第一次遇到这样的问题。测试 tflearn 的神经网络给出错误。尝试测试此代码时，Python 会生成错误。用 conv_2d 就没有这样的问题。
我的代码：
import numpy as np
import random
import tflearn
from tflearn.layers.core import input_data, dropout, fully_connected
from tflearn.layers.conv import conv_3d, max_pool_3d
from tflearn.layers.estimator import regression
trainX = [[[random.randint(0,3) for col in range(15)] for row in range(15)] for x in range(50)]
testX = [[[random.randint(0,3) for col in range(15)] for row in range(15)] for x in range(10)]
trainY = [[0,1] for x in range(100)]
testY = [[0,1] for x in range(10)]
idnn = 'test_cnn'
network = input_data(shape=[None, 15, 15,15, 1])
network = conv_3d(network, 10, 3, activation='relu')
network = max_pool_3d(network, 2)
network = conv_3d(network, 32, 3, activation='relu')
network = conv_3d(network, 32, 3, activation='relu')
network = max_pool_3d(network, 2)
network = fully_connected(network, 512, activation='relu')
network = dropout(network, 0.5)
network = fully_connected(network, 2, activation='softmax')
network = regression(network, optimizer='adam',
loss='categorical_crossentropy',
learning_rate=0.001)
# Train using classifier
model = tflearn.DNN(network, tensorboard_verbose=0)
model.fit(trainX, trainY, n_epoch=10, shuffle=True, validation_set=(testX, testY),
show_metric=True, batch_size=5, run_id= idnn)
pred = model.predict(testX)
这在尝试测试代码时会出现错误 tflearn。
ValueError：无法为张量“InputData/X:0”提供形状（50、15、15）的值，其形状为“（？、15、15、15、1）”
可能是什么问题呢 ？请有人帮忙。