convolutional: import?os import?model import?tensorflow?as?tf import?input_data data=input_data.read_data_sets('MINST_data',one_hot=True) with?tf.variable_scope("convolutional"): ????x=tf.placeholder(tf.float32,[None,784],name="x") ????keep_prob=tf.placeholder(tf.float32) ????y,variables=model.convolutional(x,keep_prob) y_=tf.placeholder(tf.float32,[None,10],name='y') cross_entropy=-tf.reduce_sum(y_*tf.log(y)) train_step=tf.train.AdamOptimizer(1e-4).minimize(cross_entropy) correct_prediction=tf.equal(tf.argmax(y,1),tf.argmax(y_,1)) accuracy=tf.reduce_mean(tf.cast(correct_prediction,tf.float32)) saver=tf.train.Saver(variables) with?tf.Session()?as?sess: ????merged_summary_op=tf.summary.merge_all() ????summay_writer=tf.summary.FileWriter('/tmp/mnist_log/1',sess.graph) ????summay_writer.add_graph(sess.graph) ????sess.run(tf.global_variables_initializer()) ????for?i?in?range(20000): ????????batch=data.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?%d,?training?accuracy?%g"%(i,train_accuracy)) ????????sess.run(train_step,feed_dict={x:batch[0],y_:batch[1],keep_prob:0.5}) ????print(sess.run(accuracy,feed_dict={x:data.test.images,y_:data.test.labels,keep_prob:1.0})) ????path=saver.save( ????????sess,os.path.join(os.path.dirname(__file__),'data','convolutional.ckpt'), ????????write_meta_graph=False,write_state=False) ????print("Saved:",path) ???? ????model: ????import?tensorflow?as?tf def?regression(x): ????W=tf.Variable(tf.zeros([784,10]),name="W") ????b=tf.Variable(tf.zeros([10]),name="b") ????y=tf.nn.softmax(tf.matmul(x,W)+b) ????return?y,[W,b] def?convolutional(x,keep_prob): ????def?conv2d(x,W): ????????return?tf.nn.conv2d([1,1,1,1],padding="SAME") ????def?max_pool_2x2(x): ????????return?tf.nn.max_pool(x,ksize=[1,2,2,1],strides=[1,2,2,1]) ????def?weight_variable(shape): ????????initial=tf.truncated_normal(shape,stddev=0.1) ????????return?tf.Variable(initial) ????def?bias_variable(shape): ????????initial=tf.constant(0.1,shape=shape) ????????return?tf.Variable(initial) ????x_image=tf.reshape(x,[-1,28,28,1]) ????W_conv1=weight_variable([5,5,1,32]) ????b_conv1=bias_variable([32]) ????h_convl=tf.nn.relu(conv2d(x_image,W_conv1)+b_conv1) ????h_pool1=max_pool_2x2(h_convl) ????W_conv2?=?weight_variable([5,?5,?32,?64]) ????b_conv2?=?bias_variable([64]) ????h_conv2?=?tf.nn.relu(conv2d(h_pool1,?W_conv2)?+?b_conv2) ????h_pool2?=?max_pool_2x2(h_conv2) ????W_fc1=weight_variable([7*7*64,1024]) ????b_fc1=bias_variable([1024]) ????h_pool2_flat=tf.reshape(h_pool2,[-1,7*7*64]) ????h_fc1=tf.nn.relu(tf.matmul(h_pool2_flat,W_fc1)+b_fc1) ????h_fc1_drop=tf.nn.dropout(h_fc1,keep_prob) ????W_fc2=weight_variable([1024,10]) ????b_fc2=bias_variable([10]) ????y=tf.nn.softmax(tf.matmul(h_fc1_drop,W_fc2)+b_fc2) ????return?y,[W_conv1,b_conv1,W_conv2,b_conv2,W_fc1,b_fc1,W_fc2,b_fc2] ???? ???? ???? ????報錯如下： ???? ???? ???? ????WARNING:tensorflow:From?D:\Python\workspace\Pybasis\minist\model.py:17:?The?name?tf.truncated_normal?is?deprecated.?Please?use?tf.random.truncated_normal?instead.Traceback?(most?recent?call?last):??File?"D:/Python/workspace/Pybasis/minist/convolutional.py",?line?11,?in?<module>????y,variables=model.convolutional(x,keep_prob)??File?"D:\Python\workspace\Pybasis\minist\model.py",?line?26,?in?convolutional????h_convl=tf.nn.relu(conv2d(x_image,W_conv1)+b_conv1)??File?"D:\Python\workspace\Pybasis\minist\model.py",?line?12,?in?conv2d????return?tf.nn.conv2d([1,1,1,1],padding="SAME")??File?"D:\Python\Anaconda3\lib\site-packages\tensorflow\python\ops\nn_ops.py",?line?1953,?in?conv2d????name=name)??File?"D:\Python\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py",?line?1070,?in?conv2d????data_format=data_format,?dilations=dilations,?name=name)??File?"D:\Python\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py",?line?626,?in?_apply_op_helper????param_name=input_name)??File?"D:\Python\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py",?line?60,?in?_SatisfiesTypeConstraint????",?".join(dtypes.as_dtype(x).name?for?x?in?allowed_list)))TypeError:?Value?passed?to?parameter?'input'?has?DataType?int32?not?in?list?of?allowed?values:?float16,?bfloat16,?float32,?float64Process?finished?with?exit?code?1