title: ValueError: Cannot feed value of shape (64, 200, 75) for Tensor 'TargetsData/Y:0', which has shape '(200, 75)'
body: <p>I know this is a dumb question but I cant seem to figure it out. I feed in a numpy array of (?,200,75) and get this error:</p>
  
  <pre><code>ValueError: Cannot feed value of shape (64, 200, 75) for Tensor 'TargetsData/Y:0', which has shape '(200, 75)'
  </code></pre>
  
  <p>Here is my code:</p>
  
  <pre><code>import numpy as np
  import tflearn
  print("loading features....")
  features = np.load("features_xs.npy")
  print("loading classes....")
  classes = np.load("classes_xs.npy")
  
  symbols = ['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p'
  ,'q','r','s','t','u','v','w','x','y','z',
  'A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','R','S','T','U',
  'V','W','X','Y','Z','1','2','3','4','5','6','7','8','9','0','.',',',
  '!','?',':',';','\'','(',')','-','_',' ','"',]
  num_symbols = len(symbols)
  
  input_layer = tflearn.input_data(shape=[None, 200,num_symbols])
  input_layer = tflearn.flatten(input_layer)
  dense1 = tflearn.fully_connected(input_layer, 1000, activation='tanh',
                                   regularizer='L2', weight_decay=0.001)
  dense2 = tflearn.fully_connected(dense1, 2000, activation='tanh',
                                   regularizer='L2', weight_decay=0.001)
  dense2 = tflearn.fully_connected(dense2, 1000, activation='tanh',
                                   regularizer='L2', weight_decay=0.001)
  dropout2 = tflearn.dropout(dense2, 0.8)
  final = tflearn.fully_connected(dropout2, (200*num_symbols), activation='tanh')
  reshape = tflearn.reshape(final, [200,num_symbols], name="Reshape")
  
  Adam = tflearn.Adam(learning_rate=0.01)
  net = tflearn.regression(reshape, optimizer=Adam,
                           loss='categorical_crossentropy')
  
  # Training
  model = tflearn.DNN(net, tensorboard_verbose=0)
  model.fit(features, classes, n_epoch=1, show_metric=True, run_id="dense_model")
  model.save("model")
  </code></pre>
  
  <p>num_symbols is == to 75 in case you're wondering</p>
  
  <p>I can't find the solution please help thanks.</p>