Question

我在MNIST数据集上训练了一个带有TensorFlow的简单神经网络。代码的训练部分工作正常。但是，当我将单个图像输入网络时，它会给我以下追溯：

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"]()]]

以下是我的变数：

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

这是我尝试输入单个数字（从数据集中随机选择）的地方：

#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)

任何帮助将不胜感激！我是TensorFlow的新手。

Answer 1

您的feed_dict仅为x而不是标签的值。你也应该为y place_holder投注，即：{x：image，y：val}

Answer 2

在您的代码中y是占位符：

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

当你告诉tensorflow sess.run(y, ...)时，它会计算占位符值，而不是推理值（这是y在损失函数中与之比较的张量）。这就是为什么它会抱怨。

您想要计算的是预测y值。它不在您的代码段中，但由于培训有效，因此应该有一个。这个张量取决于x，因此可以通过提供x值来评估它。

InvalidArgumentError：您必须为占位符张量'Placeholder_1'提供值

2 个答案: