因为我进行了相互调用,我在父类中调用了子类。 fromsrc.datasetimportBaseDatasetclassPSINSDataset(BaseDataset): from src.main importPSINSDatasetclassBaseDataset(Dataset):
简介ImportError: cannot import name 'BaseDataset' from 'src.dataset' 因为我进行了相互调用,我在父类中调用了子类。 fromsrc.datasetimportBaseDatasetclassPSINSDataset(BaseDataset):fromsrc.mainimportPSINSDatasetclassBaseDataset(Dataset):
frompaddlenlp.trlimportSFTConfig,SFTTrainerfromdatasetsimportload_datasetdataset=load_dataset("ZHUI/alpaca_demo",split="train")training_args=SFTConfig(output_dir="Qwen/Qwen2.5-0.5B-SFT",device="gpu")trainer=SFTTrainer(args=training_args,model="Qwen/Qwen2.5-0.5B-Instruct",train_dataset=dataset, )...
That said, it would be valuable to demonstrate (perhaps through examples or an end-to-end solution) the value of taking an R dataset in .rda/.rds format and incorporating it into a Python workflow. This could involve using some collection of R packages that don't have a good ...
For example, if you're interested in data science, you might start by analyzing a dataset using pandas and visualizing the data with matplotlib. Python basics. Start with the fundamentals of Python. This includes understanding the syntax, data types, control structures, functions, and more. Data...
type The type property of the dataset must be set to AzureDatabricksDeltaLakeDataset. Yes database Name of the database. No for source, yes for sink table Name of the delta table. No for source, yes for sinkExample:JSON Copy { "name": "AzureDatabricksDeltaLakeDataset", "properties": ...
{ "name": "PostgreSQLDataset", "properties": { "type": "PostgreSqlV2Table", "linkedServiceName": { "referenceName": "<PostgreSQL linked service name>", "type": "LinkedServiceReference" }, "annotations": [], "schema": [], "typeProperties": { "schema": "<schema name>", "table":...
JDBCAppendTableSink import org.apache.flink.api.scala._ import org.apache.flink.table.api.scala.{BatchTableEnvironment, table2RowDataSet} object BatchJob { case class Test(id: Int, key1: String, value1: Boolean, key2: Long, value2: Double) private var dbName: String = "default"...
Dataset API提供便捷、高效的数据集加载功能;内置千言数据集,提供丰富的面向自然语言理解与生成场景的中文数据集,为NLP研究人员提供一站式的科研体验。 from paddlenlp.datasets import load_dataset train_ds, dev_ds, test_ds = load_dataset("chnsenticorp", splits=["train", "dev", "test"]) train_ds...
You could reduce duplicate key processing by storing the already processed keys in a database and checking the database before processing a key. That would result in less space usage for the data stores, faster dataset creation, and possibly faster runtime. ...