val_dataset=pytorchvideo.data.Kinetics( data_path=os.path.join(self._DATA_PATH, "val"), clip_sampler=pytorchvideo.data.make_clip_sampler("uniform", self._CLIP_DURATION), decode_audio=False, ) returntorch.utils.
clip_sampler=video_utils.make_clip_sampler("random", 16), video_sampler=video_utils.make_video_sampler("random", 8), transform=transform, )#创建数据加载器dataloader = VideoDataloader( dataset, batch_size=4, num_workers=4, pin_memory=True, shuffle=True, ) 1. 2. 3. 4. 5. 6. 7. 8...
models.resnet.create_acoustic_resnet( model_num_class=400,) # Create Kinetics data loader. kinetics_loader = torch.utils.data.DataLoader( data.Kinetics( data_path=DATA_PATH, clip_sampler=data.make_clip_sampler( "uniform", CLIP_DURATION, ), ) batch_size=BATCH_SIZ...
)acoustic_model=models.resnet.create_acoustic_resnet(model_num_class=400,)# Create Kinetics data loader.kinetics_loader=torch.utils.data.DataLoader(data.Kinetics(data_path=DATA_PATH,clip_sampler=data.make_clip_sampler("uniform",CLIP_DURATION,),)batch_size=BATCH_SIZE,)# Deploy model...
kinetics_loader = torch.utils.data.DataLoader( data.Kinetics( data_path=DATA_PATH, clip_sampler=data.make_clip_sampler( "uniform", CLIP_DURATION, ), ) batch_size=BATCH_SIZE, ) # Deploy model. visual_net_inst_deploy = accelerator.deployment.\ convert_to_deployable_form(net_inst, input_...
importpytorchvideofrompytorchvideo.dataimportAVADataset# 加载 AVA 数据集dataset=AVADataset(data_path='path/to/ava_dataset',clip_sampler=pytorchvideo.data.make_clip_sampler("random",5),decode_audio=False)# 示例输出video,label=dataset[0]# 获取第一个视频及其标签 ...
deftrain_dataloader(self):train_dataset=pytorchvideo.data.Kinetics(data_path=os.path.join(self._DATA_PATH,"train"),clip_sampler=pytorchvideo.data.make_clip_sampler("random", self._CLIP_DURATION),decode_audio=False, ) returntorch.utils.data.DataLoader( ...
(model_num_class=400,# Create Kinetics data loader.kinetics_loader = torch.utils.data.DataLoader(data.Kinetics(data_path=DATA_PATH,clip_sampler=data.make_clip_sampler("uniform",CLIP_DURATION,),batch_size=BATCH_SIZE,# Deploy model.visual_net_inst_deploy = accelerator.deployment.\convert_to_...
data_path=os.path.join(self._DATA_PATH,"val"), clip_sampler=pytorchvideo.data.make_clip_sampler("uniform",self._CLIP_DURATION), decode_audio=False, ) returntorch.utils.data.DataLoader( val_dataset, batch_size=self._BATCH_SIZE, num_workers=self._NUM_WORKERS, ...
The fix which solved the issue for me is adding a distributed video_sampler to the datasets (both train and val). fromtorch.utils.dataimportDistributedSamplertrain_dataset=pytorchvideo.data.Kinetics(data_path=data_path,clip_sampler=pytorchvideo.data.make_clip_sampler("random",kwargs["clip_duration...