我有一个卷积神经网络的以下代码部分:
import numpy as np
import matplotlib.pyplot as plt
import cifar_tools
import tensorflow as tf
data, labels = cifar_tools.read_data('C:\\Users\\abc\\Desktop\\temp')
x = tf.placeholder(tf.float32, [None, 150 * 150])
y = tf.placeholder(tf.float32, [None, 2])
w1 = tf.Variable(tf.random_normal([5, 5, 1, 64]))
b1 = tf.Variable(tf.random_normal([64]))
w2 = tf.Variable(tf.random_normal([5, 5, 64, 64]))
b2 = tf.Variable(tf.random_normal([64]))
w3 = tf.Variable(tf.random_normal([6*6*64, 1024]))
b3 = tf.Variable(tf.random_normal([1024]))
w_out = tf.Variable(tf.random_normal([1024, 2]))
b_out = tf.Variable(tf.random_normal([2]))
def conv_layer(x,w,b):
conv = tf.nn.conv2d(x,w,strides=[1,1,1,1], padding = 'SAME')
conv_with_b = tf.nn.bias_add(conv,b)
conv_out = tf.nn.relu(conv_with_b)
return conv_out
def maxpool_layer(conv,k=2):
return tf.nn.max_pool(conv, ksize=[1,k,k,1], strides=[1,k,k,1], padding='SAME')
def model():
x_reshaped = tf.reshape(x, shape=[-1,150,150,1])
conv_out1 = conv_layer(x_reshaped, w1, b1)
maxpool_out1 = maxpool_layer(conv_out1)
norm1 = tf.nn.lrn(maxpool_out1, 4, bias=1.0, alpha=0.001/9.0, beta=0.75)
conv_out2 = conv_layer(norm1, w2, b2)
maxpool_out2 = maxpool_layer(conv_out2)
norm2 = tf.nn.lrn(maxpool_out2, 4, bias=1.0, alpha=0.001/9.0, beta=0.75)
maxpool_reshaped = tf.reshape(maxpool_out2, [-1,w3.get_shape().as_list()[0]])
local = tf.add(tf.matmul(maxpool_reshaped, w3), b3)
local_out = tf.nn.relu(local)
out = tf.add(tf.matmul(local_out, w_out), b_out)
return out
model_op = model()
cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(model_op, y))
train_op = tf.train.AdamOptimizer(learning_rate=0.001).minimize(cost)
correct_pred = tf.equal(tf.argmax(model_op, 1), tf.argmax(y,1))
accuracy = tf.reduce_mean(tf.cast(correct_pred,tf.float32))
我正在阅读150x150灰度图像,但无法理解我遇到的以下错误:
EPOCH 0
Traceback (most recent call last):
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1021, in _do_call
return fn(*args)
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1003, in _run_fn
status, run_metadata)
File "C:\Python35\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "C:\Python35\lib\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: Input to reshape is a tensor with 92416 values, but the requested shape requires a multiple of 2304
[[Node: Reshape_1 = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](MaxPool_1, Reshape_1/shape)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "cnn.py", line 70, in
_, accuracy_val = sess.run([train_op, accuracy], feed_dict={x: batch_data, y: batch_onehot_vals})
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 766, in run
run_metadata_ptr)
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 964, in _run
feed_dict_string, options, run_metadata)
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1014, in _do_run
target_list, options, run_metadata)
File "C:\Python35\lib\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: Input to reshape is a tensor with 92416 values, but the requested shape requires a multiple of 2304
[[Node: Reshape_1 = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](MaxPool_1, Reshape_1/shape)]]
Caused by op 'Reshape_1', defined at:
File "cnn.py", line 50, in
model_op = model()
File "cnn.py", line 43, in model
maxpool_reshaped = tf.reshape(maxpool_out2, [-1,w3.get_shape().as_list()[0]])
File "C:\Python35\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 2448, in reshape
name=name)
File "C:\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 759, in apply_op
op_def=op_def)
File "C:\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2240, in create_op
original_op=self._default_original_op, op_def=op_def)
File "C:\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1128, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 92416 values, but the requested shape requires a multiple of 2304
[[Node: Reshape_1 = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](MaxPool_1, Reshape_1/shape)]]
编辑-1
根据这些编辑修改后出现此新错误:
x_reshaped = tf.reshape(x, shape=[-1,150,150,1]) batch_size = x_reshaped.get_shape().as_list()[0] ... Same code as above ... maxpool_reshaped = tf.reshape(maxpool_out2, [batch_size, -1])
错误:
