from torch.autograd import Variable import cv2 from data import BaseTransform, VOC_CLASSES as labelmap from ssd import build_ssd import imageio Defining a function that will do the detection def detect(frame, net, transform): height, width = frame.shape[:2] ...
# from mxnet import gluon, nd # import mxnet as mx # from . import resnet_style # MXNET_ENABLED = True # mx_GPU = mx.gpu() # mx_CPU = mx.cpu() # except: # MXNET_ENABLED = False MXNET_ENABLED = False try: import torch @@ -59,23 +63,6 @@ def parse_model_string(pretra...
zero_gradients 并不是 torch.autograd 或torch.autograd.gradch(如果它存在的话)中的函数或变量。实际上,zero_gradients 是优化器对象的一个方法,用于将优化器中所有参数的梯度清零。 例如,在使用 torch.optim.SGD 或torch.optim.Adam 等优化器时,可以调用 optimizer.zero_grad() 来清零梯度。 如果'zero_gradient...
These efforts would likely be easier if we switched from .backward() to torch.autograd.grad(...) in a few places in Pyro (maybe everywhere). How? PyTorch has two autograd interfaces: .backward() is more side-effectful and torch.autograd.grad(...) is more functional. Pyro currently ...