I have one bug I cannot find out the reason. Here is the code:
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 where np_data is the whole training samples read from hdf5 file, and the same to np_label.
After I run the code, I got the error like this :
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: So, It shows that for the step 0 it has the result, which means that the data has been fed into the Placeholders.
But why does it come the error of feeding data into Placeholder in the next time?
When I try to comment the code summary_op = tf.merge_all_summaries() and the code works fine. why is it the case?