Traceback (most recent call last): File "cnn.py", line 52, inmodel_op = model() File "cnn.py", line 45, in model maxpool_reshaped = tf.reshape(maxpool_out2, [batch_size, -1]) File "C:\Python35\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 2448, in reshape name=name) File "C:\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 493, in apply_op raise err File "C:\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 490, in apply_op preferred_dtype=default_dtype) File "C:\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 669, in convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "C:\Python35\lib\site-packages\tensorflow\python\framework\constant_op.py", line 176, in _constant_tensor_conversion_function return constant(v, dtype=dtype, name=name) File "C:\Python35\lib\site-packages\tensorflow\python\framework\constant_op.py", line 165, in constant tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape)) File "C:\Python35\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 441, in make_tensor_proto tensor_proto.string_val.extend([compat.as_bytes(x) for x in proto_values]) File "C:\Python35\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 441, in tensor_proto.string_val.extend([compat.as_bytes(x) for x in proto_values]) File "C:\Python35\lib\site-packages\tensorflow\python\util\compat.py", line 65, in as_bytes (bytes_or_text,)) TypeError: Expected binary or unicode string, got None
编辑-2
执行以下编辑后(除了删除batch_size:
w3 = tf.Variable(tf.random_normal([361, 256])) ... ... w_out = tf.Variable(tf.random_normal([256, 2]))
我有以下错误:
EPOCH 0
W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:975] Invalid argument: logits and labels must be same size: logits_size=[256,2] labels_size=[1,2]
[[Node: SoftmaxCrossEntropyWithLogits = SoftmaxCrossEntropyWithLogits[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Reshape_2, Reshape_3)]]
Traceback (most recent call last):
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1021, in _do_call
return fn(*args)
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1003, in _run_fn
status, run_metadata)
File "C:\Python35\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "C:\Python35\lib\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: logits and labels must be same size: logits_size=[256,2] labels_size=[1,2]
[[Node: SoftmaxCrossEntropyWithLogits = SoftmaxCrossEntropyWithLogits[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Reshape_2, Reshape_3)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "cnn.py", line 73, in
_, accuracy_val = sess.run([train_op, accuracy], feed_dict={x: batch_data, y: batch_onehot_vals})
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 766, in run
run_metadata_ptr)
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 964, in _run
feed_dict_string, options, run_metadata)
File "C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1014, in _do_run
target_list, options, run_metadata)
File "C:\Python35\lib\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: logits and labels must be same size: logits_size=[256,2] labels_size=[1,2]
[[Node: SoftmaxCrossEntropyWithLogits = SoftmaxCrossEntropyWithLogits[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Reshape_2, Reshape_3)]]
Caused by op 'SoftmaxCrossEntropyWithLogits', defined at:
File "cnn.py", line 55, in
cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(model_op, y))
File "C:\Python35\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 1449, in softmax_cross_entropy_with_logits
precise_logits, labels, name=name)
File "C:\Python35\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 2265, in _softmax_cross_entropy_with_logits
features=features, labels=labels, name=name)
File "C:\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 759, in apply_op
op_def=op_def)
File "C:\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2240, in create_op
original_op=self._default_original_op, op_def=op_def)
File "C:\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1128, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): logits and labels must be same size: logits_size=[256,2] labels_size=[1,2]
[[Node: SoftmaxCrossEntropyWithLogits = SoftmaxCrossEntropyWithLogits[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Reshape_2, Reshape_3)]]
编辑-3
这是二进制(pickle)文件的样子[label,filename,data]:
[array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), array(['1.jpg', '10.jpg', '2.jpg', '3.jpg', '4.jpg', '5.jpg', '6.jpg',
'7.jpg', '8.jpg', '9.jpg'],
dtype='
我该如何解决这个问题？
谢谢.
1> 小智..：
让我们来看你原来的错误:
重塑的输入是具有92416值的张量,但是所请求的形状需要2304的倍数
这是因为您使用原始输入图像大小为24*24的代码调整代码.两个卷积和两个最大汇集层之后的张量形状是[-1,6,6,64].但是,当您的输入图像形状为150*150时,中间形状变为[-1,38,38,64].
尝试改变w3
w3 = tf.Variable(tf.random_normal([38*38*64,1024]))
你应该时刻注意你的张量形状流动.
2> Steven..：
错误发生在这里：
maxpool_reshaped = tf.reshape(maxpool_out2, [-1,w3.get_shape().as_list()[0]])
声明如下：整形的输入是具有92416值的张量，但请求的形状需要2304的倍数
含义
w3.get_shape（）。as_list（）[0] = 2304
和
maxpool_out2具有92416值
但是92416/2304的剩余分数很小，因此python无法将其余部分均匀地放入“ -1”中。
因此，您需要重新检查w3的形状以及期望的形状。
替代建议更新：
x_reshaped = tf.reshape(x, shape=[-1,150,150,1])
batch_size = x_reshaped.get_shape().as_list()[0]
... Same code as above ...
maxpool_reshaped = tf.reshape(maxpool_out2, [batch_size, -1])
京公网安备 11010802040832号 | 京ICP备19059560号-6 