我有一个错误，我找不到原因。这是代码:
with tf.Graph().as_default():
global_step = tf.Variable(0, trainable=False)
images = tf.placeholder(tf.float32, shape = [FLAGS.batch_size,33,33,1])
labels = tf.placeholder(tf.float32, shape = [FLAGS.batch_size,21,21,1])
logits = inference(images)
losses = loss(logits, labels)
train_op = train(losses, global_step)
saver = tf.train.Saver(tf.all_variables())
summary_op = tf.merge_all_summaries()
init = tf.initialize_all_variables()
sess = tf.Session()
sess.run(init)
summary_writer = tf.train.SummaryWriter(FLAGS.train_dir, sess.graph)
for step in xrange(FLAGS.max_steps):
start_time = time.time()
data_batch, label_batch = SRCNN_inputs.next_batch(np_data, np_label,
FLAGS.batch_size)
_, loss_value = sess.run([train_op, losses], feed_dict={images: data_batch, labels: label_batch})
duration = time.time() - start_time
def next_batch(np_data, np_label, batchsize,
training_number = NUM_EXAMPLES_PER_EPOCH_TRAIN):
perm = np.arange(training_number)
np.random.shuffle(perm)
data = np_data[perm]
label = np_label[perm]
data_batch = data[0:batchsize,:]
label_batch = label[0:batchsize,:]
return data_batch, label_batch
其中np_data是从hdf5文件中读取的全部训练样本，np_label同理。
运行代码后，出现如下错误:
2016-07-07 11:16:36.900831: step 0, loss = 55.22 (218.9 examples/sec; 0.585 sec/batch)
Traceback (most recent call last):
File "<ipython-input-1-19672e1f8f12>", line 1, in <module>
runfile('/home/kang/Documents/work_code_PC1/tf_SRCNN/SRCNN_train.py', wdir='/home/kang/Documents/work_code_PC1/tf_SRCNN')
File "/usr/lib/python3/dist-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 685, in runfile
execfile(filename, namespace)
File "/usr/lib/python3/dist-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 85, in execfile
exec(compile(open(filename, 'rb').read(), filename, 'exec'), namespace)
File "/home/kang/Documents/work_code_PC1/tf_SRCNN/SRCNN_train.py", line 155, in <module>
train_test()
File "/home/kang/Documents/work_code_PC1/tf_SRCNN/SRCNN_train.py", line 146, in train_test
summary_str = sess.run(summary_op)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 372, in run
run_metadata_ptr)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 636, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 708, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 728, in _do_call
raise type(e)(node_def, op, message)
InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder' with dtype float and shape [128,33,33,1]
[[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[128,33,33,1], _device="/job:localhost/replica:0/task:0/gpu:0"]()]]
[[Node: truediv/_74 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_56_truediv", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op 'Placeholder', defined at:
所以，它表明对于第 0 步它有结果，这意味着数据已被输入到占位符中。
但是为什么下次往Placeholder feed data的时候会报错呢？
当我尝试注释代码 summary_op = tf.merge_all_summaries() 并且代码工作正常。为什么会这样？
最佳答案
When I try to comment the code summary_op = tf.merge_all_summaries() and the code works fine. why is it the case?
summary_op 是一个操作。如果存在(在您的情况下确实如此)与取决于占位符值的另一个操作的结果相关的汇总操作，则您必须为图形提供所需的值。
因此，您的代码行 summary_str = sess.run(summary_op) 需要要存储值的字典。
通常，您不是重新执行操作来记录值，而是运行一次操作和 summary_op。
做类似的事情
if step % LOGGING_TIME_STEP == 0:
_, loss_value, summary_str = sess.run([train_op, losses, summary_op], feed_dict={images: data_batch, labels: label_batch})
else:
_, loss_value = sess.run([train_op, losses], feed_dict={images: data_batch, labels: label_batch})
关于python - Tensorflow:提要字典错误:您必须为占位符张量提供一个值，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/38243194/