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https://github.com/PaddlePaddle/FastDeploy.git
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CSWYF3634076
9286403570
* support v1 loader * remove useless code * remove useless * [Model] support Qwen3VL images success * [Model] support Qwen3VL rope_3d * [Model] support Qwen3VL remove log * [Model] support Qwen3VL RL * [Model] support Qwen3VL tp * [Model] support Qwen3VL video * [Model] support Qwen3VL fix ernievl * [Model] support Qwen3VL fix get_image_boundaries.cc array out of bounds * [Model] support Qwen3VL fix multi card * [Model] support Qwen3VL file close * [Model] support Qwen3VL fix ce * [Model] support Qwen3VL fix unittest * [Model] support Qwen3VL add unittest --------- Co-authored-by: Ayakouji <yuhongh@qq.com>
41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. 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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"""
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from collections import OrderedDict
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from paddle import nn
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class ClassInstantier(OrderedDict):
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"""Instantiates layers lazily when accessed."""
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def __getitem__(self, key):
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content = super().__getitem__(key)
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cls, kwargs = content if isinstance(content, tuple) else (content, {})
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return cls(**kwargs)
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ACT2CLS = {
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"gelu_tanh": (nn.GELU, {"approximate": "tanh"}),
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}
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ACT2FN = ClassInstantier(ACT2CLS)
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def get_activation_fn(hidden_act: str):
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if hidden_act == "gelu_pytorch_tanh":
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return ACT2FN["gelu_tanh"]
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raise KeyError(f"function {hidden_act} not found in ACT2FN mapping {list(ACT2FN.keys())}")
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