Tong Tony
Reputation: 43
Tensorflow placeholder_2 error
I am writing a program to do some handwriting recognition using Tensorflow.
I followed the tutorial on the TF website, but there is some problem with my code.
Here is my code:
def weight_variable(shape):
initial = tf.truncated_normal(shape, stddev = 0.05)
return tf.Variable(initial)
def bias_variable(shape):
initial = tf.constant(0.1, shape = shape)
return tf.Variable(initial)
#x
x = tf.placeholder(tf.float32, shape = [None, 2500])
x_image = tf.reshape(x, [-1, 50, 50, 1])
#y
y_ = tf.placeholder(tf.float32, shape = [None, 10])
#useful layers
def conv2dsame(x, W, strides):
return tf.nn.conv2d(x, W, strides = strides, padding = 'SAME')
def conv2dvalid(x, W, strides):
return tf.nn.conv2d(x, W, strides = strides, padding = 'VALID')
def max_pool_2x2(x, strides):
return tf.nn.max_pool(x, ksize=[1,2,2,1], strides = strides, padding = 'SAME')
#hidden layer 1: conv layer
W_conv1 = weight_variable([12, 12, 1, 25])
b_conv1 = bias_variable([25])
h_conv1 = tf.nn.relu(conv2dvalid(x_image, W_conv1, [1,2,2,1])+b_conv1)
#hidden layer 2: conv layer
W_conv2 = weight_variable([5, 5, 25, 64])
b_conv2 = bias_variable([64])
h_conv2 = tf.nn.relu(conv2dvalid(h_conv1, W_conv2, [1,1,1,1])+b_conv2)
#hidden layer 3: 2x2 max pool
h_pool2 = max_pool_2x2(h_conv2, [1,2,2,1])
#hidden layer 4: fully-connected layer
W_fc1 = weight_variable([8*8*64, 1024])
b_fc1 = bias_variable([1024])
h_pool2_flat = tf.reshape(h_pool2, [-1, 8*8*64])
h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1)
keep_prob = tf.placeholder(tf.float32)
h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob)
#hidden layer 5: fully-connected layer
W_fc2 = weight_variable([1024, 10])
b_fc2 = bias_variable([10])
y_conv = tf.matmul(h_fc1_drop, W_fc2)+b_fc2
cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits = y_conv, labels = y_))
correct_prediction = tf.equal(tf.argmax(y_conv, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
sess = tf.Session()
sess.run(tf.global_variables_initializer())
iteration = 3000
for i in range(iteration):
batch = get_mini_batch(50)
if i%100 == 0:
train_accuracy = sess.run(accuracy, feed_dict={x:batch[0], y_:batch[1], keep_prob: 1.})
print ('step %d, training accuracy %g'%(i, train_accuracy))
sess.run(train_step, feed_dict={x:batch[0], y_:batch[1], keep_prob: 0.75})
val_set = get_mini_batch(50)
print ('test accuracy %g'%accuracy.eval(feed_dict={x:val_set[0], y:val_set[1], keep_prob: 1.0}, session=sess))
where get_mini_batch is a function which returns some mini-batch.
It returns the following error message:
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1038 try:
-> 1039 return fn(*args)
1040 except errors.OpError as e:
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1020 feed_dict, fetch_list, target_list,
-> 1021 status, run_metadata)
1022
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/contextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:
InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_2' with dtype float
[[Node: Placeholder_2 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-38-1b652368caea> in <module>()
6 batch = get_mini_batch(50)
7 if i%100 == 0:
----> 8 train_accuracy = sess.run(accuracy, feed_dict={x:batch[0], y_:batch[1], keep_prob: 1.})
9 print ('step %d, training accuracy %g'%(i, train_accuracy))
10 sess.run(train_step, feed_dict={x:batch[0], y_:batch[1], keep_prob: 0.75})
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
776 try:
777 result = self._run(None, fetches, feed_dict, options_ptr,
--> 778 run_metadata_ptr)
779 if run_metadata:
780 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
980 if final_fetches or final_targets:
981 results = self._do_run(handle, final_targets, final_fetches,
--> 982 feed_dict_string, options, run_metadata)
983 else:
984 results = []
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1030 if handle is None:
1031 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1032 target_list, options, run_metadata)
1033 else:
1034 return self._do_call(_prun_fn, self._session, handle, feed_dict,
/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1050 except KeyError:
1051 pass
-> 1052 raise type(e)(node_def, op, message)
1053
1054 def _extend_graph(self):
InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_2' with dtype float
[[Node: Placeholder_2 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op 'Placeholder_2', defined at:
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/__main__.py", line 3, in <module>
app.launch_new_instance()
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/traitlets/config/application.py", line 596, in launch_instance
app.start()
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 162, in start
super(ZMQIOLoop, self).start()
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tornado/ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 498, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-5-e240ef8f1b26>", line 22, in <module>
keep_prob = tf.placeholder(tf.float32)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py", line 1507, in placeholder
name=name)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1997, in _placeholder
name=name)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/ubuntu/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_2' with dtype float
[[Node: Placeholder_2 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
I googled this message and nothing is helpful. I think it might because of the dropout layer, but I have already put keep_prob in feed_dict.
What does 'Placeholder_2' actually mean?
Can anyone help me?
Upvotes: 1
Views: 267
Answers (1)
Miriam Farber
Reputation: 19634
In your last row, replace y with y_. That is, you need to have:
print ('test accuracy %g'%accuracy.eval(feed_dict={x:val_set[0], y_:val_set[1], keep_prob: 1.0}, session=sess))
This is because you defined the associated placeholder as follows:
y_ = tf.placeholder(tf.float32, shape = [None, 10])
so the variable y does not exist in your code.
Upvotes: 1
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