from datasets import load_dataset dataset = load_dataset("rotten_tomatoes", split="train") Dataset({ features: ['text', 'label'], num_rows: 8530 }) Configurations 示例,使用 get_dataset_config_names 方法查看包含的子集 from datasets import get_dataset_config_names configs = get_dataset_config...
数据集的split名称可以通过函数get_dataset_split_names()获取。有些数据集包含很多子数据集,如不同语言记录一个子数据集,这些子数据集在加载时使用configuration来指定,函数get_dataset_config_names()可以帮助我们获取所有configuration名称。 #拼接train和test splittrain_test_ds=datasets.load_dataset("bookcorpus",s...
train_ds, eval_ds, _ = datasets.get_dataset(config, File "/home/lesjie/scoreInverseProblems_2/datasets.py", line 122, in get_dataset dataset_builder = tfds.builder(config.data.dataset.replace('_', ''), data_dir='/home/data/Brats/training/') File "/root/miniconda3/envs/tf2.4/lib/...
To enable the bucketing feature in the dataset section of the config files, you need to pass the multiple tarred datasets as a list of lists. If user passes just a list of strings, then the datasets would simply get concatenated which would be different from bucketing. Here is an example...
Here you can post your trained models on different Datasets - 3 files: cfg weights names Optional: accuracy mAP@0.5 or/and mAP@0.5...0.95 Optional: BFLOPS and/or Inference time (milliseconds) COCO test-dev Model Size BFLOPS Inference tim...
from azureml.core import Workspace, Dataset from azureml.datadrift import DataDriftDetector from datetime import datetime # get the workspace object ws = Workspace.from_config() # get the target dataset target = Dataset.get_by_name(ws, 'target') # set the baseline dataset baseline = target....
val spark=SparkSession.builder().appName("Spark SQL Example").config("spark.some.config.option","some-value").getOrCreate()// 包含隐式转换(比如讲 RDDs 转成 DataFrames)APIimportspark.implicits._ Spark 2.0中的 SparkSession对于 Hive 的各个特性提供了内置支持,包括使用 HiveQL 编写查询语句,使用...
static voidsortByMostRecentlyAdded(java.util.List<DataSetInventoryRecord> dataSetRecords, boolean sortAscending) Sorts dataset list by most recently added. Methods inherited from class java.lang.Object clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait ...
get_file_dataset(dataset_filter='all', enable_telemetry: bool = True) -> FileDataset 参数 展开表 名称说明 cls 必需 当前类 dataset_filter str 一个筛选器,用于确定返回的数据。 可以是“all”(默认值)、“train”或“test”。 默认值: all enable_telemetry bool 是否为此数据集启用遥测。
Mount when startup: When configuring an instance, set the Dataset or Mount Settings parameters. Restart the instance for the changes to take effect. Dynamic mount: Use the SDK for PAI to configure mounting within the DSW instance without the need to restart the instance. To improve the perform...