e57cca971c
**Background:**
There are two principles about operator registration in PyTorch
- The same namespace can be only registered once by `TORCH_LIBRARY`
- The operator signatures can be only registered once by `def`
Considering that all custom operators defined in the current repo are
only used by Ascend, instead of defining a common operator schema by
vLLM, all accelerators then follow this operator schema and complete the
implementation based on their respective hardware, which is conducive to
functional abstraction.
Therefore, we can rename the operator registration namespace to an
Ascend-specific namespace(**_C_ascend**).
Related ISSUE: https://github.com/vllm-project/vllm-ascend/issues/2742
- vLLM version: main
- vLLM main:
f592b3174b
Signed-off-by: FFFrog <ljw1101.vip@gmail.com>
59 lines
2.2 KiB
Python
59 lines
2.2 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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#
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import torch
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import vllm_ascend.ops.common_fused_moe # noqa
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import vllm_ascend.ops.fused_moe # noqa
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import vllm_ascend.ops.layernorm # noqa
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import vllm_ascend.ops.register_custom_ops # noqa
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import vllm_ascend.ops.vocab_parallel_embedding # noqa
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from vllm_ascend.ops.activation import AscendQuickGELU, AscendSiluAndMul
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from vllm_ascend.ops.rotary_embedding import (
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AscendDeepseekScalingRotaryEmbedding, AscendRotaryEmbedding)
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class dummyFusionOp:
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default = None
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def __init__(self, name=""):
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self.name = name
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def register_dummy_fusion_op() -> None:
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torch.ops._C_ascend.rms_norm = dummyFusionOp(name="rms_norm")
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torch.ops._C_ascend.fused_add_rms_norm = dummyFusionOp(
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name="fused_add_rms_norm")
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torch.ops._C_ascend.static_scaled_fp8_quant = dummyFusionOp(
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name="static_scaled_fp8_quant")
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torch.ops._C_ascend.dynamic_scaled_fp8_quant = dummyFusionOp(
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name="dynamic_scaled_fp8_quant")
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torch.ops._C_ascend.dynamic_per_token_scaled_fp8_quant = dummyFusionOp(
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name="dynamic_per_token_scaled_fp8_quant")
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torch.ops._C_ascend.rms_norm_static_fp8_quant = dummyFusionOp(
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name="rms_norm_static_fp8_quant")
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torch.ops._C_ascend.fused_add_rms_norm_static_fp8_quant = dummyFusionOp(
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name="fused_add_rms_norm_static_fp8_quant")
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torch.ops._C_ascend.rms_norm_dynamic_per_token_quant = dummyFusionOp(
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name="rms_norm_dynamic_per_token_quant")
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__all__ = [
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"AscendQuickGELU", "AscendSiluAndMul", "AscendRotaryEmbedding",
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"AscendDeepseekScalingRotaryEmbedding"
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]
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