检查Python的模块搜索路径是否包含data.createdataloader所在的目录: Python 的模块搜索路径通常包括当前目录('.')、环境变量PYTHONPATH指定的目录,以及标准库目录等。 您可以通过打印sys.path来检查当前的搜索路径: python import sys print(sys.path) 如果data目录不在这个列表中,您可以通过修改PYTHONPATH环境变量或在...
# 从第2章导入create_dataloader_v1函数fromchapter02importcreate_dataloader_v1# 设置随机种子以确保可重复性torch.manual_seed(123)# 创建训练数据加载器train_loader=create_dataloader_v1(train_data,batch_size=2,max_length=GPT_CONFIG_124M["context_length"],stride=GPT_CONFIG_124M["context_length"],d...
from torch.utils.data import DataLoader num_workers = 0 batch_size = 8 torch.manual_seed(123) train_loader = DataLoader( dataset=train_dataset, batch_size=batch_size, shuffle=True, num_workers=num_workers, drop_last=True, ) val_loader = DataLoader( dataset=val_dataset, batch_size=batch_...
从torch.utils.data导入DataLoader,用于创建mini-batch sizes(可理解成batch_size大小的数据块)。从torchvision.utisl导入save_image函数,用于保存一些fake samples(模型生成图片)。从math,导入log2和sqrt函数。导入Numpy,用于做线性代数运算(linear algebra)。导入os,用于跟操作系统互动。导入tqdm,用来显示进度条。导入...
def create_dataloader_v1(txt, batch_size=4, max_length=256, stride=128, shuffle=True, drop_last=True, num_workers=0): # Initialize the tokenizer tokenizer = tiktoken.get_encoding("gpt2") # Create dataset dataset = GPTDatasetV1(txt, tokenizer, max_length, stride) # Create dataloader ...
import os import argparse import json from medlvlm.datasets.datasets.vindrcxr_dataset import VinDrCXRDataset from torch.utils.data import DataLoader from tqdm import tqdm import os from medlvlm.common.registry import registry from medlvlm.common.config import Config from medlvlm.conversation.conversatio...
python获取datafrom获取总行数 # 如何实现“python获取datafrom获取总行数” ## 1. 整体流程 首先,我们需要明确整个操作的流程。下面是一份表格展示每个步骤: | 步骤 | 操作 | |---|---| | 1 | 导入必要的库 | | 2 | 读取数据并获取总行数 | 读取数据 python 数据文件 原创 mob649e...
# 需要导入模块: from ansible.parsing.dataloader import DataLoader [as 别名]# 或者: from ansible.parsing.dataloader.DataLoader importload_from_file[as 别名]defmain(self, path):data_dir = self.conf['data_dir'] loader = DataLoader() full_path="%s/%s"% (data_dir, path)ifos.path.isfile("...
Use the scm/planningDataLoader/import account to upload the zipped file. Note: For more information about uploading files to the Universal Content Manager server, see the following section in the Implementing Common Features for SCM guide: External Integration chapter, External Data Integration...
write(text_data) else: with open(file_path, "r", encoding="utf-8") as file: text_data = file.read() from previous_chapters import create_dataloader_v1 # Train/validation ratio train_ratio = 0.90 split_idx = int(train_ratio * len(text_data)) torch.manual_seed(123) train_loader =...