wehub-resource-sync
116 lines
4.0 KiB
Python
116 lines
4.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
# Schema/aliasing tests for the AITER FP8 quantization custom ops.
|
|
#
|
|
# These use the shared opcheck helper, whose test_schema check catches custom
|
|
# ops whose implementation aliases an input that the registered schema declares
|
|
# as non-aliasing -- the failure mode behind the rocm_aiter_per_tensor_quant
|
|
# regression (a returned scale that aliased the input scale).
|
|
#
|
|
# Skipped if AITER is not installed or the platform is not ROCm.
|
|
|
|
import importlib.util
|
|
|
|
import pytest
|
|
import torch
|
|
|
|
from tests.kernels.utils import opcheck
|
|
|
|
# this import statement is needed to ensure the ops are registered
|
|
from vllm._aiter_ops import rocm_aiter_ops
|
|
from vllm.platforms import current_platform
|
|
|
|
aiter_available = importlib.util.find_spec("aiter") is not None
|
|
|
|
pytestmark = pytest.mark.skipif(
|
|
not (current_platform.is_rocm() and aiter_available),
|
|
reason="AITER ops are only available on ROCm with aiter package installed",
|
|
)
|
|
|
|
FP8_DTYPE = current_platform.fp8_dtype()
|
|
|
|
|
|
def _x(M=128, N=4096):
|
|
return torch.randn((M, N), dtype=torch.float16, device="cuda")
|
|
|
|
|
|
def test_per_tensor_quant_static_schema():
|
|
"""Static per-tensor: caller provides scale (the aliasing regression)."""
|
|
x = _x()
|
|
out = torch.empty_like(x, dtype=FP8_DTYPE)
|
|
scale = torch.ones(1, dtype=torch.float32, device="cuda")
|
|
opcheck(
|
|
torch.ops.vllm.rocm_aiter_per_tensor_quant,
|
|
(out, x, scale, False),
|
|
)
|
|
|
|
|
|
def test_per_tensor_quant_dynamic_schema():
|
|
"""Dynamic per-tensor: op computes scale into the caller's buffer."""
|
|
x = _x()
|
|
out = torch.empty_like(x, dtype=FP8_DTYPE)
|
|
scale = torch.empty(1, dtype=torch.float32, device="cuda")
|
|
opcheck(
|
|
torch.ops.vllm.rocm_aiter_per_tensor_quant,
|
|
(out, x, scale, True),
|
|
)
|
|
|
|
|
|
def test_per_token_quant_dynamic_schema():
|
|
"""Dynamic per-token: op computes scale into a freshly allocated buffer."""
|
|
x = _x()
|
|
opcheck(
|
|
torch.ops.vllm.rocm_aiter_per_token_quant,
|
|
(x, FP8_DTYPE, None),
|
|
)
|
|
|
|
|
|
def test_group_fp8_quant_schema():
|
|
"""Dynamic per-token-group quant."""
|
|
x = _x()
|
|
opcheck(
|
|
torch.ops.vllm.rocm_aiter_group_fp8_quant,
|
|
(x, 128),
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize("dynamic", [True, False])
|
|
def test_per_tensor_quant_matches_native(dynamic):
|
|
"""Wrapper output matches the native scaled_fp8_quant reference."""
|
|
from vllm import _custom_ops as ops
|
|
|
|
torch.manual_seed(0)
|
|
x = _x()
|
|
if dynamic:
|
|
scale_in = None
|
|
else:
|
|
scale_in = torch.tensor([0.5], dtype=torch.float32, device="cuda")
|
|
|
|
out, scale = rocm_aiter_ops.per_tensor_quant(x, FP8_DTYPE, scale_in)
|
|
ref_out, ref_scale = ops.scaled_fp8_quant(x, scale_in)
|
|
|
|
assert out.shape == x.shape
|
|
assert out.dtype == FP8_DTYPE
|
|
assert scale.shape == ref_scale.shape
|
|
deq = out.to(torch.float32) * scale
|
|
if dynamic:
|
|
# Dynamic mode: AITER and native each compute their own scale, so their
|
|
# outputs differ and can't be compared. Just check that AITER's output
|
|
# dequantizes back to the input, within fp8 rounding error.
|
|
torch.testing.assert_close(deq, x.to(torch.float32), rtol=0.07, atol=5e-2)
|
|
else:
|
|
# Static mode: both use the caller's scale, so the outputs must match.
|
|
assert torch.equal(scale, scale_in)
|
|
ref_deq = ref_out.to(torch.float32) * ref_scale
|
|
torch.testing.assert_close(deq, ref_deq, rtol=2e-2, atol=2e-2)
|
|
|
|
|
|
# A test_per_tensor_quant_torch_compile test previously lived here to validate
|
|
# the per-tensor aliasing contract. It existed because opcheck's test_schema
|
|
# could not check this op directly: test_schema compares the op's outputs with
|
|
# torch.allclose, but on fp8 outputs that comparison runs arithmetic fp8 does not
|
|
# support and raises "mul_cuda" is unimplemented for fp8. The fp8-safe opcheck
|
|
# helper fixes that by casting to double before the comparison, so the per-tensor
|
|
# schema tests above can now run test_schema directly. That makes this test
|
|
# redundant, so it has been removed.
|