在Tensorflow 1.2.0中读取CSV文件

import tensorflow as tf
import os

def read_csv_file(file_path, batch_size=32, shuffle=True):
    # 创建一个Dataset对象，从CSV文件中读取数据
    dataset = tf.data.experimental.make_csv_dataset(
        file_pattern=file_path,
        batch_size=batch_size,
        shuffle=shuffle,
        num_epochs=1,
        column_names=None,
        column_defaults=None,
        label_name=None,
        select_columns=None,
        field_delim=',',
        use_quote_delim=True,
        na_value='',
        header=True
    )
    
    # 对数据进行预处理等操作
    dataset = dataset.map(preprocess_data)
    
    return dataset

def preprocess_data(features, labels):
    # 对特征进行预处理
    processed_features = ...
    
    # 对标签进行预处理
    processed_labels = ...
    
    return processed_features, processed_labels

file_path = 'path/to/csv/file.csv'
batch_size = 32
shuffle = True

dataset = read_csv_file(file_path, batch_size, shuffle)

# 迭代获取数据
for features, labels in dataset:
    # 在这里进行模型训练或其他操作
    ...