InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1'

Question

I trained a simple neural network with TensorFlow on the MNIST dataset. The training portion of the code works fine. However, when I feed a single image into the network, it gives me the following traceback:

Traceback (most recent call last):
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1021, in _do_call
    return fn(*args)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1003, in _run_fn
    status, run_metadata)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/contextlib.py", line 88, in __exit__
    next(self.gen)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 469, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1' with dtype float
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "tfbasics.py", line 113, in <module>
    classification = sess.run(y, feed_dict)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 766, in run
    run_metadata_ptr)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 964, in _run
    feed_dict_string, options, run_metadata)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1014, in _do_run
    target_list, options, run_metadata)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1034, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1' with dtype float
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'Placeholder_1', defined at:
  File "tfbasics.py", line 20, in <module>
    y = tf.placeholder('float') #labels
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1587, in placeholder
    name=name)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 2043, in _placeholder
    name=name)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
    op_def=op_def)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1128, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_1' with dtype float
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Here are my variables:

x = tf.placeholder('float', shape = [None, 784]) 
y = tf.placeholder('float') #labels

Here is where I am trying to input a single number (randomly chosen from the dataset):

#pick random number
num = randint(0, mnist.test.images.shape[0])
img = mnist.test.images[num]

#format the image
inp = np.asarray(img)
inp = np.transpose(inp)
image = np.expand_dims(inp, axis=0) # shape  : (1, 784)


#feed the image into the session
with tf.Session() as sess:
    feed_dict = {x: image}
    classification = sess.run(y, feed_dict)
    print(classification)

Any help would be appreciated! I am new to TensorFlow.

Answer 1

If you are still getting the same error even after feeding the right numpy shape and also maintaining the correct dtypes (np.int32 or np.float32) as suggested by the error message, then the following code should solve your problem:

#this code will print the list of placeholders and other variables declared in the memory which is causing your error
[n.name for n in tf.get_default_graph().as_graph_def().node] 
#it will reset your declared placeholders so you can start over
tf.reset_default_graph()

This similar problem could be solved by restarting the kernel repeatedly for each debug however it's not feasible.

Answer 2

In your code y is a placeholder:

x = tf.placeholder('float', shape = [None, 784]) 
y = tf.placeholder('float') #labels

When you tell tensorflow sess.run(y, ...), it's computing the placeholder value, not the inference value (that's the tensor that y is compared to in the loss function). That's why it's complaining.

What you want to compute instead is the predicted y value. It's not in your code snippet, but since the training works, there should be one. This tensor depends on x, so it can be evaluated just by feeding x value.

Answer 3

Your feed_dict only put value for the x and not for the label. you should also put for the y place_holder i.e.: {x:image, y:val}