Pytorch 对象检测模型优化

如何解决Pytorch 对象检测模型优化

我想减小对象检测模型的大小。同样，我尝试使用 pytorch-mobile 优化器优化 Faster R-CNN 模型以进行对象检测，但是生成的 .pt zip 文件与原始模型尺寸。

我使用了下面提到的代码

import torch
import torchvision
from torch.utils.mobile_optimizer import optimize_for_mobile

model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)

model.eval()
script_model = torch.jit.script(model)
from torch.utils.mobile_optimizer import optimize_for_mobile
script_model_vulkan = optimize_for_mobile(script_model,backend='Vulkan')
torch.jit.save(script_model_vulkan,"frcnn.pth")

解决方法

你必须先量化你的模型
请按照以下步骤操作here
&然后使用这些方法

from torch.utils.mobile_optimizer import optimize_for_mobile
script_model_vulkan = optimize_for_mobile(script_model,backend='Vulkan')
torch.jit.save(script_model_vulkan,"frcnn.pth")

编辑：

resnet50 模型的量化过程

import torchvision
model = torchvision.models.resnet50(pretrained=True)
import os
import torch

def print_model_size(mdl):
    torch.save(mdl.state_dict(),"tmp.pt")
    print("%.2f MB" %(os.path.getsize("tmp.pt")/1e6))
    os.remove('tmp.pt')
print_model_size(model) # will print original model size
backend = "qnnpack"
model.qconfig = torch.quantization.get_default_qconfig(backend)
torch.backends.quantized.engine = backend
model_static_quantized = torch.quantization.prepare(model,inplace=False)
model_static_quantized = torch.quantization.convert(model_static_quantized,inplace=False)



print_model_size(model_static_quantized) ## will print quantized model size