Tensorflow InvalidArgumentError（上記のトレースバック参照）：最小テンソルランク：2しかし、得られた：1

Question

TensorFlowを初めて使用しており、CIFAR-10データセットの画像を分類するアルゴリズムを作成しようとしています。私はこのエラーを取得しています：ここで

InvalidArgumentError (see above for traceback): Minimum tensor rank: 2 but got: 1 

は私のコードです：

Traceback (most recent call last): 
    File "cifar_10.py", line 72, in <module> 
    train_neural_network(x) 
    File "cifar_10.py", line 69, in train_neural_network 
    accuracy = accuracy.eval({x:test_data['data'],y:test_data['labels']}) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 559, in eval 
    return _eval_using_default_session(self, feed_dict, self.graph, session) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3761, in _eval_using_default_session 
    return session.run(tensors, feed_dict) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 717, in run 
    run_metadata_ptr) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 915, in _run 
    feed_dict_string, options, run_metadata) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 965, in _do_run 
    target_list, options, run_metadata) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 985, in _do_call 
    raise type(e)(node_def, op, message) 
tensorflow.python.framework.errors.InvalidArgumentError: Minimum tensor rank: 2 but got: 1 
    [[Node: ArgMax_1 = ArgMax[T=DT_INT64, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_Placeholder_1_0, ArgMax_1/dimension)]] 

Caused by op u'ArgMax_1', defined at: 
    File "cifar_10.py", line 72, in <module> 
    train_neural_network(x) 
    File "cifar_10.py", line 65, in train_neural_network 
    correct = tf.equal(tf.argmax(prediction,1), tf.argmax(y,1)) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 166, in arg_max 
    name=name) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 749, in apply_op 
    op_def=op_def) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2380, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/home/mddrill/anaconda2/envs/python27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1298, in __init__ 
    self._traceback = _extract_stack() 

InvalidArgumentError (see above for traceback): Minimum tensor rank: 2 but got: 1 
    [[Node: ArgMax_1 = ArgMax[T=DT_INT64, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_Placeholder_1_0, ArgMax_1/dimension)]] 

私はエラーが発生している場所の上にマークされました：ここ

import tensorflow as tf 
from tensorflow.examples.tutorials.mnist import input_data 
import cPickle 

n_nodes_hl1 = 500 
n_nodes_hl2 = 500 
n_nodes_hl3 = 500 

n_classes = 10 
batch_size = 100 
image_size = 32*32*3 # because 3 channels 

x = tf.placeholder('float', shape=(None, image_size)) 
y = tf.placeholder(tf.int64) 

with open('test_batch','rb') as f: 
    test_data = cPickle.load(f) 
    print test_data 
def neural_network_model(data): 
    hidden_1_layer = {'weights':tf.Variable(tf.random_normal([image_size, n_nodes_hl1])), 'biases':tf.Variable(tf.random_normal([n_nodes_hl1]))} 
    hidden_2_layer = {'weights':tf.Variable(tf.random_normal([n_nodes_hl1, n_nodes_hl2])), 'biases':tf.Variable(tf.random_normal([n_nodes_hl2]))} 
    hidden_3_layer = {'weights':tf.Variable(tf.random_normal([n_nodes_hl2, n_nodes_hl3])), 'biases':tf.Variable(tf.random_normal([n_nodes_hl3]))} 
    output_layer = {'weights':tf.Variable(tf.random_normal([n_nodes_hl3, n_classes])), 'biases':tf.Variable(tf.random_normal([n_classes]))} 
    # input_data * weights + biases 
    l1 = tf.add(tf.matmul(data, hidden_1_layer['weights']), hidden_1_layer['biases']) 
    # activation function 
    l1 = tf.nn.relu(l1) 

    l2 = tf.add(tf.matmul(l1, hidden_2_layer['weights']), hidden_2_layer['biases']) 
    l2 = tf.nn.relu(l2) 

    l3 = tf.add(tf.matmul(l2, hidden_3_layer['weights']), hidden_3_layer['biases']) 
    l3 = tf.nn.relu(l3) 

    output = tf.matmul(l3, output_layer['weights']) + output_layer['biases'] 
    return output 

def train_neural_network(x): 
    prediction = neural_network_model(x) 
    cost = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(prediction, tf.squeeze(y))) 
    #learning rate = 0.001 
    optimizer = tf.train.AdamOptimizer().minimize(cost) 
    hm_epochs = 10 
    with tf.Session() as sess: 
     sess.run(tf.initialize_all_variables()) 
     for epoch in range(hm_epochs): 
      epoch_loss = 0 
      for i in range(5): 
       with open('data_batch_'+str(i+1),'rb') as f: 
        train_data = cPickle.load(f) 
       _, c = sess.run([optimizer, cost], feed_dict={x:train_data['data'],y:train_data['labels']}) 
       epoch_loss += c 
      print 'Epoch ' + str(epoch) + ' completed out of ' + str(hm_epochs) + ' loss: ' + str(epoch_loss) 
     correct = tf.equal(tf.argmax(prediction,1), tf.argmax(y,1))//THIS IS THE LINE WHERE THE ERROR OCCURS 
     accuracy = tf.reduce_mean(tf.cast(correct, 'float')) 
     with open('test_batch','rb') as f: 
      test_data = cPickle.load(f) 
      accuracy = accuracy.eval({x:test_data['data'],y:test_data['labels']}) 
     print 'Accuracy: ' + str(accuracy) 

train_neural_network(x) 

はトレースバックです。 correct = tf.equal(tf.argmax(prediction,1), tf.argmax(y,1))という行にあります。なぜ私はこれを手に入れているのですか？どうすれば修正できますか？ tf.argmaxの公式TensorFlowのドキュメントからの引用

Answer 1

、

axis: A Tensor. Must be one of the following types: int32, int64. int32, 0 <= axis < rank(input). Describes which axis of the input Tensor to reduce across. For vectors, use axis = 0.

argmax()の1ランク<=1でinputを持っているので、あなたはこのエラーを取得しています。 axis=1を渡すので、有効な出力を得るには、rank> 1のテンソルを渡す必要があります。これはtf.argmax(y, 1)のbecuaseであるよう

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あなたのコードをより詳しく見ると、それはそうです。 1の代わりに0またはNoneを渡すようにしてください。