2025-02-02 14:58:18 -05:00
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# SPDX-License-Identifier: Apache-2.0
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2024-09-25 10:35:52 -04:00
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import gguf
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import pytest
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import torch
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from tests.kernels.utils import opcheck
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from vllm import _custom_ops as ops # noqa: F401
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@pytest.mark.parametrize("quant_type", [12])
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def test_ggml_opcheck(quant_type):
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block_size, type_size = gguf.GGML_QUANT_SIZES[quant_type]
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shape = [256, 1152]
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qweight = torch.randint(0, 100, shape, device='cuda', dtype=torch.uint8)
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m = qweight.shape[0]
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n = qweight.shape[1] // type_size * block_size
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opcheck(torch.ops._C.ggml_dequantize, (qweight, quant_type, m, n))
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x = torch.rand((m, 512), device='cuda', dtype=torch.float16)
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opcheck(torch.ops._C.ggml_mul_mat_a8,
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(qweight, x, quant_type, qweight.shape[0]))
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opcheck(torch.ops._C.ggml_mul_mat_vec_a8,
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(qweight, x, quant_type, qweight.shape[0]))
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