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step35/67-
...
fix/139-qu
| Author | SHA1 | Date | |
|---|---|---|---|
| 48dfa5d0f7 | |||
| 1c6c3defe9 |
@@ -37,6 +37,7 @@ class QuantLevel:
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layer_adaptive: int # TURBO_LAYER_ADAPTIVE value (0-7)
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kv_type: str # -ctk/-ctv flag value
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min_memory_headroom_gb: float # Minimum free memory to recommend this level
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quality_score: int = 0 # Explicit quality ordering (higher = better)
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description: str = ""
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@@ -50,6 +51,7 @@ QUANT_LEVELS = [
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layer_adaptive=7,
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kv_type="turbo4",
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min_memory_headroom_gb=4.0,
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quality_score=100,
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description="PolarQuant + QJL 4-bit. Best quality, ~4.2x KV compression."
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),
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QuantLevel(
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@@ -60,6 +62,7 @@ QUANT_LEVELS = [
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layer_adaptive=5,
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kv_type="turbo3",
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min_memory_headroom_gb=3.0,
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quality_score=80,
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description="3-bit TurboQuant. High quality, ~6x KV compression."
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),
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QuantLevel(
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@@ -70,6 +73,7 @@ QUANT_LEVELS = [
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layer_adaptive=3,
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kv_type="turbo2",
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min_memory_headroom_gb=2.0,
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quality_score=60,
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description="2-bit TurboQuant. Balanced, ~10x KV compression."
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),
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QuantLevel(
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@@ -80,6 +84,7 @@ QUANT_LEVELS = [
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layer_adaptive=0,
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kv_type="q4_0",
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min_memory_headroom_gb=1.5,
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quality_score=40,
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description="Standard 4-bit quant. Fast fallback, no TurboQuant."
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),
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]
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@@ -22,7 +22,10 @@ class TestQuantLevels:
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def test_levels_ordered_by_quality(self):
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"""Levels should be ordered from best quality to most aggressive."""
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for i in range(len(QUANT_LEVELS) - 1):
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assert QUANT_LEVELS[i].bits_per_channel > QUANT_LEVELS[i + 1].bits_per_channel
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# Use quality_score for explicit quality ordering
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# (bits_per_channel doesn't always correlate with quality:
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# q4_0 has 4.0 bits but lower quality than turbo2 with 1.5 bits)
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assert QUANT_LEVELS[i].quality_score > QUANT_LEVELS[i + 1].quality_score
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def test_all_levels_have_required_fields(self):
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for level in QUANT_LEVELS:
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@@ -32,6 +35,7 @@ class TestQuantLevels:
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assert level.quality_label
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assert level.layer_adaptive >= 0
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assert level.kv_type
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assert level.quality_score > 0
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class TestKVEstimate:
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