b917361ca5
torch_npu 2.5.1 support autoload now. This patch does: 1. remove useless torch_npu import 2. replace `torch_npu.npu` to `torch.npu`. Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
51 lines
1.9 KiB
Python
51 lines
1.9 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.activation # noqa
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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.rotary_embedding # noqa
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import vllm_ascend.ops.vocab_parallel_embedding # noqa
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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.cuda.CUDAGraph = torch.npu.NPUGraph
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torch.ops._C.rms_norm = dummyFusionOp(name="rms_norm")
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torch.ops._C.fused_add_rms_norm = dummyFusionOp(name="fused_add_rms_norm")
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torch.ops._C.static_scaled_fp8_quant = dummyFusionOp(
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name="static_scaled_fp8_quant")
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torch.ops._C.dynamic_scaled_fp8_quant = dummyFusionOp(
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name="dynamic_scaled_fp8_quant")
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torch.ops._C.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.rms_norm_static_fp8_quant = dummyFusionOp(
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name="rms_norm_static_fp8_quant")
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torch.ops._C.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.rms_norm_dynamic_per_token_quant = dummyFusionOp(
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name="rms_norm_dynamic_per_token_quant")
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