if isinstance(train_dataset, torch.utils.data.IterableDataset): if self.args.world_size > 1: train_dataset = IterableDatasetShard( train_dataset, batch_size=self._train_batch_size, drop_last=self.args.dataloader_drop_last, num_processes=self.args.world_size, process_index=self.args.process_...
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self.train_loop(self.train_dataloader) File "D:\Anaconda\envs\myModelScope2\lib\site-packages\modelscope\trainers\trainer.py", line 1234, in train_loop self.train_step(self.model, data_batch) File "D:\Anaconda\envs\myModelScope2\lib\site-packages\modelscope\trainers\multi_modal\clip\clip...
TensorDataset可以用来对tensor进行打包,类似于Python中的zip。 #x_train y_train 和 x_test y_test都是经过预处理的DataFrame数据 dl_train = DataLoader(TensorDataset(torch.tensor(x_train).float(),torch.tensor(y_train).float(),shuffle = True,batch_size=8) dl_valid = DataLoader(TensorDataset(torch.t...
你不必重写。您可以在PyTorch Dataset中重用核心数据加载逻辑
# 需要导入模块: import data [as 别名]# 或者: from data import create_dataloader [as 别名]definit_train_setting(self):self.train_dataset=create_dataloader(self.opt)self.train_model=create_model(self.opt)self.train_total_steps=0self.epoch_len=self.opt.niter+self.opt.niter_decayself.cur_lr...
代码列表:basic_transforms.py import cv2 import numpy as np import random import matplotlib.pyplot as plt class Compose(object): def __init__(self, transforms): self.transforms = transforms def __ca…
In train.py. The target data for targets must come from the data in the dataloader, but why can't I find the data for targets in the dataloader? Any idea why, thanks! Environment No response Minimal Reproducible Example No response
( ValueError: train_dataloader, train_cfg, and optim_wrapper should be either all None or not None, but got train_dataloader=None, train_cfg={'type': 'EpochBasedTrainLoop', 'max_epochs': 12, 'val_interval': 1}, optim_wrapper={'type': 'OptimWrapper', 'optimizer': {'type': 'SGD'...
transform=testTransform, gpu=self.gpu_id) dataloader_params = { 'batch_size' : config['batch_size'], 'pin_memory' : True, 'num_workers' : 32 } train_loader = DataLoader(train_dataset, shuffle=True, **dataloader_params) val_loader = DataLoader(val_dataset, shuffle=False, **dataloader_...