mirror of
https://github.com/hiyouga/LLaMA-Factory.git
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45 lines
1.9 KiB
Python
45 lines
1.9 KiB
Python
# Copyright 2025 the LlamaFactory team.
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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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import unittest
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from unittest.mock import MagicMock, patch
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from transformers import AutoModelForCausalLM
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class TestKernelPlugin(unittest.TestCase):
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@patch("torch.accelerator.current_accelerator")
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def test_apply_kernel(self, mock_get_accelerator):
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mock_device = MagicMock()
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mock_device.type = "npu"
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mock_get_accelerator.return_value = mock_device
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model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-qwen2.5")
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original_rmsnorm_forward = model.model.layers[0].input_layernorm.forward
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original_swiglu_forward = model.model.layers[0].mlp.forward
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from llamafactory.v1.plugins.model_plugins.kernels.mlp import npu_swiglu
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from llamafactory.v1.plugins.model_plugins.kernels.registry import apply_kernel
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from llamafactory.v1.plugins.model_plugins.kernels.rms_norm import npu_rms_norm
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from llamafactory.v1.plugins.model_plugins.kernels.rope import npu_rope
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apply_kernel(model, npu_rope.NpuRoPEKernel)
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model = apply_kernel(model, npu_rms_norm.NpuRMSNormKernel)
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assert model.model.layers[0].input_layernorm is not original_rmsnorm_forward
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model = apply_kernel(model, npu_swiglu.NpuSwiGluKernel)
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assert model.model.layers[0].mlp.forward is not original_swiglu_forward
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