tensorflow InvalidArgumentError: You must feed a value for placeholder tensor with dtype float
<p>I am new to tensorflow and want to train a logistic model for classification.</p>

<pre><code># Set model weights
W = tf.Variable(tf.zeros([30, 16]))
b = tf.Variable(tf.zeros([16]))
train_X, train_Y, X, Y = input('train.csv')

#construct model
pred = model(X, W, b)
# Minimize error using cross entropy
cost = tf.reduce_mean(-tf.reduce_sum(Y*tf.log(pred), reduction_indices=1))
# Gradient Descent
learning_rate = 0.1
#optimizer = tf.train.AdamOptimizer(learning_rate).minimize(cost)
optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)
# Initializing the variables
init = tf.initialize_all_variables()

get_ipython().magic(u'matplotlib inline')
import collections
import matplotlib.pyplot as plt

training_epochs = 200
batch_size = 300
train_X, train_Y, X, Y = input('train.csv')
acc = []
x = tf.placeholder(tf.float32, [None, 30]) 
y = tf.placeholder(tf.float32, [None, 16])
with tf.Session() as sess:
     sess.run(init)
     # Training cycle
     for epoch in range(training_epochs):
         avg_cost = 0.0
         #print(type(y_train[0][0]))
         print(type(train_X))
         print(type(train_X[0][0]))
         print X
         _, c = sess.run([optimizer, cost], feed_dict = {x: train_X, y: train_Y})
</code></pre>

<p>The feef_dict method does not work, with the complain: <strong>InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_54' with dtype float
     [[Node: Placeholder_54 = Placeholderdtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]]
Caused by op u'Placeholder_54':</strong></p>

<p>I check the data type, for the training feature data X:</p>

<pre><code>  train_X type: &lt;type 'numpy.ndarray'&gt;
  train_X[0][0]: &lt;type 'numpy.float32'&gt;
  train_X size: (300, 30)
  place_holder info : Tensor("Placeholder_56:0", shape=(?, 30), dtype=float32)
</code></pre>

<p>I do not know why it complains. Hope sb could help, thanks</p>

<p>Show the code for model() - I bet it defines two placeholders: X is placeholder_56, so where is placeholder_54 coming from?</p>

<p>Then pass the model x,y into the feed_dict, delete your x, y global placeholders, all will work :)</p>

python types tensorflow