这是我在TensorFlow上的第一次尝试：我正在使用多个输入构建线性回归模型。
问题是结果总是NaN ，我怀疑这是因为我是一个使用numpy和tensorflow进行矩阵运算的完整菜鸟（matlab background hehe）。
以下是代码：
import numpy as np
import tensorflow as tf
N_INP = 2
N_OUT = 1
# Model params
w = tf.Variable(tf.zeros([1, N_INP]), name='w')
b = tf.Variable(tf.zeros([1, N_INP]), name='b')
# Model input and output
x = tf.placeholder(tf.float32, [None, N_INP], name='x')
y = tf.placeholder(tf.float32, [None, N_OUT], name='y')
linear_model = tf.reduce_sum(x * w + b, axis=1, name='out')
# Loss as sum(error^2)
loss = tf.reduce_sum(tf.square(linear_model - y), name='loss')
# Create optimizer
optimizer = tf.train.GradientDescentOptimizer(0.01)
train = optimizer.minimize(loss, name='train')
# Define training data
w_real = np.array([-1, 4])
b_real = np.array([1, -5])
x_train = np.array([[1, 2, 3, 4], [0, 0.5, 1, 1.5]]).T
y_train = np.sum(x_train * w_real + b_real, 1)[np.newaxis].T
print('Real X:\n', x_train)
print('Real Y:\n', y_train)
# Create session and init parameters
sess = tf.Session()
sess.run(tf.global_variables_initializer())
# Training loop
train_data = {x: x_train, y: y_train}
for i in range(1000):
sess.run(train, train_data)
# Eval solution
w_est, b_est, curr_loss, y_pred = sess.run([w, b, loss, linear_model], train_data)
print("w: %s b: %s loss: %s" % (w_est, b_est, curr_loss))
print("y_pred: %s" % (y_pred,))
这是输出：
Real X:
[[ 1. 0. ]
[ 2. 0.5]
[ 3. 1. ]
[ 4. 1.5]]
Real Y:
[[-5.]
[-4.]
[-3.]
[-2.]]
w: [[ nan nan]] b: [[ nan nan]] loss: nan
y_pred: [ nan nan nan nan]
答案 0 :(得分：0)
您需要在<?php
include_once("../php/db_connection.php");
include_once("php/admin_session.php");
?>
<?php
// ADD NEW PROPERTY
$error_msg = '';
if(isset($_POST['title'])){
$title = $_POST['title'];
$names = $_POST['name'];
$description = $_POST['description'];
$price = $_POST['price'];
$category = $_POST['category'];
$location = $_POST['location'];
$map = $_POST['map'];
$img = "../rent_images/$names";
if(isset($_FILES['product_image'])){
foreach($_FILES['product_image']['tmp_name'] as $key => $tmp_name ){
$file_name = $key.$_FILES['product_image']['name'][$key];
$file_size =$_FILES['product_image']['size'][$key];
$file_tmp =$_FILES['product_image']['tmp_name'][$key];
$file_type=$_FILES['product_image']['type'][$key];
if($file_size > 2097152){
$error_msg ='File size must be less than 2 MB';
}
$desired_dir=$img;
if(empty($error_msg)==true){
if(is_dir($desired_dir)==false){
mkdir("$desired_dir", 0755); // Create directory if it does not exist
}
if(is_dir("$desired_dir/".$file_name)==false){
move_uploaded_file($file_tmp,"$desired_dir/".$file_name);
}
else{ // rename the file if another one exist
$new_dir="$desired_dir/".$file_name.time();
rename($file_tmp,$new_dir) ;
}
}
}
$sql_addProduct = mysqli_query($connection, "INSERT INTO rents(id,title,name,description,price,category,location,map,date_added) VALUES('','$title','$names','$description','$price','$category','$location','$map',now())");
if(!$sql_addProduct){
$error_msg = '<div class="atention">Couldn\'t upload the images or property details, please try again</div>';
}else{
header("location: property_list.php");
exit();
}
}
}
?>
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>Admin Panel</title>
<link rel="stylesheet" type="text/css" href="style/bootstrap.css">
<link rel="stylesheet" href="style/style.css" type="text/css" media="screen"/>
<script type="text/javascript" src="js/jquery-1.11.3.js"></script>
<script type="text/javascript" src="js/bootstrap.min.js"></script>
<script type="text/javascript">
$(function(){
var pull = $('#pull');
menu = $('nav ul');
menuHeight = menu.height();
$(pull).on('click', function(e){
e.preventDefault();
menu.slideToggle();
});
});
</script>
<script type="text/javascript">
$(window).resize(function(){
var w = $(window).width();
if(w > 320 && menu.is(':hidden')){
menu.removeAttr('style');
}
});
</script>
</head>
<body>
<div class="container">
<div>
<?php include_once("template/header.php"); ?>
</div>
<div class="row">
<p><a href="property_list.php"> Click Here Update Property</a></p>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr>
<td valign="top" width="100%">
<section id="main_content">
<h1>Add Product</h1>
<?php echo $error_msg; ?>
<form action="" method="post" enctype="multipart/form-data">
<input type="text" class="input-login" name="title" placeholder="Title" maxlength="100"><br><br>
<input type="text" class="input-login" name="name" placeholder="Name" maxlength="100"><br><br>
<textarea cols="50" rows="10" name="description" placeholder="Detailed description"></textarea><br><br>
<input type="text" class="input-login" name="price" placeholder="Price" maxlength="15"><br><br>
<input name="category" class="input-login" placeholder="Category" maxlength="50"><br><br>
<input name="location" class="input-login" placeholder="location" maxlength="50"><br><br>
<textarea cols="50" rows="10" name="map" class="input-login" placeholder="Insert Google map address"></textarea><br><br>
<input type="file" name="product_image[]" multiple title="Select property images"><br>
<br/>
<button id="submitBTN">Add Product</button>
</form>
</section>
</td>
</tr>
</table>
</div>
<div>
<?php include_once("../template/footer.php"); ?>
</div>
</div>
</body>
</html>
的定义中添加keep_dims=True。也就是说，
linear_model原因是否则结果会“变平”，您无法从中减去linear_model = tf.reduce_sum(x * w + b, axis=1, name='out',keep_dims=True)
。
例如，
y