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6e668dc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Unit tests for QuantizationConfigArgs parsing."""
import pytest
from vllm.config.quantization import (
QUANT_KEY_NAMES,
QuantizationConfigArgs,
QuantSpec,
resolve_quantization_config,
)
from vllm.model_executor.layers.quantization.utils.quant_utils import (
kFp8Dynamic128Sym,
kFp8DynamicTokenSym,
kFp8Static128BlockSym,
kFp8StaticTensorSym,
kInt8StaticChannelSym,
kMxfp8Dynamic,
)
# ---- QuantSpec ------------------------------------------------------------
def test_quant_spec_resolves_string_to_quant_key():
spec = QuantSpec(weight="mxfp8", activation="fp8_per_token")
assert spec.weight == kMxfp8Dynamic
assert spec.activation == kFp8DynamicTokenSym
def test_quant_spec_accepts_quant_key_directly():
spec = QuantSpec(weight=kFp8StaticTensorSym)
assert spec.weight is kFp8StaticTensorSym
assert spec.activation is None
def test_quant_spec_rejects_unknown_name():
with pytest.raises(ValueError, match="unknown quantization name"):
QuantSpec(weight="not_a_real_format")
# ---- QuantizationConfigArgs string shorthand on linear/moe ----------------
def test_args_linear_string_resolves_via_quant_key_names():
# A bare QUANT_KEY_NAMES entry desugars to QuantSpec(weight=<key>).
args = QuantizationConfigArgs(linear="fp8_per_block_static")
assert args.linear == QuantSpec(weight=kFp8Static128BlockSym)
assert args.moe is None
def test_args_moe_string_resolves_via_online_shorthand():
# An online-shorthand name pulls the matching slot from _ONLINE_SHORTHANDS
# (so `linear: "fp8_per_block"` and `moe: "fp8_per_block"` produce the
# same per-layer-kind spec the `--quantization fp8_per_block` shorthand
# would).
args = QuantizationConfigArgs(moe="fp8_per_block")
assert args.moe == QuantSpec(weight=kFp8Static128BlockSym)
def test_args_string_shorthand_missing_slot_raises():
# int8_per_channel_weight_only sets only `moe`; using it on `linear`
# has no defined spec and should raise rather than silently no-op.
with pytest.raises(ValueError, match="does not define a linear spec"):
QuantizationConfigArgs(linear="int8_per_channel_weight_only")
def test_args_accepts_dict_form():
args = QuantizationConfigArgs(moe={"activation": "mxfp8"})
assert args.moe == QuantSpec(weight=None, activation=kMxfp8Dynamic)
# ---- resolve_quantization_config -----------------------------------------
def test_resolve_shorthand_only_populates_both_slots():
args = resolve_quantization_config("fp8_per_block", None)
assert args.linear == QuantSpec(weight=kFp8Static128BlockSym)
assert args.moe == QuantSpec(weight=kFp8Static128BlockSym)
def test_resolve_int8_shorthand_leaves_linear_unset():
# int8_per_channel_weight_only is MoE-only; linear stays None so that
# OnlineQuantizationConfig leaves Linear layers in full precision.
args = resolve_quantization_config("int8_per_channel_weight_only", None)
assert args.linear is None
assert args.moe == QuantSpec(weight=kInt8StaticChannelSym)
def test_resolve_quantization_config_only():
# When only `quantization_config` is given (e.g. for an already-quantized
# checkpoint that needs an activation override), it's returned as-is.
args = resolve_quantization_config(None, {"moe": {"activation": "mxfp8"}})
assert args.linear is None
assert args.moe == QuantSpec(weight=None, activation=kMxfp8Dynamic)
def test_resolve_merges_explicit_over_shorthand():
# Explicit linear in quantization_config wins; moe falls back to the
# shorthand's slot.
args = resolve_quantization_config(
"fp8_per_tensor",
{"linear": "fp8_per_block"},
)
assert args.linear == QuantSpec(weight=kFp8Static128BlockSym)
assert args.moe == QuantSpec(weight=kFp8StaticTensorSym)
def test_resolve_rejects_quantization_config_with_non_shorthand_quant():
# If --quantization names something other than an online shorthand,
# quantization_config is not allowed via this path (checkpoint quant
# paths read it directly off ModelConfig instead).
with pytest.raises(ValueError, match="quantization_config is only supported"):
resolve_quantization_config("gptq", {"linear": "fp8_per_block"})
# ---- QUANT_KEY_NAMES coverage --------------------------------------------
def test_quant_key_names_round_trip():
# Every advertised name should round-trip through QuantSpec without error
# and produce the same QuantKey it maps to.
for name, expected in QUANT_KEY_NAMES.items():
assert QuantSpec(weight=name).weight == expected, name
assert QuantSpec(activation=name).activation == expected, name
def test_static_block_weight_paired_with_dynamic_block_activation():
# The block-FP8 shorthand pair: 128x128 static weights + 1x128 dynamic
# activations. Pinning this so renames in QUANT_KEY_NAMES don't quietly
# rewire the kernel dispatch.
spec = QuantSpec(weight="fp8_per_block_static", activation="fp8_per_block_dynamic")
assert spec.weight == kFp8Static128BlockSym
assert spec.activation == kFp8Dynamic128Sym
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