问题描述
嗨。我是Tensorflow的新手，正在尝试使用CNN运行cifar10数据集。
我的网络由三层构成，例如
- 卷积+最大池化
- 完全连接的层
- Softmax层
以下是我的张量流模型代码。
15 def model(X, w, w2, w_o, p_keep_conv, p_keep_hidden):
16
17 layer1 = tf.nn.relu(tf.nn.conv2d(X, w,strides=[1, 1, 1, 1], padding='SAME'))
18 layer1 = tf.nn.max_pool(l1, ksize=[1, 2, 2, 1],strides=[1, 2, 2, 1], padding='SAME')
19
20 layer1 = tf.reshape(l1,[-1,w2.get_shape().as_list()[0]])
21 layer1 = tf.nn.dropout(l1, p_keep_conv)
22
23 layer2 = tf.nn.relu(tf.matmul(layer1, w2))
24 layer2 = tf.nn.dropout(l4, p_keep_hidden)
25
26 pyx = tf.matmul(layer2, w_o)
27 return pyx
28
输入的图像具有[-1、32、32、3]形状。（32 * 32像素，RGB）
由于最大池化的过滤器为[1,2,2,1]，因此跨度为[1,2,2,1]，输出通道为5，
我认为最大池化层和完全连接层之间的权重形式（以下代码中的w2）应为[5 * 16 * 16 * 3，125]。
（5：通道，16：32/2像素，3：RGB，125：输出＃神经元）
以下是我的参数张量流代码。
60 trX = trX.reshape(-1, 32, 32, 3) # 32x32x3 input img
61 teX = teX.reshape(-1, 32, 32, 3) # 32x32x3 input img
62
63 X = tf.placeholder("float", [None, 32, 32, 3])
64 Y = tf.placeholder("float", [None, 10])
65
66 w = init_weights([5, 5, 3, 5])
67 w2 = init_weights([5*16*16*3, 125])
68 w_o = init_weights([125, 10])
69
70 p_keep_conv = tf.placeholder("float")
71 p_keep_hidden = tf.placeholder("float")
72
73 py_x = model(X, w, w2, w_o, p_keep_conv, p_keep_hidden)
74
75 cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(py_x, Y))
76 #train_op = tf.train.RMSPropOptimizer(0.001, 0.9).minimize(cost)
77 train_op = tf.train.AdamOptimizer(1e-4).minimize(cost)
78 predict_op = tf.argmax(py_x, 1)
79
但是它向我显示如下错误。
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/client/session.py", line 715, in _do_call
return fn(*args)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/client/session.py", line 697, in _run_fn
status, run_metadata)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/contextlib.py", line 66, in __exit__
next(self.gen)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/framework/errors.py", line 450, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors.InvalidArgumentError: Input to reshape is a tensor with 6400 values, but the requested shape requires a multiple of 3840
[[Node: Reshape = Reshape[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](MaxPool, Reshape/shape)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "convCifar.py", line 99, in <module>
p_keep_conv: 0.8, p_keep_hidden: 0.5})
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/client/session.py", line 372, in run
run_metadata_ptr)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/client/session.py", line 636, in _run
feed_dict_string, options, run_metadata)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/client/session.py", line 708, in _do_run
target_list, options, run_metadata)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/client/session.py", line 728, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors.InvalidArgumentError: Input to reshape is a tensor with 6400 values, but the requested shape requires a multiple of 3840
[[Node: Reshape = Reshape[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](MaxPool, Reshape/shape)]]
Caused by op 'Reshape', defined at:
File "convCifar.py", line 82, in <module>
py_x = model(X, w, w4, w_o, p_keep_conv, p_keep_hidden)
File "convCifar.py", line 27, in model
l1 = tf.reshape(l1,[-1,w4.get_shape().as_list()[0]])
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1383, in reshape
name=name)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/ops/op_def_library.py", line 704, in apply_op
op_def=op_def)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/framework/ops.py", line 2260, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/tensorflow/python/framework/ops.py", line 1230, in __init__
self._traceback = _extract_stack()
I think the problem is about the dimension of "w2"(weight between max pooling layer and fully connected layer). Also, I can not understand How the 6400 can be occurred.
如何解决该错误？
如果信息量很小，请告诉我。
谢谢！
Please let me know if the information is small.Thank you!
推荐答案
错误 tensorflow.python.framework.errors.InvalidArgumentError：要重塑的输入是具有6400值的张量，但请求的形状需要3840的倍数。表明输入张量 tf.reshape（）第20行中的值不是3840的倍数。
The error tensorflow.python.framework.errors.InvalidArgumentError: Input to reshape is a tensor with 6400 values, but the requested shape requires a multiple of 3840 suggests that the input tensor of tf.reshape() in line 20 has a number of values that is not a multiple of 3840.
那是因为张量 l1 是' t在函数 model 中定义（您可能更早使用过，可能有6400个值）。您可能要设置 l1 = layer1 。请注意，在函数 model 中也未定义张量 l4 。
That's because tensor l1 isn't defined within function model (you might have used it earlier and it might have 6400 values). You probably want to set l1=layer1. Note that tensor l4 isn't defined in function model either.
请告诉我我的答案是否不能解决您的错误。
Please, let me know if my answer doesn't solve your error.
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