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TensorFlow 数据集

TensorFlow Datasets 是一个现成的数据集集合，可以与 TensorFlow 或其他 Python 机器学习框架（如 Jax）一起使用。所有数据集都以 tf.data.Datasets 的形式提供，使得输入管道易于使用且高性能。要开始使用，请参阅 指南 和 数据集列表。

本笔记本展示了如何将TensorFlow Datasets加载到我们可以用于下游处理的文档格式中。

安装​

你需要安装 tensorflow 和 tensorflow-datasets python 包。

%pip install --upgrade --quiet  tensorflow
%pip install --upgrade --quiet  tensorflow-datasets

示例​

例如，我们使用mlqa/en 数据集。

MLQA (Multilingual Question Answering Dataset) 是一个用于评估多语言问答性能的基准数据集。该数据集包含7种语言：阿拉伯语、德语、西班牙语、英语、印地语、越南语、中文。

# Feature structure of `mlqa/en` dataset:

FeaturesDict(
    {
        "answers": Sequence(
            {
                "answer_start": int32,
                "text": Text(shape=(), dtype=string),
            }
        ),
        "context": Text(shape=(), dtype=string),
        "id": string,
        "question": Text(shape=(), dtype=string),
        "title": Text(shape=(), dtype=string),
    }
)
import tensorflow as tf
import tensorflow_datasets as tfds
# try directly access this dataset:
ds = tfds.load("mlqa/en", split="test")
ds = ds.take(1)  # Only take a single example
ds
<_TakeDataset element_spec={'answers': {'answer_start': TensorSpec(shape=(None,), dtype=tf.int32, name=None), 'text': TensorSpec(shape=(None,), dtype=tf.string, name=None)}, 'context': TensorSpec(shape=(), dtype=tf.string, name=None), 'id': TensorSpec(shape=(), dtype=tf.string, name=None), 'question': TensorSpec(shape=(), dtype=tf.string, name=None), 'title': TensorSpec(shape=(), dtype=tf.string, name=None)}>

现在我们必须创建一个自定义函数来将数据集样本转换为文档。

这是一个需求。TF数据集没有标准格式，这就是为什么我们需要创建一个自定义的转换函数。

让我们使用context字段作为Document.page_content，并将其他字段放在Document.metadata中。

from langchain_core.documents import Document


def decode_to_str(item: tf.Tensor) -> str:
    return item.numpy().decode("utf-8")


def mlqaen_example_to_document(example: dict) -> Document:
    return Document(
        page_content=decode_to_str(example["context"]),
        metadata={
            "id": decode_to_str(example["id"]),
            "title": decode_to_str(example["title"]),
            "question": decode_to_str(example["question"]),
            "answer": decode_to_str(example["answers"]["text"][0]),
        },
    )


for example in ds:
    doc = mlqaen_example_to_document(example)
    print(doc)
    break
API Reference:Document
page_content='After completing the journey around South America, on 23 February 2006, Queen Mary 2 met her namesake, the original RMS Queen Mary, which is permanently docked at Long Beach, California. Escorted by a flotilla of smaller ships, the two Queens exchanged a "whistle salute" which was heard throughout the city of Long Beach. Queen Mary 2 met the other serving Cunard liners Queen Victoria and Queen Elizabeth 2 on 13 January 2008 near the Statue of Liberty in New York City harbour, with a celebratory fireworks display; Queen Elizabeth 2 and Queen Victoria made a tandem crossing of the Atlantic for the meeting. This marked the first time three Cunard Queens have been present in the same location. Cunard stated this would be the last time these three ships would ever meet, due to Queen Elizabeth 2\'s impending retirement from service in late 2008. However this would prove not to be the case, as the three Queens met in Southampton on 22 April 2008. Queen Mary 2 rendezvoused with Queen Elizabeth 2  in Dubai on Saturday 21 March 2009, after the latter ship\'s retirement, while both ships were berthed at Port Rashid. With the withdrawal of Queen Elizabeth 2 from Cunard\'s fleet and its docking in Dubai, Queen Mary 2 became the only ocean liner left in active passenger service.' metadata={'id': '5116f7cccdbf614d60bcd23498274ffd7b1e4ec7', 'title': 'RMS Queen Mary 2', 'question': 'What year did Queen Mary 2 complete her journey around South America?', 'answer': '2006'}
``````output
2023-08-03 14:27:08.482983: W tensorflow/core/kernels/data/cache_dataset_ops.cc:854] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset  will be discarded. This can happen if you have an input pipeline similar to `dataset.cache().take(k).repeat()`. You should use `dataset.take(k).cache().repeat()` instead.
from langchain_community.document_loaders import TensorflowDatasetLoader
from langchain_core.documents import Document

loader = TensorflowDatasetLoader(
    dataset_name="mlqa/en",
    split_name="test",
    load_max_docs=3,
    sample_to_document_function=mlqaen_example_to_document,
)

TensorflowDatasetLoader 有以下参数：

  • dataset_name: 要加载的数据集的名称
  • split_name: 要加载的拆分的名称。默认为 "train"。
  • load_max_docs: 加载文档数量的限制。默认为100。
  • sample_to_document_function: 一个将数据集样本转换为文档的函数
docs = loader.load()
len(docs)
2023-08-03 14:27:22.998964: W tensorflow/core/kernels/data/cache_dataset_ops.cc:854] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset  will be discarded. This can happen if you have an input pipeline similar to `dataset.cache().take(k).repeat()`. You should use `dataset.take(k).cache().repeat()` instead.
3
docs[0].page_content
'After completing the journey around South America, on 23 February 2006, Queen Mary 2 met her namesake, the original RMS Queen Mary, which is permanently docked at Long Beach, California. Escorted by a flotilla of smaller ships, the two Queens exchanged a "whistle salute" which was heard throughout the city of Long Beach. Queen Mary 2 met the other serving Cunard liners Queen Victoria and Queen Elizabeth 2 on 13 January 2008 near the Statue of Liberty in New York City harbour, with a celebratory fireworks display; Queen Elizabeth 2 and Queen Victoria made a tandem crossing of the Atlantic for the meeting. This marked the first time three Cunard Queens have been present in the same location. Cunard stated this would be the last time these three ships would ever meet, due to Queen Elizabeth 2\'s impending retirement from service in late 2008. However this would prove not to be the case, as the three Queens met in Southampton on 22 April 2008. Queen Mary 2 rendezvoused with Queen Elizabeth 2  in Dubai on Saturday 21 March 2009, after the latter ship\'s retirement, while both ships were berthed at Port Rashid. With the withdrawal of Queen Elizabeth 2 from Cunard\'s fleet and its docking in Dubai, Queen Mary 2 became the only ocean liner left in active passenger service.'
docs[0].metadata
{'id': '5116f7cccdbf614d60bcd23498274ffd7b1e4ec7',
 'title': 'RMS Queen Mary 2',
 'question': 'What year did Queen Mary 2 complete her journey around South America?',
 'answer': '2006'}

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