csvのデータをTensorFlowに正しく読み込む方法

Question

this so postingは、キューを使用してcsvファイルを読み込むコードを設定する方法を教えてくれました。しかし、私はそれを実行するたびに、私はエラーに遭遇する。私はそれをデバッグしようとしましたが、エラーの意味を理解することはできません。誰か助けてくれますか？

私が使用しているコードは、上記の記事で掲載されたものはほとんどそのままです：

import tensorflow as tf 

dataset = '/Users/hdadmin/Data/actions/testing.csv' 

def file_len(fname): 
    with open(fname) as f: 
     for i, l in enumerate(f): 
      pass 
    return i + 1 

def read_from_csv(filename_queue): 
    reader = tf.TextLineReader(skip_header_lines=1) 
    _, csv_row = reader.read(filename_queue) 
    record_defaults = [[0],[0],[0],[0],[0]] 
    colHour,colQuarter,colAction,colUser,colLabel = tf.decode_csv(csv_row, record_defaults=record_defaults) 
    features = tf.pack([colHour,colQuarter,colAction,colUser]) 
    label = tf.pack([colLabel]) 
    return features, label 

def input_pipeline(batch_size, num_epochs=None): 
    filename_queue = tf.train.string_input_producer([dataset], num_epochs=num_epochs, shuffle=True) 
    example, label = read_from_csv(filename_queue) 
    min_after_dequeue = 1000 
    capacity = min_after_dequeue + 3 * batch_size 
    example_batch, label_batch = tf.train.shuffle_batch(
     [example, label], batch_size=batch_size, capacity=capacity, 
     min_after_dequeue=min_after_dequeue) 
    return example_batch, label_batch 

file_length = file_len(dataset) - 1 
examples, labels = input_pipeline(file_length, 1) 

with tf.Session() as sess: 
    tf.initialize_all_variables().run() 

    # start populating filename queue 
    coord = tf.train.Coordinator() 
    threads = tf.train.start_queue_runners(coord=coord) 

    try: 
    while not coord.should_stop(): 
     example_batch, label_batch = sess.run([examples, labels]) 
     print(example_batch) 
    except tf.errors.OutOfRangeError: 
    print('Done training, epoch reached') 
    finally: 
    coord.request_stop() 

    coord.join(threads) 

私は取得していますエラーは次のとおりです。

E tensorflow/core/client/tensor_c_api.cc:485] Attempting to use uninitialized value input_producer/limit_epochs/epochs 
    [[Node: input_producer/limit_epochs/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@input_producer/limit_epochs/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/cpu:0"](input_producer/limit_epochs/epochs)]] 
E tensorflow/core/client/tensor_c_api.cc:485] RandomShuffleQueue '_2_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 10000, current size 0) 
    [[Node: shuffle_batch = QueueDequeueMany[_class=["loc:@shuffle_batch/random_shuffle_queue"], component_types=[DT_INT32, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]] 
Done training, epoch reached 
E tensorflow/core/client/tensor_c_api.cc:485] FIFOQueue '_0_input_producer' is closed and has insufficient elements (requested 1, current size 0) 
    [[Node: ReaderRead = ReaderRead[_class=["loc:@TextLineReader", "loc:@input_producer"], _device="/job:localhost/replica:0/task:0/cpu:0"](TextLineReader, input_producer)]] 
E tensorflow/core/client/tensor_c_api.cc:485] Queue '_2_shuffle_batch/random_shuffle_queue' is already closed. 
    [[Node: shuffle_batch/random_shuffle_queue_Close = QueueClose[_class=["loc:@shuffle_batch/random_shuffle_queue"], cancel_pending_enqueues=false, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch/random_shuffle_queue)]] 
Traceback (most recent call last): 
    File "csv_test.py", line 49, in <module> 
    coord.join(threads) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/coordinator.py", line 357, in join 
    six.reraise(*self._exc_info_to_raise) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/queue_runner.py", line 185, in _run 
    sess.run(enqueue_op) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 382, in run 
    run_metadata_ptr) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 655, in _run 
    feed_dict_string, options, run_metadata) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 723, in _do_run 
    target_list, options, run_metadata) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 743, in _do_call 
    raise type(e)(node_def, op, message) 
tensorflow.python.framework.errors.FailedPreconditionError: Attempting to use uninitialized value input_producer/limit_epochs/epochs 
    [[Node: input_producer/limit_epochs/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@input_producer/limit_epochs/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/cpu:0"](input_producer/limit_epochs/epochs)]] 
Caused by op u'input_producer/limit_epochs/CountUpTo', defined at: 
    File "csv_test.py", line 31, in <module> 
    examples, labels = input_pipeline(file_length, 1) 
    File "csv_test.py", line 21, in input_pipeline 
    filename_queue = tf.train.string_input_producer([dataset], num_epochs=num_epochs, shuffle=True) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 194, in string_input_producer 
    summary_name="fraction_of_%d_full" % capacity) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 133, in input_producer 
    input_tensor = limit_epochs(input_tensor, num_epochs) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 84, in limit_epochs 
    counter = epochs.count_up_to(num_epochs) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 577, in count_up_to 
    return state_ops.count_up_to(self._variable, limit=limit) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_state_ops.py", line 127, in count_up_to 
    result = _op_def_lib.apply_op("CountUpTo", ref=ref, limit=limit, name=name) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 703, in apply_op 
    op_def=op_def) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2310, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/usr/local/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1232, in __init__ 
    self._traceback = _extract_stack() 

私は5で構成されるデータを作りました例と一致する列。

"v1","v2","v3","v4","v5" 
1,1,1,3,10 
4,2,1,10,8 
1,4,1,9,3 
3,3,1,1,5 
3,4,1,4,3 
3,2,1,5,8 
1,1,1,9,7 
4,1,1,4,9 
2,3,1,8,4 

ありがとうございました。

Answer 1

あなたが欠けているものは、ローカルの変数の初期化です（たとえばinput_producer/limit_epochs/epochs）。ローカル変数は、すべて変数の初期化中に初期化されません.btwは非常に混乱します。

あなたが一度にすべてを初期化します、次の初期化操作を追加することができます

init_op = tf.group(tf.initialize_all_variables(), 
        tf.initialize_local_variables()) 

をしてから：

sess.run(init_op)