Question

我正在使用一个Alexnet，用5个类的花数据进行微调。现在，我想预测使用微调模型。下面显示的是主要代码。

import os
import numpy as np
import tensorflow as tf
from datetime import datetime
from alexnet_flower import AlexNet
from datagenerator import ImageDataGenerator

from scipy.misc import imread
from scipy.misc import imresize
import time
import matplotlib.image as mpimg
from scipy.ndimage import filters
import urllib
from numpy import random
from numpy import *
import os
from pylab import *
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook

from tensorflow.core.protobuf import saver_pb2

im1 = (imread("one.png")[:,:,:3]).astype(float32)
#print(im1.shape())
im1 = im1 - mean(im1)
#im1 = imresize(im1,[227,227,3])
im1[:, :, 0], im1[:, :, 2] = im1[:, :, 2], im1[:, :, 0]

im2 = (imread("two.png")[:,:,:3]).astype(float32)
im2 = im2 - mean(im2)
#im2 = imresize(im2,[227,227,3])
im2[:, :, 0], im2[:, :, 2] = im2[:, :, 2], im2[:, :, 0]

"""
Configuration settings
"""

print(im1.shape)
num_classes  = 5
x = tf.placeholder(tf.float32, [2, 227, 227, 3])
#y = tf.placeholder(tf.float32, [None, num_classes])
keep_prob = tf.placeholder(tf.float32)

#print(x)

# Initialize model
model = AlexNet(x,keep_prob,num_classes)

# Link variable to model output
score = model.fc8

saver = tf.train.Saver(write_version = saver_pb2.SaverDef.V1)

#x1 = tf.placeholder(tf.float32, (None,) + xdim)

with tf.Session() as sess:

  # Initialize all variables
  sess.run(tf.global_variables_initializer())

  # Add the model graph to TensorBoard

  # Load the pretrained weights into the non-trainable layer
  saver.restore(sess,"/home/saurabh/deep_learning/tests/finetune_alexnet_with_tensorflow/model_epoch1.ckpt")
 # x1:[im1,im2]
  print('error!!!!!!')

  output = sess.run(score, feed_dict = {x:[im1,im2]})

我在alexnet使用此代码的代码。我认为alexnet代码没有问题，因为我使用这段代码进行了微调。

最后我收到了这个错误。我试了很多调试它，我无法理解这个问题。谢谢你的帮助。

   Traceback (most recent call last):
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1021, in _do_call
    return fn(*args)
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1003, in _run_fn
    status, run_metadata)
  File "/home/saurabh/anaconda3/lib/python3.6/contextlib.py", line 89, in __exit__
    next(self.gen)
  File "/home/saurabh/anaconda3/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 "finetune_prediction_flowers.py", line 81, in <module>
    output = sess.run(score, feed_dict = {x:[im1,im2]})
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 766, in run
    run_metadata_ptr)
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 964, in _run
    feed_dict_string, options, run_metadata)
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1014, in _do_run
    target_list, options, run_metadata)
  File "/home/saurabh/anaconda3/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 "finetune_prediction_flowers.py", line 56, in <module>
    keep_prob = tf.placeholder(tf.float32)
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1587, in placeholder
    name=name)
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 2043, in _placeholder
    name=name)
  File "/home/saurabh/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
    op_def=op_def)
  File "/home/saurabh/anaconda3/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 "/home/saurabh/anaconda3/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"]()]]

Answer 1

错误信息非常清楚：

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"]()]]

含义：您必须向占位符keep_prob提供值，因为您在致电score时请求sess.run，而keep_prob则要求with tf.Session() as sess: # Load the pretrained weights into the non-trainable layer saver.restore(sess,"/home/saurabh/deep_learning/tests/finetune_alexnet_with_tensorflow/model_epoch1.ckpt") output = sess.run(score, feed_dict = {x:[im1,im2], keep_prob: 0.8})拥有值。因此，只需将保持概率设置为您想要的值（例如0.8）：

sess.run(tf.global_variables_initializer())

顺便说一句：如果您要从检查点恢复，则无需拨打else if(array[b]==2&&done2=false)

tensorflow占位符出错。

1 个答案: