gradle预编译SpringSource项目失败

Question

我刚从t.isValid()克隆了Spring Source，我想把它导入到我的想法中。 根据文件# Import MNIST data #import input_data #mnist = input_data.read_data_sets("/tmp/data/", one_hot=True) from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) import tensorflow as tf # Set parameters learning_rate = 0.01 training_iteration = 30 batch_size = 100 display_step = 2 # TF graph input x = tf.placeholder("float", [None, 784]) # mnist data image of shape 28*28=784 y = tf.placeholder("float", [None, 10]) # 0-9 digits recognition => 10 classes # Create a model # Set model weights W = tf.Variable(tf.zeros([784, 10])) b = tf.Variable(tf.zeros([10])) with tf.name_scope("Wx_b") as scope: # Construct a linear model model = tf.nn.softmax(tf.matmul(x, W) + b) # Softmax # Add summary ops to collect data w_h = tf.summary.histogram("weights", W) b_h = tf.summary.histogram("biases", b) # More name scopes will clean up graph representation with tf.name_scope("cost_function") as scope: # Minimize error using cross entropy # Cross entropy cost_function = -tf.reduce_sum(y*tf.log(model)) # Create a summary to monitor the cost function tf.summary.scalar("cost_function", cost_function) with tf.name_scope("train") as scope: # Gradient descent optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost_function) # Initializing the variables init = tf.initialize_all_variables() # Merge all summaries into a single operator merged_summary_op = tf.summary.merge_all() # Launch the graph with tf.Session() as sess: sess.run(init) summary_writer = tf.summary.FileWriter('/home/raed/Tensorflow/tensorflow_demo', graph_def=sess.graph_def) # Training cycle for iteration in range(training_iteration): avg_cost = 0. total_batch = int(mnist.train.num_examples/batch_size) # Loop over all batches for i in range(total_batch): batch_xs, batch_ys = mnist.train.next_batch(batch_size) # Fit training using batch data sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys}) # Compute the average loss avg_cost += sess.run(cost_function, feed_dict={x: batch_xs, y: batch_ys})/total_batch # Write logs for each iteration summary_str = sess.run(merged_summary_op, feed_dict={x: batch_xs, y: batch_ys}) summary_writer.add_summary(summary_str, iteration*total_batch + i) # Display logs per iteration step if iteration % display_step == 0: print ("Iteration:" "%04d" % (iteration + 1), "cost=", "{:.9f}".format(avg_cost)) print ("Tuning completed!") # Test the model predictions = tf.equal(tf.argmax(model, 1), tf.argmax(y, 1)) # Calculate accuracy accuracy = tf.reduce_mean(tf.cast(predictions, "float")) print ("Accuracy:", accuracy.eval({x: mnist.test.images, y: mnist.test.labels})) ，我运行了命令：git://github.com/SpringSource/Spring-framework.git，但它失败并出现异常：

有人会告诉我为什么会这样吗？以及如何解决..非常感谢！