title: TensorFlow Cannot feed value of shape (100, 784) for Tensor 'Placeholder:0'
body: <p>I am learning TensorFLow. So to understand how to make something, I tried to copy some code from a source and execute it. But I'm hitting an error message. So I tried some solution from this website but it does not work (I kept my test in comments). </p>
  
  <pre><code>    """programme 1 """
  import tensorflow as tf 
  import numpy as np
  
  from tensorflow.examples.tutorials.mnist import input_data
  mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
  
  
  
  
  
  X = tf.placeholder(tf.float32,[None, 28, 28, 1]) #28 * 28 taille image 1 = 1pixel car noir et blanc "X" valeur
  W = tf.Variable(tf.zeros([784, 10])) # 28*28 = 784 , 10 -&gt; 0 à 9  "W" = weight = poid
  b = tf.Variable(tf.zeros([10])) #chiffre de 0 à 9 a reconnaitre "b" = constante 
  init = tf.initialize_all_variables()
  
  #model
  Y = tf.nn.softmax(tf.matmul(tf.reshape(X,[-1, 784]), W) + b) #fonction "matmul": produit matriciel "-1": reussite obligatoire
  
  #Place holder
  Y_ = tf.placeholder(tf.float32, [None, 10])
  
  #loss function
  cross_entropy = -1 * tf.reduce_sum(Y_ * tf.log(Y)) #formule
  
  # % of correct annwer found in batch
  is_correct = tf.equal(tf.argmax(Y,1),tf.argmax(Y_,1))
  accuracy = tf.reduce_mean(tf.cast(is_correct,tf.float32))
  
  #training step
  optimizer = tf.train.GradientDescentOptimizer(0.003) #petit pas
  train_step = optimizer.minimize(cross_entropy)
  
  sess = tf.Session()
  sess.run(init) 
  
  for i in range(10000):
      #load batch of image and ocrrects answer
      batch_X, batch_Y = mnist.train.next_batch(100)
      batch_X = np.reshape(batch_X, (-1, 784))
      #batch_Y = np.reshape(batch_Y, (-1, 784))
  
      train_data = {X: batch_X, Y_: batch_Y}
  
      #train
      sess.run(train_step, feed_dict=train_data)
  
      a,c = sess.run([accuracy,cross_entropy],feed = train_data)
  
      test_data = {X:mnist.test.images, Y_:mnist.test.labels}
      a,c = sess.run([accuracy,cross_entropy],feed = test_data)
  </code></pre>
  
  <p>the log :</p>
  
  <pre><code>    Traceback (most recent call last):
    File "d:\tensorflow\test1.py", line 46, in &lt;module&gt;
      sess.run(train_step, feed_dict=train_data)
    File "C:\Users\Proprietaire\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 895, in run
      run_metadata_ptr)
    File "C:\Users\Proprietaire\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1100, in _run
      % (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
  ValueError: Cannot feed value of shape (100, 784) for Tensor 'Placeholder:0', which has shape '(?, 28, 28, 1)'
  2017-08-30 19:07:37.406994: W C:\tf_jenkins\home\workspace\rel-win\M\windows\PY\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
  </code></pre>
  
  <p>line 46 is </p>
  
  <pre><code>sess.run(train_step, feed_dict=train_data)
  </code></pre>
  
  <p>What can I do to resolve this error?</p>