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52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
# Copyright (c) 2022 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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import fastdeploy as fd
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import numpy as np
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# 下载模型并解压
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model_url = "https://bj.bcebos.com/fastdeploy/models/mobilenetv2.tgz"
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fd.download_and_decompress(model_url)
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option = fd.RuntimeOption()
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option.set_model_path("mobilenetv2/inference.pdmodel",
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"mobilenetv2/inference.pdiparams")
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# **** CPU 配置 ****
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option.use_cpu()
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option.use_paddle_infer_backend()
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option.set_cpu_thread_num(12)
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# **** GPU 配置 ***
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# 如需使用GPU，使用如下注释代码
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# option.use_gpu(0)
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# **** IPU 配置 ***
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# 如需使用IPU，使用如下注释代码
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# option.use_ipu()
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# 初始化构造runtime
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runtime = fd.Runtime(option)
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# 获取模型输入名
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input_name = runtime.get_input_info(0).name
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# 构造随机数据进行推理
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results = runtime.infer({
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input_name: np.random.rand(1, 3, 224, 224).astype("float32")
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})
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print(results[0].shape)
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