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@fan-min-97 可以参考paddle官网的教程，进行动转静部署。 https://www.paddlepaddle.org.cn/tutorials/projectdetail/3714002

复现项目是这个。 https://aistudio.baidu.com/aistudio/projectdetail/2580805，在动转静的用于部署时：
执行代码：
import paddle
from yolo import *
from models.common import *
from models.experimental import *
from utils.autoanchor import check_anchor_order
from utils.general import check_version, check_yaml, make_divisible, print_args, LOGGER
from utils.plots import feature_visualization
from utils.paddle_utils import copy_attr, fuse_conv_and_bn, initialize_weights, model_info, scale_img,
select_device, time_sync

save inference model

from paddle.static import InputSpec

加载训练好的模型参数

model=Model()
state_dict = paddle.load("YOLOv5-Paddle/runs/train/exp8/weights/best.pdparams")

将训练好的参数读取到网络中

model.set_state_dict(state_dict)

设置模型为评估模式

model.eval()

保存inference模型

paddle.jit.save(
layer=model,
path="YOLOv5-Paddle/inference/helmet",
input_spec=[InputSpec(shape=[None, 640], dtype='float32')])

print("==>Inference model saved in YOLOv5-Paddle/inference/helmet.")

问题1：model=Model()这个model 在项目的YOLOv5_Paddle/models/yolo.py中定义的，是否这里有误？该如何定义这个model
问题2： input_spec=[InputSpec(shape=[None, 784], dtype='float32')]) 也不行，报错

报错：
ValueError: In transformed code:

File "/home/aistudio/YOLOv5-Paddle/models/yolo.py", line 128, in forward
return self._forward_once(x, profile, visualize)  # single-scale inference, train
File "/home/aistudio/YOLOv5-Paddle/models/yolo.py", line 151, in _forward_once
x = m(x)
File "/home/aistudio/YOLOv5-Paddle/models/common.py", line 85, in forward
    def forward(self, x):
        return self.act(self.bn(self.conv(x)))
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE

    def forward_fuse(self, x):

File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 917, in __call__
return self._dygraph_call_func(*inputs, **kwargs)
File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 907, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/conv.py", line 677, in forward
use_cudnn=self._use_cudnn)
File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/functional/conv.py", line 148, in _conv_nd
type=op_type, inputs=inputs, outputs=outputs, attrs=attrs)
File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/layer_helper.py", line 43, in append_op
return self.main_program.current_block().append_op(*args, **kwargs)
File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/framework.py", line 3184, in append_op
attrs=kwargs.get("attrs", None))
File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/framework.py", line 2344, in __init__
self.desc.infer_shape(self.block.desc)

ValueError: (InvalidArgument) The input of Op(Conv) should be a 4-D or 5-D Tensor. But received: input's dimension is 2, input's shape is [-1, 640].

[Hint: Expected in_dims.size() == 4 || in_dims.size() == 5 == true, but received in_dims.size() == 4 || in_dims.size() == 5:0 != true:1.] (at /paddle/paddle/fluid/operators/conv_op.cc:74)
[operator < conv2d > error]