Tensorflow.python.framework.errors_impl. Invalidargumenterror:you must feed a value for placeholder tensor ' x_1 ' with dtype float and shape [?, 227,227,3]

Remember the super stupid super-torture my bug.

Error content:

Tensorflow.python.framework.errors_impl. Invalidargumenterror:you must feed a value for placeholder tensor ' x_1 ' with dtype float and shape [?, 227,227,3]
[[node:x_1 = Placeholder[dtype=dt_float, shape=[?,227,227,3], _device= "/job:localhost/replica:0/task:0/device:gpu : 0 "] ()]
[[node:fc3/_33 = _recv[client_terminated=false, recv_device= "/job:localhost/replica:0/task:0/device:cpu:0", Send_ Device= "/job:localhost/replica:0/task:0/device:gpu:0", Send_device_incarnation=1, Tensor_name= "EDGE_110_FC3", Tensor_type=dt_float, _device= "/job:localhost/replica:0/task:0/device:cpu:0"] ()]

The error is simple to understand and does not give placeholder ' x_1 ' assignment.

Here is my forecast code:

Image = Image.open (imagefile)
Image = Image.resize ([227, 227])
Image_array = Np.array (image)
Image_array = Image_array.astype (float)
Image = Np.reshape (Image_array, [1, 227, 227, 3])
Saver = tf.train.import_meta_graph ("/home/ubuntu/demo/package/5.8_2000op_256batch/alexnetmodel.ckpt.meta")
Graph = Tf.get_default_graph ()
Prediction = Graph.get_tensor_by_name ("fc3:0")
x = Graph.get_tensor_by_name ("x:0")
With TF. Session () as Sess:
Saver.restore (Sess, "/home/ubuntu/demo/package/5.8_2000op_256batch/alexnetmodel.ckpt")
Predict = Sess.run (prediction, Feed_dict={x:image})
Max_index = Np.argmax (Predict)
If max_index==0:
Return "Cat"
Else
Return "Dog"

Previously, there was a problem with the image format and could not be entered as input to X.

Because the most original, the source code is written like this:

Image = Image.open (imagefile)
Image = Image.resize ([227, 227])
Image_array = Np.array (image)

Image = Tf.cast (image_array,tf.float32)
Image = Tf.image.per_image_standardization (image)
Image = Tf.reshape (image, [1, 227, 227, 3])

Instead of using the TF method, the return value is a tensor, and tensor is a data type that cannot be assigned to a placeholder definition.

• Sess.run () The first parameter is the variable to fetch, the type of the variable can only be tensor or string, if you want to add feed_dict = {} , note that the data type of the feed can be Python scalars, strings, lists, NumPy Ndarrays, or tensorhandles, cannot be tensor.fecth to get the variable is <type ‘numpy.ndarray‘> . The bottom line is that when you run the diagram, the tensor is sess.run() taken out and then feeds in.

So the shape of the image changes, Tf.reshape () changed to Np.reshape (), but there is a problem, error for the above you must feed a value for placeholder tensor ' x_1 ' with Dtype Flo At and shape [?, 227,227,3] ....

Finished completely put me whole, do not know what kind of input to x, but it is very strange, placeholder tensor ' x_1 ' there, has not defined ' x_1 ' this kind of thing ah. Post the training code, placeholder the application.

x = Tf.placeholder (Tf.float32, [None, 227, 227, 3],name= ' x ')
y = Tf.placeholder (Tf.float32, [None, n_classes])

The feeling is ok ah, very good ah. If the code really does not have a problem really good, the key is their brain residue, x = Tf.placeholder (Tf.float32, [None, 227, 227, 3],name= ' x ') applied two times

Remove one. It's OK. Very annoying, troubled myself for several days

Tensorflow.python.framework.errors_impl. Invalidargumenterror:you must feed a value for placeholder tensor ' x_1 ' with dtype float and shape [?, 227,227,3]