I have programmed a multi-layer neural network but I'm getting an error while feeding my dimension into it. I'm getting a Value Error.

Here is The Code:

```
import pandas as pd
import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
from sklearn import datasets
from sklearn import metrics
from sklearn import model_selection
from sklearn import preprocessing

# In[207]:

df =pd.read_csv("train_data.csv")

# In[252]:

target = df["target"]
feat=df.drop(['target','connection_id'],axis=1)
target[189]

# In[209]:

len(feature.columns)

# In[210]:

logs_path="Server_attack"

# In[211]:

#Hyperparameters
batch_size=100
learning_rate=0.5
training_epochs=10

# In[244]:

X=tf.placeholder(tf.float32,[None,41])
Y_=tf.placeholder(tf.float32,[None,3])
lr=tf.placeholder(tf.float32)

# In[245]:

#5Layer Neural Network
L=200
M=100
N=60
O=30

# In[257]:

#Weights and Biases
W1=tf.Variable(tf.truncated_normal([41,L],stddev=0.1))
B1=tf.Variable(tf.ones([L]))
W2=tf.Variable(tf.truncated_normal([L,M],stddev=0.1))
B2=tf.Variable(tf.ones([M]))
W3=tf.Variable(tf.truncated_normal([M,N],stddev=0.1))
B3=tf.Variable(tf.ones([N]))
W4=tf.Variable(tf.truncated_normal([N,O],stddev=0.1))
B4=tf.Variable(tf.ones([O]))
W5=tf.Variable(tf.truncated_normal([O,3],stddev=0.1))
B5=tf.Variable(tf.ones([3]))               

# In[247]:

Y1=tf.nn.relu(tf.matmul(X,W1)+B1)
Y2=tf.nn.relu(tf.matmul(Y1,W2)+B2)
Y3=tf.nn.relu(tf.matmul(Y2,W3)+B3)
Y4=tf.nn.relu(tf.matmul(Y3,W4)+B4)
Ylogits=tf.nn.relu(tf.matmul(Y4,W5)+B5)
Y=tf.nn.softmax(Ylogits)

# In[216]:

cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=Ylogits,labels=Y_)
cross_entropy = tf.reduce_mean(cross_entropy)

# In[217]:

correct_prediction=tf.equal(tf.argmax(Y,1),tf.argmax(Y_,1))
accuracy=tf.reduce_mean(tf.cast(correct_prediction,tf.float32))

# In[218]:

train_step=tf.train.AdamOptimizer(learning_rate).minimize(cross_entropy)

# In[219]:

#TensorBoard Parameters
tf.summary.scalar("cost",cross_entropy)
tf.summary.scalar("accuracy",accuracy)
summary_op=tf.summary.merge_all()

# In[220]:

init = tf.global_variables_initializer()
sess=tf.Session()
sess.run(init)

# In[253]:

with tf.Session() as sess:
    sess.run(init)
    writer = tf.summary.FileWriter(logs_path,graph=tf.get_default_graph())
    for epoch in range(training_epochs):
        batch_count=int(len(feature)/batch_size)
        for i in range(batch_count):

            batch_x,batch_y=feature.iloc[i, :].values.tolist(),target[i]

            _,summary = sess.run([train_step,summary_op],
                                 {X:batch_x,Y:batch_y,learning_rate:0.001}
                                )

```

I'm getting the following error:

```
ValueError: Cannot feed value of shape (41,) for Tensor 'Placeholder_24:0', which has shape '(?, 41)'

```

I need to reshape I guess.