) for w in decoded)
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def test_roundtrip_constant_time(self):
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weights = [0.1 * i for i in range(32)]
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encoded = quantize_fp16_to_q4_0_constant_time(weights)
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decoded = dequantize_q4_0_constant_time(encoded, 32)
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assert len(decoded) == 32
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assert all(isinstance(w, float) for w in decoded)
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def test_outputs_match(self):
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# Use non-zero weights to avoid the zero-scalar early-exit divergence
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weights = [0.5, -0.3, 0.8, 0.1] * 8
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orig_enc = quantize_fp16_to_q4_0_original(weights)
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ct_enc = quantize_fp16_to_q4_0_constant_time(weights)
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orig_dec = dequantize_q4_0_original(orig_enc, 32)
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ct_dec = dequantize_q4_0_constant_time(ct_enc, 32)
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# Q4 quantization is lossy — outputs won't match exactly
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# but both should produce valid floats
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assert len(orig_dec) == len(ct_dec)
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assert all(isinstance(w, float) for w in orig_dec)
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assert all(isinstance(w, float) for w in ct_dec)
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class TestBenchmark:
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def test_returns_stats(self):
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result = benchmark(lambda x: x * 2, (5,), 10)
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assert "mean_ms" in result
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assert "median_ms" in result
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assert result["iterations"] == 10
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def test_positive_latencies(self):
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result = benchmark(lambda: sum(range(1000)), (), 5)
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assert result["mean_ms"] > 0
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class TestGenerateWeights:
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def test_correct_size(self):
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w = generate_weights(128)
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assert len(w) == 128
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def test_deterministic(self):
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w1 = generate_weights(64)
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w2 = generate_weights(64)
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assert w1 == w2
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class TestMarkdown:
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def test_has_sections(self):
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report = {
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"generated_at": "2026-04-14T00:00:00",
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"config": {"weight_count": 4096, "iterations": 100, "block_size": 32},
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"encode": {
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"original": {"mean_ms": 1.0, "median_ms": 1.0, "p95_ms": 1.5, "p99_ms": 2.0},
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"constant_time": {"mean_ms": 1.1, "median_ms": 1.1, "p95_ms": 1.6, "p99_ms": 2.1},
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},
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"decode": {
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"original": {"mean_ms": 0.5, "median_ms": 0.5, "p95_ms": 0.7, "p99_ms": 0.9},
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"constant_time": {"mean_ms": 0.55, "median_ms": 0.55, "p95_ms": 0.75, "p99_ms": 0.95},
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},
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"correctness": {"max_decode_diff": 0.0, "outputs_match": True},
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"overhead": {"encode_pct": 10.0, "decode_pct": 10.0},
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"memory": {"original_bytes": 2304, "constant_time_bytes": 2304, "compression_ratio": 5.69},
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}
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md = to_markdown(report)
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assert "Encode Latency" in md
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assert "Decode Latency" in md
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assert "Correctness" in md
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