16 lines
951 B
Python
16 lines
951 B
Python
import tensorflow_datasets as tfds
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splits=tfds.Split.TRAIN.subsplit(weighted=[2,1,1])
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# tfds.Split.TRAIN.subsplit函数按传入的权重将其分成为训练集占50%，验证集占25%，测试集占25%
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# metadata属性用于获取MNIST数据集的基本信息，包括数据的种类，大小以及对应的形式
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(raw_trian,raw_validation,raw_test),metadata=tfds.load('mnist',split=list(splits),with_info=True,as_supervised=True)
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import tensorflow as tf
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# load函数中添加split参数，表示将数据在传入的时候直接进行分割，按数据的类型分割成“image”和“model”
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# batch_size=-1,可以从返回的tf.Tensor对象获取NumPy数组中完整数据集
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minst_data=tfds.load('mnist',split=tfds.Split.TRAIN,batch_size=-1)
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numpy_ds=tfds.as_numpy(minst_data)
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numpy_image,numpy_label=numpy_ds["image"],numpy_ds["label"]
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'''minst_train,minst_test=minst_data['train'],minst_data['test']
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print(minst_train)
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print(minst_test'''
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