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719ccfd773
Add test_fp8_min_max_helper.py with mocked unit tests that verify: - Standard FP8 dtype uses PyTorch's finfo values - fnuz dtype on fnuz platform (MI300) returns 224.0, not 240.0 - Standard dtype on fnuz platform uses finfo values - fnuz dtype on non-fnuz platform uses finfo values These tests use mocking to verify the logic without requiring actual ROCm hardware. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> Signed-off-by: c0de128 <kevin.mckay@outlook.com>
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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Unit tests for the get_fp8_min_max() helper function.
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These tests verify the FP8 min/max value logic for both standard
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and fnuz (ROCm MI300) dtype handling.
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"""
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from unittest.mock import patch
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import pytest
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import torch
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class TestGetFp8MinMax:
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"""Test cases for get_fp8_min_max() function."""
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def test_standard_fp8_dtype(self):
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"""Test that standard FP8 dtype uses PyTorch's finfo values."""
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from vllm.model_executor.layers.quantization.utils.quant_utils import (
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get_fp8_min_max,
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)
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# For standard float8_e4m3fn, should return finfo values
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fp8_min, fp8_max = get_fp8_min_max(torch.float8_e4m3fn)
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finfo = torch.finfo(torch.float8_e4m3fn)
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# Standard FP8 max is 448.0 for e4m3fn
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assert fp8_max == finfo.max, f"Expected finfo.max={finfo.max}, got {fp8_max}"
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assert fp8_min == finfo.min, f"Expected finfo.min={finfo.min}, got {fp8_min}"
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@patch("vllm.model_executor.layers.quantization.utils.quant_utils.current_platform")
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def test_fnuz_fp8_dtype_on_fnuz_platform(self, mock_platform):
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"""Test that fnuz dtype on fnuz platform returns 224.0."""
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mock_platform.is_fp8_fnuz.return_value = True
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mock_platform.fp8_dtype.return_value = torch.float8_e4m3fnuz
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# Re-import to use mocked platform
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from importlib import reload
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import vllm.model_executor.layers.quantization.utils.quant_utils as qu
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reload(qu)
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fp8_min, fp8_max = qu.get_fp8_min_max(torch.float8_e4m3fnuz)
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# fnuz on ROCm MI300 should return 224.0, not 240.0
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assert fp8_max == 224.0, (
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f"Expected 224.0 for fnuz on fnuz platform, got {fp8_max}"
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)
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assert fp8_min == -224.0, (
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f"Expected -224.0 for fnuz on fnuz platform, got {fp8_min}"
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)
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@patch("vllm.model_executor.layers.quantization.utils.quant_utils.current_platform")
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def test_standard_dtype_on_fnuz_platform(self, mock_platform):
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"""Test that standard dtype on fnuz platform uses finfo values."""
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mock_platform.is_fp8_fnuz.return_value = True
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from vllm.model_executor.layers.quantization.utils.quant_utils import (
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get_fp8_min_max,
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)
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# Standard e4m3fn dtype should use finfo even on fnuz platform
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fp8_min, fp8_max = get_fp8_min_max(torch.float8_e4m3fn)
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finfo = torch.finfo(torch.float8_e4m3fn)
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assert fp8_max == finfo.max, (
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f"Standard dtype should use finfo.max={finfo.max}, got {fp8_max}"
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)
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@patch("vllm.model_executor.layers.quantization.utils.quant_utils.current_platform")
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def test_fnuz_dtype_on_non_fnuz_platform(self, mock_platform):
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"""Test that fnuz dtype on non-fnuz platform uses finfo values."""
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mock_platform.is_fp8_fnuz.return_value = False
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from vllm.model_executor.layers.quantization.utils.quant_utils import (
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get_fp8_min_max,
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)
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# fnuz dtype on non-fnuz platform should use finfo
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fp8_min, fp8_max = get_fp8_min_max(torch.float8_e4m3fnuz)
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finfo = torch.finfo(torch.float8_e4m3fnuz)
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# Should be 240.0, not 224.0 (non-fnuz platform)
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assert fp8_max == finfo.max, (
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f"Non-fnuz platform should use finfo.max={finfo.max}, got {fp8_max}"
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)
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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