嗨，我有一个while循环，打印出来自表用户的所有用户名，名称等，但我需要的是一个按钮，可以运行查询，删除该行上的用户ID，所以基本上在最后对于每个用户的行，应该有一个删除按钮，该按钮仅删除该用户但不刷新页面。到目前为止我有这个
# text_dcnn.py
import tensorflow as tf
class TextDCNN(object):
"""
A CNN for NLP tasks. Architecture is as follows:
Embedding layer, conv layer, max-pooling and softmax layer
"""
def __init__(self, sequence_lengths, num_classes, vocab_size, embedding_size, filter_sizes, num_filters):
"""
Makes a new CNNClassifier
Args:
sequence_length: The length of each sentence
num_classes: Number of classes in the output layer (positive and negative would be 2 classes)
vocab_size: The size of the vocabulary, needed to define the size of the embedding layer
embedding_size: Dimensionality of the embeddings
filter_sizes: Number of words the convolutional filters will cover, there will be num_filters for each size
specified.
num_filters: The number of filters per filter size.
Returns: A new CNNClassifier with the given parameters.
"""
# Define the inputs and the dropout
self.max_length = max([l for l in sequence_lengths])
self.input_x = tf.placeholder(tf.int32, [None, self.max_length], name="input_x")
self.input_y = tf.placeholder(tf.float32, [None, num_classes], name="input_y")
self.dropout_keep_prob = tf.placeholder(tf.float32, name="dropout_keep_prob")
# Runs the operations on the CPU and organizes them into an embedding scope
with tf.device("/cpu:0"), tf.name_scope("embedding"):
W = tf.Variable( # Make a 4D tensor to store batch, width, height, and channel
tf.random_uniform([vocab_size, embedding_size], -1.0, 1.0),
name="W"
)
self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x)
self.embedded_chars_expanded = tf.expand_dims(self.embedded_chars, -1)
pooled_outputs = []
for i, filter_size in enumerate(filter_sizes):
with tf.name_scope("conv-maxpool-%s" % filter_size):
# Conv layer
filter_shape = [filter_size, embedding_size, 1, num_filters]
# W is the filter matrix
W = tf.Variable(tf.truncated_normal(filter_shape, stddev=0.1), name="W")
b = tf.Variable(tf.constant(0.1, shape=[num_filters]), name="b")
conv = tf.nn.conv2d(
self.embedded_chars_expanded,
W,
strides=[1, 1, 1, 1],
padding="VALID",
name="conv"
)
# Apply nonlinearity
h = tf.nn.relu(tf.nn.bias_add(conv, b), name="relu")
# Max-pooling layer over the outputs
pooled = tf.nn.max_pool(
h,
ksize=[1, sequence_lengths[i] - filter_size + 1, 1, 1],
strides=[1, 1, 1, 1],
padding="VALID",
name="pool"
)
pooled_outputs.append(pooled)
# Combine all of the pooled features
num_filters_total = num_filters * len(filter_sizes)
pooled_outputs = [tf.reshape(out, [-1, 94, 1, self.max_length]) for out in pooled_outputs]
self.h_pool = tf.concat(3, pooled_outputs)
# self.h_pool = tf.concat(3, pooled_outputs)
self.h_pool_flat = tf.reshape(self.h_pool, [-1, num_filters_total])
# Add dropout
with tf.name_scope("dropout"):
# casted = tf.cast(self.dropout_keep_prob, tf.int32)
self.h_drop = tf.nn.dropout(self.h_pool_flat, self.dropout_keep_prob)
# Do raw predictions (no softmax)
with tf.name_scope("output"):
W = tf.Variable(tf.truncated_normal([num_filters_total, num_classes], stddev=0.1), name="W")
b = tf.Variable(tf.constant(0.1, shape=[num_classes]), name="b")
# xw_plus_b(...) is just Wx + b matmul alias
self.scores = tf.nn.xw_plus_b(self.h_drop, W, b, name="scores")
self.predictions = tf.argmax(self.scores, 1, name="predictions")
# Calculate mean cross-entropy loss
with tf.name_scope("loss"):
# softmax_cross_entropy_with_logits(...) calculates cross-entropy loss
losses = tf.nn.softmax_cross_entropy_with_logits(self.scores, self.input_y)
self.loss = tf.reduce_mean(losses)
# Calculate accuracy
with tf.name_scope("accuracy"):
correct_predictions = tf.equal(self.predictions, tf.argmax(self.input_y, 1))
self.accuracy = tf.reduce_mean(tf.cast(correct_predictions, "float"), name="accuracy")
但我遇到的问题是，如果我把这行代码：
while($row = mysql_fetch_array($theuser)){
$accid = $row["account_id"];
echo '<tr><td>'.$row["username"].'</td>
<td>'.$row["name"].'</td>
<td>'.$row["l_name"].'</td>
<td>'.$row["email"].'</td>
<td>'.$row["phone"].'</td>
<td><form action="" method="post" >
<input class="button" type="submit" name="submitdelete" value="delete"></form></td></tr>';}
在while循环中，它将删除所有用户。如果我把它放在while循环之外它就不会得到id。
有没有办法例如写输入的名称，如： name =“submitdelete34”和34表示用户的id，因此在while循环中它的编码如下：
if(isset($_POST['submitdelete'])){
mysql_query("Delete from users where account_id='$accid'");
}
并使其发挥作用。
请帮帮我
答案 0 :(得分：1)
让它变得更容易。让我们添加一个隐藏的输入：
<input type="hidden" name="account_id" value="<?php echo $accid;?>">
<input class="button" type="submit" name="submitdelete" value="delete">
现在在你的php中你可以获得id：
$connection = mysqli_connect("my_host", "my_user", "my_password", "my_db");
// simple error handler
if (!$connection){
echo "SQL connection failed: ". mysqli_error($connection);
exit;
}
if(isset($_POST['submitdelete'])){
$acctid = (int) $_POST['account_id'];// <-- gotta protect from sql injection.
mysqli_query($connection, "Delete from users where account_id='$accid'");
}
<强> BUT：
更好的解决方案是不删除记录。你桌子上的一个字段可以叫做“活跃”字样。并且您可以将其设置为TINYINT。通过这种删除记录的方式，您可以设置active=0。
如果您误删了，可以随时将其重新设置为active=1
注意我使用了mysqli_而不是mysql_。您需要将代码全部更新为mysqli_，因为the other is deprecated。它已从较新版本的php中删除
答案 1 :(得分：-1)
使用mysql_fetch_assoc
while($row = mysql_fetch_assoc($theuser)){
echo '<tr><td>'.$row["username"].'</td>
<td>'.$row["name"].'</td>
<td>'.$row["l_name"].'</td>
<td>'.$row["email"].'</td>
<td>'.$row["phone"].'</td>
<td><form action="" method="post" >
<input type="hidden" name="accid" value="'.$row["account_id"].'" />
<input class="button" type="submit" name="submitdelete" value="delete"></td></tr>';
}
echo "</form>";
动作php脚本：
if($_POST['submitdelete']=='delete'){
mysql_query("delete from users where account_id='{$_POST["accid"]}'");
}