深度学习-Tensorflow2.2-tf.data输入模块{2}-tf.data基础用法-09

TF.DATA 模块

tf.data模块简介

import tensorflow as tf

# 使用一个列表建立dataset
dataset = tf.data.Dataset.from_tensor_slices([1,2,3,4,5])

dataset

# 应用dataset
for ele in dataset:
    print(ele)

# 把Tensor输出为numpy类型
for ele in dataset:
    print(ele.numpy())

# 使用一个嵌套列表建立dataset
dataset = tf.data.Dataset.from_tensor_slices([[1,2,3,],[4,5,6],[7,8,9]])

dataset

for ele in dataset:
    print(ele)

for ele in dataset:
    print(ele.numpy())

dataset_dic = tf.data.Dataset.from_tensor_slices({
     "A":[1,2,3,4],
                                                 "B":[5,6,7,8],
                                                 "C":[10,11,12,13]
                                                 })

dataset_dic

for ele in dataset_dic:
    print(ele)

import numpy as np

dataset = tf.data.Dataset.from_tensor_slices(np.array([1,2,3,4,5]))

for ele in dataset:
    print(ele.numpy())

# 取值
dataset = tf.data.Dataset.from_tensor_slices([1,2,3,4,5,6,7,8,9])
for ele in dataset.take(4):
    print(ele.numpy())

next(iter(dataset.take(1)))

# shuffle 乱序dataset
dataset = dataset.shuffle(9)

# repeat循环count=3重复3次
dataset = dataset.repeat(count=3)
for ele in dataset:
    print(ele.numpy())

# batch 每一次请求出来3个数字
dataset = dataset.batch(3)
for ele in dataset:
    print(ele.numpy())

# 总结
dataset = tf.data.Dataset.from_tensor_slices([1,2,3,4,5])
# shuffle 乱序dataset
dataset = dataset.shuffle(5)
# repeat循环count=3重复3次
dataset = dataset.repeat(count=3)
# batch 每一次请求出来3个数字
dataset = dataset.batch(3)
# repeat循环count=3重复3次
dataset = dataset.repeat(count=3)
for ele in dataset:
    print(ele.numpy())

# tf.square做平方运算
dataset = tf.data.Dataset.from_tensor_slices([1,2,3,4,5])
dataset = dataset.map(tf.square)
for ele in dataset:
    print(ele.numpy())