代码无法正常运行我是一个深度学习和Python的初学者，这是我的卷积神经网络的代码。我完全无法理解这个错误，并且语法上看起来没有任何问题。

#!/usr/bin/env python3# -*- coding: utf-8 -*-"""Created on Thu Apr 20 17:23:07 2017@author: gengyoung"""from tensorflow.examples.tutorials.mnist import input_dataimport tensorflow as tfmnist = input_data.read_data_sets("MNIST_data/",one_hot=True)sess = tf.InteractiveSession()def weights(shape):    return tf.Variable(tf.truncated_normal(shape,stddev=0.1))def biases(shape):    return tf.Variable(tf.constant(0.1,shape=shape))def conv2d(X,W):    return tf.nn.conv2d(X,W,[1,1,1,1],padding='SAME')def max_pool_2x2(X):    return tf.nn.max_pool(X,[1,2,2,1],[1,1,1,1],padding='SAME')X = tf.placeholder(dtype=tf.float32,shape=[None,784])y = tf.placeholder(dtype=tf.float32,shape=[None,10])keep_prob = tf.placeholder(tf.float32)X_train = tf.reshape(X,[-1,28,28,1])w1 = weights([5,5,1,32])b1 =biases([32])conv1 = tf.nn.relu(conv2d(X_train,w1)+b1)pool1 = max_pool_2x2(conv1)w2 = weights([5,5,32,64])b2 = biases([64])conv2 = tf.nn.relu(conv2d(pool1,w2)+b2)pool2 = max_pool_2x2(conv2)f_w1 = weights([7*7*64,1024])f_b1 = biases([1024])f_w2 = weights([1024,10])f_b2 = biases([10])flatten_pool2 = tf.reshape(pool2,[-1,7*7*64])h1 = tf.nn.relu(tf.matmul(flatten_pool2,f_w1)+f_b1)h1_drop = tf.nn.dropout(h1,keep_prob)predict_y = tf.nn.softmax(tf.matmul(h1_drop,f_w2)+f_b2)cross_entropy = tf.reduce_mean(-tf.reduce_sum(y*tf.log(predict_y),reduction_indices=[1]))train_step = tf.train.AdamOptimizer(0.0001).minimize(cross_entropy)corrct_prediction = tf.equal(tf.argmax(predict_y,1),tf.argmax(y,1))accuracy = tf.reduce_mean(tf.cast(corrct_prediction,tf.float32))tf.global_variables_initializer().run()for i in range(2000):    batch = mnist.train.next_batch(50)    if i%100 == 0:        train_accuracy = accuracy.eval(feed_dict={X:batch[0],y:batch[1],keep_prob:1.0})        print("step:%04d accuracy:%.9f"%(i,train_accuracy))    train_step.run(feed_dict={X:batch[0],y:batch[1],keep_prob:0.5})print("Test accuracy: %.9f"%accuracy.eval(feed_dict={X:mnist.test.images,y:mnist.test.labels,                                           keep_prob:1.0}))

接下来是错误信息：

Python 3.6.0 |Anaconda custom (x86_64)| (default, Dec 23 2016, 13:19:00) [GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] on darwinType "help", "copyright", "credits" or "license" for more information.>>> runfile('/Users/gengyoung/CNN.py', wdir='/Users/gengyoung')Extracting MNIST_data/train-images-idx3-ubyte.gzExtracting MNIST_data/train-labels-idx1-ubyte.gzExtracting MNIST_data/t10k-images-idx3-ubyte.gzExtracting MNIST_data/t10k-labels-idx1-ubyte.gzW tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.Traceback (most recent call last):  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1022, in _do_call    return fn(*args)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1004, in _run_fn    status, run_metadata)  File "/anaconda/lib/python3.6/contextlib.py", line 89, in __exit__    next(self.gen)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status    pywrap_tensorflow.TF_GetCode(status))tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [800] vs. [50]     [[Node: Equal = Equal[T=DT_INT64, _device="/job:localhost/replica:0/task:0/cpu:0"](ArgMax, ArgMax_1)]]During handling of the above exception, another exception occurred:Traceback (most recent call last):  File "<stdin>", line 1, in <module>  File "/anaconda/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 866, in runfile    execfile(filename, namespace)  File "/anaconda/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 102, in execfile    exec(compile(f.read(), filename, 'exec'), namespace)  File "/Users/gengyoung/CNN.py", line 50, in <module>    train_accuracy = accuracy.eval(feed_dict={X:batch[0],y:batch[1],keep_prob:1.0})  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 567, in eval    return _eval_using_default_session(self, feed_dict, self.graph, session)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3729, in _eval_using_default_session    return session.run(tensors, feed_dict)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 767, in run    run_metadata_ptr)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 965, in _run    feed_dict_string, options, run_metadata)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1015, in _do_run    target_list, options, run_metadata)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1035, in _do_call    raise type(e)(node_def, op, message)tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [800] vs. [50]     [[Node: Equal = Equal[T=DT_INT64, _device="/job:localhost/replica:0/task:0/cpu:0"](ArgMax, ArgMax_1)]]Caused by op 'Equal', defined at:  File "<stdin>", line 1, in <module>  File "/anaconda/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 866, in runfile    execfile(filename, namespace)  File "/anaconda/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 102, in execfile    exec(compile(f.read(), filename, 'exec'), namespace)  File "/Users/gengyoung/CNN.py", line 44, in <module>    corrct_prediction = tf.equal(tf.argmax(predict_y,1),tf.argmax(y,1))  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py", line 721, in equal    result = _op_def_lib.apply_op("Equal", x=x, y=y, name=name)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op    op_def=op_def)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2327, in create_op    original_op=self._default_original_op, op_def=op_def)  File "/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1226, in __init__    self._traceback = _extract_stack()InvalidArgumentError (see above for traceback): Incompatible shapes: [800] vs. [50]     [[Node: Equal = Equal[T=DT_INT64, _device="/job:localhost/replica:0/task:0/cpu:0"](ArgMax, ArgMax_1)]]

回答：

你的最大池化函数的滑动窗口步长返回了一个不同形状的张量，导致乘到预测时产生了错误。将其更改为

def max_pool_2x2(X):        return tf.nn.max_pool(X,[1,2,2,1],[1,2,2,1],padding='SAME')

以便与你的代码保持一致。

我还建议你查看一些关于卷积和最大池化的解释和实现，比如这个，以便了解如何为你的代码进行修改。