Question

火车图像集40的长度 X_train形状：（40、32、32、3） y_train形状：（40，）我收到这个错误：无法为张量为'（1，32，32，3）'的张量'Placeholder_17：0'输入形状（40，32，32，3）的值

x = tf.placeholder(dtype=tf.float32, shape=[1, 32, 32, 3])

c1 = tf.layers.conv2d(inputs=x, activation=tf.nn.relu, filters=32, 
kernel_size=[5,5], padding='VALID', strides=1)
p1 = tf.layers.max_pooling2d(inputs=c1, pool_size=[2,2], strides=2)

c2 = tf.layers.conv2d(inputs=p1, activation=tf.nn.relu, filters=64, 
kernel_size=[5,5], padding='VALID', strides=1)
p2 = tf.layers.max_pooling2d(inputs=c2, pool_size=[2,2], strides=2)

f = tf.contrib.layers.flatten(p2) 

fc1 = tf.layers.dense(inputs=f, units=64, activation=tf.nn.relu) 

logits = tf.layers.dense(inputs = fc1, units=2)

tf.layers.dropout(inputs = fc1, rate = 0.4) 



epochs = 50

for i in range(epochs):
    sess.run([trainer], feed_dict={x:X_train/255., y:y_train})
    [acc, l] = sess.run([accuracy, loss], feed_dict={x:X_train/255., y:y_train})
    print('Epoch %d - Loss: | %.2f Accuracy: %.2f'%(i,np.mean(l),acc))

Answer 1

您需要使占位符尺寸和输入尺寸匹配。因此，您将必须将placeholder_17设置为(40, 32, 32, 3)或以尺寸(1, 32, 32, 3)迭代地将每个图像馈入placeholder_17。

Tensorflow图像重塑

1 个答案: